computer science thesis ppt

PhD Dissertation Defense Slides Design: Start

• Tips for designing the slides
• Presentation checklist
• Example slides
• Additional Resources

Purpose of the Guide

This guide was created to help ph.d. students in engineering fields to design dissertation defense presentations. the guide provides 1) tips on how to effectively communicate research, and 2) full presentation examples from ph.d. graduates. the tips on designing effective slides are not restricted to dissertation defense presentations; they can be used in designing other types of presentations such as conference talks, qualification and proposal exams, and technical seminars., the tips and examples are used to help students to design effective presentation. the technical contents in all examples are subject to copyright, please do not replicate. , if you need help in designing your presentation, please contact julie chen ([email protected]) for individual consultation. .

• Example Slides Repository
• Defense slides examples Link to examples dissertation defense slides.

Useful Links

• CIT Thesis and dissertation standards
• Dissertations and Theses @ Carnegie Mellon This link opens in a new window Covers 1920-present. Full text of some dissertations may be available 1997-present. Citations and abstracts of dissertations and theses CMU graduate students have published through UMI Dissertation Publishing. In addition to citations and abstracts, the service provides free access to 24 page previews and the full text in PDF format, when available. In most cases, this will be works published in 1997 forward.
• Communicate your research data Data visualization is very important in communicating your data effectively. Check out these do's and don'ts for designing figures.

Power Point Template and other Resources

• CEE Powerpoint Slide Presentation Template 1
• CEE Powerpoint Slide Presentation Template 2

Source: CEE Department Resources https://www.cmu.edu/cee/resources/index.html

• CMU Powerpoint Slide Template

Source: CMU Marketing and Communications

https://www.cmu.edu/marcom/brand-standards/downloads/index.html

• Use of CMU logos, marks, and Unitmarks

Email me for questions and schedule an appointment

Top 7 tips for your defense presentation

1. show why your study is important, remember, your audience is your committee members, researchers in other fields, and even the general public. you want to convince all of them why you deserve a ph.d. degree. you need to talk about why your study is important to the world. in the engineering field, you also need to talk about how your study is useful. try to discuss why current practice is problematic or not good enough, what needs to be solved, and what the potential benefits will be. , see how dr. posen and dr. malings explained the importance of their studies..

• Carl Malings Defense Slides with Notes
• I. Daniel Posen Defense Slides with Notes

2. Emphasize YOUR contribution 

Having a ph.d. means that you have made some novel contributions to the grand field. this is about you and your research. you need to keep emphasizing your contributions throughout your presentation. after talking about what needs to be solved, try to focus on emphasizing the novelty of your work. what problems can be solved using your research outcomes what breakthroughs have you made to the field why are your methods and outcomes outstanding you need to incorporate answers to these questions in your presentation. , be clear what your contributions are in the introduction section; separate what was done by others and what was done by you. , 3. connect your projects into a whole piece of work, you might have been doing multiple projects that are not strongly connected. to figure out how to connect them into a whole piece, use visualizations such as flow charts to convince your audience. the two slides below are two examples. in the first slide, which was presented in the introduction section, the presenter used a flow diagram to show the connection between the three projects. in the second slide, the presenter used key figures and a unique color for each project to show the connection..

• Xiaoju Chen Defense Slides with Notes

4. Tell a good story 

The committee members do not necessarily have the same background knowledge as you. plus, there could be researchers from other fields and even the general public in the room. you want to make sure all of your audience can understand as much as possible. focus on the big picture rather than technical details; make sure you use simple language to explain your methods and results. your committee has read your dissertation before your defense, but others have not. , dr. cook and dr. velibeyoglu did a good job explaining their research to everyone. the introduction sessions in their presentations are well designed for this purpose. .

• Laren M. Cook Defense Slides with Notes
• Irem Velibeyoglu Defense with Notes

5. Transition, transition, transition

Use transition slides to connect projects , it's a long presentation with different research projects. you want to use some sort of transition to remind your audience what you have been talking about and what is next. you may use a slide that is designed for this purpose throughout your presentation. , below are two examples. these slides were presented after the introduction section. the presenters used the same slides and highlighted the items for project one to indicate that they were moving on to the first project. throughout the presentation, they used these slides and highlighted different sections to indicate how these projects fit into the whole dissertation. .

You can also use some other indications on your slides, but remember not to make your slides too busy.  Below are two examples. In the first example, the presenter used chapter numbers to indicate what he was talking about. In the second example, the presenter used a progress bar with keywords for each chapter as the indicator. 

Use transition sentences to connect slides 

Remember transition sentences are also important; use them to summarize what you have said and tell your audience what they will expect next. if you keep forgetting the transition sentence, write a note on your presentation. you can either write down a full sentence of what you want to say or some keywords., 6. be brief, put details in backup slides , you won't have time to explain all of the details. if your defense presentation is scheduled for 45 minutes, you can only spend around 10 minutes for each project - that's shorter than a normal research conference presentation focus on the big picture and leave details behind. you can put the details in your backup slides, so you might find them useful when your committee (and other members of the audience) ask questions regarding these details., 7. show your presentation to your advisor and colleagues, make sure to ask your advisor(s) for their comments. they might have a different view on what should be emphasized and what should be elaborated. , you also want to practice at least once in front of your colleagues. they can be your lab mates, people who work in your research group, and/or your friends. they do not have to be experts in your field. ask them to give you some feedback - their comments can be extremely helpful to improve your presentation. , below are some other tips and resources to design your defense presentation. .

• Tips for designing your defense presentation

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• Last Updated: Jan 9, 2024 11:18 AM
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Home Blog Presentation Ideas How To Do a Proper Thesis Defense Using the Right PowerPoint Presentation

How To Do a Proper Thesis Defense Using the Right PowerPoint Presentation

Writing a thesis is stressful, but preparing an oral defense can be even more painful. But it doesn’t have to be; with proper preparation and a good presentation, you will be able to better equip yourself comes time to present your thesis defense.

But what makes a good thesis defense?

A proper presentation helps you with your thesis defense because it helps you capture the panels’ attention and gives you cues and reminders on what to say as well.

It also helps keep your data organized while visually looking good and provides a flow structure for the rest of your presentation.

In today’s article, we will be giving you The Right PowerPoint Templates for Your Thesis Defense and a powerful outline composed of best practices and layouts specifically designed to help you defend your thesis in both written and oral presentations.

In the next segments of this article, we’ll walk you through the most feasible process on how to ace this kind of presentation.

Let’s dive into the outline of what makes a great thesis defense.

Thesis Defense Overview

Similarities.

• Type of Degree

Thesis and Dissertation Distinction Varies on Location

Three most common thesis defense myths, how to use chatgpt to structure your thesis.

• Introduction
• Literature Review
• Methodology
• Acknowledgements
• Questions and Answers
• Contact Information
• Tips During Your Oral Defense
• More Quick Tips on How to Present

A thesis defense is composed of two parts – a thesis and a defense.

The thesis, according to Grad School Hub , represents a student’s collective understanding of his or her program and major.

Universities often include a thesis in every course as one of the final requirements to earn a particular graduate or postgraduate degree.

The thesis, however, isn’t just a mere requirement.

It helps the students to grow out of their shell from their respective discipline and give them the opportunity to present all the findings of their study.

Moreover, some people think a thesis is just a long essay, but it’s not. Unlike an essay, a thesis needs to assert something.

This can be considered one of the most crucial research documents that a student makes during their academic schooling .

On the other hand, defense is the presentation of the pieces of evidence to support and prove your research.

It’s the most essential part of the thesis process.

Your presentation has to be prepared to answer questions from members of the committee and any other panel present, and it’s your job to convince them and defend your thesis with ample proof.

Prior to presenting, you have to carefully determine what appropriate evidence should be presented before the panel, depending on what thesis you have to defend.

Thesis and Dissertation Distinguished

A thesis or dissertation is usually required to complete a particular graduate degree. These two words are often used interchangeably by most students when referring to research studies.

But while being almost similar in format or structure, it’s worth noting that they have significant differences that set them apart from each other.

The very reason why thesis and dissertation are treated the same is that these two are both extensive papers. Not just merely long essays like what others are claiming.

Both of these papers are extensive. This is why students are given ample time, usually the entire last semester of the last year of study, to complete all the requirements and finally acquire their degree.

With regards to structure, both papers are very similar with few differences.

Differences Between Thesis and Dissertation

One of the significant differences between the two is to whom the paper is assigned. A thesis is usually required for those students earning a bachelor’s or master’s degree. While a dissertation is for those, who want to obtain a doctorate degree.

However, not all students taking a master’s degree are required to make a thesis. Prior to their enrollment, they have been given a choice of whether they’ll go for a non-thesis program or with a thesis.

Those who have a plan to escalate their degree to a doctorate eventually should take the path of a thesis. This is to prepare themselves for a more extensive dissertation requirement as doctorate students. Otherwise, they will be only limited to earning a master’s degree.

But above all, the most significant difference between the two papers is the purpose for which it is written.

A thesis, like what has been mentioned above, is being done by students obtaining a bachelor’s or master’s degree and has the purpose of testing their understanding of the discipline they’re engaged with.

A thesis is focused on obtaining technical expertise.

On the other hand, a dissertation is made for students to come up with an original study that other researchers haven’t already studied.

USA: In the United States of America, they consider a thesis shorter than a dissertation. In fact, aside from being a requirement to graduate in college, a thesis is now also inculcated in master’s degree programs. And since the dissertation is more extensive, the thesis is treated as preliminary in gaining a doctorate degree.

Europe: The distinction between the two papers is almost opposite to that of the USA. In Europe, a dissertation is only a broader research study from a post-graduate program and not the making of original research. Instead, educational systems in the said continent treat the doctoral thesis as a more elaborate paper writing.

The difference between a thesis and a dissertation might not seem that big, but it’s important that we know what makes them different.

If your upcoming defense gives you pressure and uneasiness, it could be cause you are not sure what to expect. Today we will dispel three common thesis defense myths that will help you be more confident in your presentation.

“Answer all the questions correctly. Otherwise, your thesis won’t get approved.”

You are expected to have a focus on your research.

That being said, you have to study each part of your thesis, every detail, and even your sources.

You have to study and practice how to effectively deliver your presentation.

But don’t overthink to the extent that you’re stressing yourself to know everything perfectly.

Don’t overstress if you can’t answer one of the questions, this doesn’t necessarily mean the committee won’t approve your thesis.

You should know that research is a continuous study.

So you should expect that your committee will always be able to find a gap in your study to fill in future related research .

So in times you don’t exactly know the answer, admit it, and you’ll learn as they give their sides or suggestions.

Making up an answer will only displease your committee, so it’s to be upfront, honest, and transparent.

“The committee is just there to find holes in your study. They don’t care about you.”

One of the typical descriptions students have of the committee is that they are just there to poke holes in your thesis.

Going in with this perspective makes standing before them a nerve-wracking experience.

They’re not your enemy.

In fact, they are there to help you polish your study.

They might challenge you with difficult suggestions and tricky questions.

In the end, they will walk you through the process to come up with better results that won’t only benefit you but also your research.

They care about you and your study, and they’re ultimately there to make your thesis and the research better.  Separate yourself from your work look at it objectively, and don’t take their comments personally .

“If your thesis defense isn’t successful, you have to start your thesis all over again”

An unsuccessful defense is one of the worst-case fears most students have.

One thing that you should be aware of is when you aren’t able to please your committee, you don’t need to start a new thesis again or go back to square one with your existing paper.

It’s unusual that your committee will ask you to change your topic and start from scratch again.

The fact that you’ve been permitted to defend your study means your research is almost complete.

They might suggest further details or ask you for minor revisions, and that’s normal.

But overall, you need to go into this defense thinking that your presentation will be successful. Otherwise, you are already setting yourself up for failure with the wrong mindset.

Remember that positive thoughts attract positive results.

Thesis Defense Presentation Structure and Slides Content

We can use language learning models like ChatGPT to help us curate the structure of our thesis presentation. Let’s see a step-by-step solution on how to apply this.

Step 1: Define the thesis topic and research questions

You can set the environment for ChatGPT to work by explaining what your thesis is going to cover and which specific questions you aim to address through the course of that document. This gives ChatGPT the context from which it shall formulate the structure. A prompt can be written like this:

“Take the role of an academic professional who shall help me to write my thesis. This thesis is going to cover the topic of (insert topic), and through its course, I want to answer these questions: Question 1 – Question 2 – Question 3 – Consider this information as the starting point for this chat.”

Step 2: Ask for an outline

With the previously provided information, ask ChatGPT to generate an outline for your presentation. If some of the points listed in the output don’t convince you, then chat with the interface until you reach a final outline. Then, ask to elaborate on each specific point for information or cues you may have overlooked.

Step 3: Ask ChatGPT which content should you place per slide

Instead of debating how are you going to trim your thesis into a presentation format, ask ChatGPT to do the decision process for you. You can be as specific as asking how many words per slide, how many slides should the presentation have, if you need any visual element, etc.

N.B.: We don’t recommend using ChatGPT to retrieve academic references as, in some cases, it can provide faulty results. You can ask if any facts on this presentation need to be checked or similar questions. ChatGPT is a powerful tool, but it shouldn’t be considered a bible, so be extra cautious about grabbing content directly from its outputs.

1. Title Page

This slide should contain the information that is provided on the title page of your hard copy . Here is an example of title page or cover slide for your title defense or thesis presentation.

• The title of your research paper
• Where you are studying
• Name and details of your course
• Name of Adviser

2. Introduction Slide

Your introduction slide should provide the committee with an idea of the following:

• What is the topic area that you are investigating ?
• What are the specific research questions that you set out to answer?
• Why is this question important to answer?
• What were the objectives of your research?

3. Literature Review Slide

It’s not necessary to cover everything that’s currently understood in the available literature. You may want to present the following content under a Literature Review slide:

• Relevant current research that is close to your topic
• Different theories that may apply to your specific area of research
• Areas of weakness that are currently highlighted

4. Methodology Slide

Make sure to touch the factors below within your process, and include the following in the Methodology slide:

• The type of study you have conducted: qualitative, quantitative, or mixed
• The methods that you chose and why
• Details of the population, sampling methods, and other information
• Provide information regarding how you have analyzed the data that you have collected

5. Results Slide

This part should give the committee/audience a good understanding of what you’ve discovered during your research. The statistics & results slide could include the final results of your analysis, here is an example:

• An overall description of the data that you collected during your research
• The results of the analysis that you have done on that data
• What were the most significant findings from your data

6. Discussion Slide

Highlight here the meaning of the findings in relation to your discipline program and the research that you have done:

• What are the major findings, and what do they mean with regard to your research
• How do these findings relate to what others have found in the past
• How can you explain any unusual or surprising result

7. Conclusions Slide

You have to end your presentation with a conclusion summarizing all that you have found within your research. Here is an example of a Conclusion slide in a Thesis presentation:

• Restate your research questions
• Show how your results answer these questions
• Show what contribution you have made
• State any limitations to the work you have done
• Suggest future research
• Make any recommendations

See Also: How to Create a Great Investors Pitch Deck and Close the Deal

8. Acknowledgements Slide

Express gratitude to your advisor, committee members, peers, and others who supported your research journey. This slide provides a moment to acknowledge the collaborative nature of academic work.

9. Questions and Answers Slide

Dedicate a slide for audience questions at the end of your presentation.

Encourage engagement by inviting questions from the audience.

Be prepared to provide clear and concise responses to inquiries.

10. References Slide

Include a slide listing your cited sources throughout your presentation.

Use a consistent citation style (APA, MLA, Chicago, etc.).

The References slide demonstrates your thorough engagement with existing literature.

11. Contact Information Slide

If you’re open to further inquiries or collaborations, consider adding your contact information.

Include your email address or relevant professional social media handles.

How to use SlideModel AI Presentation Maker for your Thesis Presentation

If you want to save hours of manual time, you can leverage AI tools to make your thesis presentation. The best part of integrating AI tools into our workflow is that we can pair them to get even better results than we expected. With SlideModel’s AI presentation maker , users can create an entire slide deck by introducing these variables:

• Topic of your thesis
• Number of slides to include in your thesis presentation
• Outline checkup

And that’s it! Download the AI-generated presentation in PPTX format or for Google Slides, and edit it if you require adding some extra content. The core elements are already done, and you can save countless hours of hard work.

Tips During Your Oral Defense!

Review your materials.

Even if you already feel confident with your upcoming presentation, you still need to review your materials.

You can bring the hard copy of your thesis with you during the defense, but you don’t want to get lost in your presentation when you forget some specific details and have to scan your papers.

You should know your paper in and out.

Rehearse Your Presentation

It’s not wrong if it sounds like a script when you speak in your oral defense. It’s expected and understandable.

You need to practice your presentation, especially when there’s a time restriction given to every presenter.

You only need to prepare enough slides that would fit your time limit. A hundred slides aren’t suitable for a 15 to 20-minute presentation, nor 10 slides for an hour of defense.

Your rehearsal will be more effective if you practice it in front of an audience.

Note: You will experience complete silence in the defense room. You might feel awkward because, most of the time, you’re the only one speaking out loud.  This is completely fine, and it’s something you should practice in rehearsal should you be afraid.

Narrow the Presentation of Ideas

Regarding your slides, you don’t have to include everything that’s in your paper. You should narrow down your ideas to the main points and the most important details, such as the statistics and findings.

If the members of your committee think you lack details or they want to hear a further explanation, they won’t hesitate to ask you.

Prepare for the Unexpected Questions

The panel tends to challenge the presenters, usually through some hard questions.

Its aim is how well do you you have done your research and how prepared you are.

But as long as you know the ins and outs of your paper, you shouldn’t lose your confidence regardless of which questions they ask.

Just keep in mind that what you’re saying in your oral defense is not in conflict with what is written on the hard copy you provided them.

What To Do When You Don’t Know the Answer

If the committee asks you a question and you don’t know the answer, don’t make up a baseless answer.

Baseless means out-of-context answers or something without proof or backup.

How To Deal With The Nervousness

The committee expects you to be nervous. Of course, it’s normal.

However, one effect of being nervous is the changes in your behavior.

There’s a tendency for you’ll talk fast, which will make it hard for the committee to understand you.

It might also cause you to have a mental block.

So try to slow down. Take a deep breath.

Inhale, exhale.  Remember to breathe!

It’s OK to pause, and it’s OK to take your time; it’s more important that the committee clearly understands what you are trying to articulate.

More Quick Tips on How to Present!

• Introduce yourself at the beginning
• Introduce the title of the presentation
• Don’t read your notes if possible
• Don’t speak too fast
• Put an emphasis on what you’re saying so you don’t sound monotonous
• Look at your adviser once in a while for possible signs
• Stand on the right of the white screen if you are right-handed so you can easily refer to the slide without giving your back to the committee
• Face the audience when you talk
• Keep an eye contact
• Make sure to keep attention to the reactions of the committee and don’t forget to react in turn

We hope you enjoyed this article on how to do a proper thesis defense and how to best prepare for one using proven tips and techniques to help you get through this.  Hopefully, after your defense, you will be set as the one in your class to deliver an inspiring graduation speech for your peers. If you have value, please remember to share this article. We also recommend you read these Thesis Statement Examples for inspiration to create your own professionally.

1. MasterDoc PowerPoint Template

Creating a Thesis presentation should be a straight forward task; based on your thesis document and following the tips described above you have a high level structure already outlined. The MasterDoc PowerPoint template provides professional layouts with texts and image placeholders; so you can create document like slides using your thesis defense as your content. This template is ideal for a highly detailed documents, where visuals and words unite to illustrate one concept per page. The result is an asset that can be read and digested more quickly than either your thesis document or a presentation created for assisting a speech. A document created with the MasterDoc PowerPoint templates is meant to be printed or distributed, read on screen without the accompaniment of a presenter or used in an e-learning platform as pure learning content.

Use This Template

2. Thesis Presentation PowerPoint Template

You had invested a considerable time researching, testing hypothesis and confirming your thesis. Craft your thesis presentation with the same level of detail you applied in your work. Using the Thesis Presentation PowerPoint Template you will focus only in your content and your message. The layouts, images,design and structure will be taken care by the template.

3. Master Thesis PowerPoint Template

The Master Thesis PowerPoint Template is a professional document designed for postgraduate degrees presentations. It provides simple sections that follow  the structure and best practices of traditional research thesis presentations. Starting with the introduction to the theory and state of the art scenario; following with hypothesis research and its findings and concluding with the confirmation or negation of the initial thesis statement.

4. Essay Outline PowerPoint Template

Your thesis defense can be accompanied by an essay, that states your thesis and argues about it using several supporting paragraphs. This kind of document is ideal to be an intermediate step between reading assisting to the thesis presentation and reading the complete thesis documentation. It has more information that your thesis defense abstract, but does summarizes the supporting evidence and examples that allows the argument of each idea behind the thesis. You can use the Essay Outline Template to present your Essay outline and create an essay linked to your thesis defense documentation.

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Academics, Degree, Dissertation, Doctorate, Education, Faculty, Master, PhD, Student, Thesis Filed under Presentation Ideas

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36 Responses to “How To Do a Proper Thesis Defense Using the Right PowerPoint Presentation”

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Home > FACULTIES > Computer Science > CSD-ETD

Computer Science Theses and Dissertations

This collection contains theses and dissertations from the Department of Computer Science, collected from the Scholarship@Western Electronic Thesis and Dissertation Repository

Theses/Dissertations from 2024 2024

A Target-Based and A Targetless Extrinsic Calibration Methods for Thermal Camera and 3D LiDAR , Farhad Dalirani

Investigating Tree- and Graph-based Neural Networks for Natural Language Processing Applications , Sudipta Singha Roy

Theses/Dissertations from 2023 2023

Classification of DDoS Attack with Machine Learning Architectures and Exploratory Analysis , Amreen Anbar

Multi-view Contrastive Learning for Unsupervised Domain Adaptation in Brain-Computer Interfaces , Sepehr Asgarian

Improved Protein Sequence Alignments Using Deep Learning , Seyed Sepehr Ashrafzadeh

INVESTIGATING IMPROVEMENTS TO MESH INDEXING , Anurag Bhattacharjee

Algorithms and Software for Oligonucleotide Design , Qin Dong

Framework for Assessing Information System Security Posture Risks , Syed Waqas Hamdani

De novo sequencing of multiple tandem mass spectra of peptide containing SILAC labeling , Fang Han

Local Model Agnostic XAI Methodologies Applied to Breast Cancer Malignancy Predictions , Heather Hartley

A Quantitative Analysis Between Software Quality Posture and Bug-fixing Commit , Rongji He

A Novel Method for Assessment of Batch Effect on single cell RNA sequencing data , Behnam Jabbarizadeh

Dynamically Finding Optimal Kernel Launch Parameters for CUDA Programs , Taabish Jeshani

Citation Polarity Identification From Scientific Articles Using Deep Learning Methods , Souvik Kundu

Denoising-Based Domain Adaptation Network for EEG Source Imaging , Runze Li

Decoy-Target Database Strategy and False Discovery Rate Analysis for Glycan Identification , Xiaoou Li

DpNovo: A DEEP LEARNING MODEL COMBINED WITH DYNAMIC PROGRAMMING FOR DE NOVO PEPTIDE SEQUENCING , Yizhou Li

Developing A Smart Home Surveillance System Using Autonomous Drones , Chongju Mai

Look-Ahead Selective Plasticity for Continual Learning , Rouzbeh Meshkinnejad

The Two Visual Processing Streams Through The Lens Of Deep Neural Networks , Aidasadat Mirebrahimi Tafreshi

Source-free Domain Adaptation for Sleep Stage Classification , Yasmin Niknam

Data Heterogeneity and Its Implications for Fairness , Ghazaleh Noroozi

Enhancing Urban Life: A Policy-Based Autonomic Smart City Management System for Efficient, Sustainable, and Self-Adaptive Urban Environments , Elham Okhovat

Evaluating the Likelihood of Bug Inducing Commits Using Metrics Trend Analysis , Parul Parul

On Computing Optimal Repairs for Conditional Independence , Alireza Pirhadi

Open-Set Source-Free Domain Adaptation in Fundus Images Analysis , Masoud Pourreza

Migration in Edge Computing , Arshin Rezazadeh

A Modified Hopfield Network for the K-Median Problem , Cody Rossiter

Predicting Network Failures with AI Techniques , Chandrika Saha

Toward Building an Intelligent and Secure Network: An Internet Traffic Forecasting Perspective , Sajal Saha

An Exploration of Visual Analytic Techniques for XAI: Applications in Clinical Decision Support , Mozhgan Salimiparsa

Attention-based Multi-Source-Free Domain Adaptation for EEG Emotion Recognition , Amir Hesam Salimnia

Global Cyber Attack Forecast using AI Techniques , Nusrat Kabir Samia

IMPLEMENTATION OF A PRE-ASSESSMENT MODULE TO IMPROVE THE INITIAL PLAYER EXPERIENCE USING PREVIOUS GAMING INFORMATION , Rafael David Segistan Canizales

A Computational Framework For Identifying Relevant Cell Types And Specific Regulatory Mechanisms In Schizophrenia Using Data Integration Methods , Kayvan Shabani

Weakly-Supervised Anomaly Detection in Surveillance Videos Based on Two-Stream I3D Convolution Network , Sareh Soltani Nejad

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Reducing Negative Transfer of Random Data in Source-Free Unsupervised Domain Adaptation , Anthony Wong

Deep Neural Methods for True/Pseudo- Invasion Classification in Colorectal Polyp Whole-Slide Images , Zhiyuan Yang

Developing a Relay-based Autonomous Drone Delivery System , Muhammad Zakar

Learning Mortality Risk for COVID-19 Using Machine Learning and Statistical Methods , Shaoshi Zhang

Machine Learning Techniques for Improved Functional Brain Parcellation , Da Zhi

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The Design and Implementation of a High-Performance Polynomial System Solver , Alexander Brandt

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Algorithms for Regular Chains of Dimension One , Juan P. Gonzalez Trochez

Towards a Novel and Intelligent e-commerce Framework for Smart-Shopping Applications , Susmitha Hanumanthu

Multi-Device Data Analysis for Fault Localization in Electrical Distribution Grids , Jacob D L Hunte

Towards Parking Lot Occupancy Assessment Using Aerial Imagery and Computer Vision , John Jewell

Potential of Vision Transformers for Advanced Driver-Assistance Systems: An Evaluative Approach , Andrew Katoch

Psychological Understanding of Textual journals using Natural Language Processing approaches , Amirmohammad Kazemeinizadeh

Driver Behavior Analysis Based on Real On-Road Driving Data in the Design of Advanced Driving Assistance Systems , Nima Khairdoost

Solving Challenges in Deep Unsupervised Methods for Anomaly Detection , Vahid Reza Khazaie

Developing an Efficient Real-Time Terrestrial Infrastructure Inspection System Using Autonomous Drones and Deep Learning , Marlin Manka

Predictive Modelling For Topic Handling Of Natural Language Dialogue With Virtual Agents , Lareina Milambiling

Improving Deep Entity Resolution by Constraints , Soudeh Nilforoushan

Respiratory Pattern Analysis for COVID-19 Digital Screening Using AI Techniques , Annita Tahsin Priyoti

Extracting Microservice Dependencies Using Log Analysis , Andres O. Rodriguez Ishida

False Discovery Rate Analysis for Glycopeptide Identification , Shun Saito

Towards a Generalization of Fulton's Intersection Multiplicity Algorithm , Ryan Sandford

An Investigation Into Time Gazed At Traffic Objects By Drivers , Kolby R. Sarson

Exploring Artificial Intelligence (AI) Techniques for Forecasting Network Traffic: Network QoS and Security Perspectives , Ibrahim Mohammed Sayem

A Unified Representation and Deep Learning Architecture for Persuasive Essays in English , Muhammad Tawsif Sazid

Towards the development of a cost-effective Image-Sensing-Smart-Parking Systems (ISenSmaP) , Aakriti Sharma

Advances in the Automatic Detection of Optimization Opportunities in Computer Programs , Delaram Talaashrafi

Reputation-Based Trust Assessment of Transacting Service Components , Konstantinos Tsiounis

Fully Autonomous UAV Exploration in Confined and Connectionless Environments , Kirk P. Vander Ploeg

Three Contributions to the Theory and Practice of Optimizing Compilers , Linxiao Wang

Developing Intelligent Routing Algorithm over SDN: Reusable Reinforcement Learning Approach , Wumian Wang

Predicting and Modifying Memorability of Images , Mohammad Younesi

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Generating Effective Sentence Representations: Deep Learning and Reinforcement Learning Approaches , Mahtab Ahmed

A Physical Layer Framework for a Smart City Using Accumulative Bayesian Machine Learning , Razan E. AlFar

Load Balancing and Resource Allocation in Smart Cities using Reinforcement Learning , Aseel AlOrbani

Contrastive Learning of Auditory Representations , Haider Al-Tahan

Cache-Friendly, Modular and Parallel Schemes For Computing Subresultant Chains , Mohammadali Asadi

Protein Interaction Sites Prediction using Deep Learning , Sourajit Basak

Predicting Stock Market Sector Sentiment Through News Article Based Textual Analysis , William A. Beldman

Improving Reader Motivation with Machine Learning , Tanner A. Bohn

A Black-box Approach for Containerized Microservice Monitoring in Fog Computing , Shi Chang

Visualization and Interpretation of Protein Interactions , Dipanjan Chatterjee

A Framework for Characterising Performance in Multi-Class Classification Problems with Applications in Cancer Single Cell RNA Sequencing , Erik R. Christensen

Exploratory Search with Archetype-based Language Models , Brent D. Davis

Evolutionary Design of Search and Triage Interfaces for Large Document Sets , Jonathan A. Demelo

Building Effective Network Security Frameworks using Deep Transfer Learning Techniques , Harsh Dhillon

A Deep Topical N-gram Model and Topic Discovery on COVID-19 News and Research Manuscripts , Yuan Du

Automatic extraction of requirements-related information from regulatory documents cited in the project contract , Sara Fotouhi

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A Visual Analytics System for Rapid Sensemaking of Scientific Documents , Amirreza Haghverdiloo Barzegar

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A Technique for Evaluating the Health Status of a Software Module Using Process Metrics , . Ria

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Mitosis Detection from Pathology Images , Jinhang Zhang

Theses/Dissertations from 2020 2020

Visual Analytics of Electronic Health Records with a focus on Acute Kidney Injury , Sheikh S. Abdullah

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Computer Science Master Thesis Defense Presentation Template

Master Thesis Defense

Transcript: Advertisers use this regularly Hypothesis: The participants will have a better memory of a target when in attention span than when not in attention span Participants performed slightly better on the recognition test when the brand name was outside the visual attention span than when inside Mini experiment Horver Borger Master Thesis Defense Business Communication and Digital Media 2017 Triumph T. Odita The Influence of Gaze Cue on Visual Attention Span in Advertisements Eye-tracking Recognition study & To determine if viewers recognize objects inside their visual attention span To establish how viewers process images with a gaze cue 71% 73% 29% 27% Results The Visual Attention Span 20 Images which were used as experimental items in the recognition study "the visual field from which useful information is derived during a fixation" Rayner (1998) Conclusion Gaze Cue "When people believe that useful information about the objects or resources in the environment can be obtained by observing the direction or location of the other’s attention" Bayliss, A., Bartlett, J., Naughtin, C., & Kritikos, A. (2011) The hypothesis is not supported "From an early age, children begin learning to respond to these kinds of nonverbal hints" Chris Moore (2008) Horver Borger Questions? Thank You. Horver Borger

Transcript: Master Thesis Defense Sarah Anna Bradler BA MEM 2015 28/09/2017 Differences in leadership in Austria und Taiwan (R.O.C): A cross-cultural analysis focusing on leadership and discrimination AGENDA 1 Introduction Introduction Literature review Literature review Methodology Methodology Results Results Data Interpetation and Discussion Data Interpetation and Discussion Limitations and suggestions for further research Limitations and suggestions for further research Introduction 2 was raised.. during stay abroad in Taiwan and travelling throughout South East Asia by the challenging political situation worlwide... and intense discussion with locals in Austria and Taiwan Research Motivation Research Motivation Problem Statement Problem Statement Cross-cultural team work in the global environment Cross-cultural team work in the global environment Leadership have to deal with complex tasks have to adapt to a challenging set of competencies to be effective in motivating and leading multinational teams who are able to manage these diverse stressors at a workplace, increase the physical and mental health of the employees on a daily basis and therefore will increase their work performance (Nilsson, Andersson, Ejlertsson, & Troein, 2012, p. 2). Leadership Discrimination omnipresent part of organizational life basically neither positive nor negative but very complex defined as to be a behavior of an individual, organization or a group in which some people are treated differently from others. (Cooper & Cooper, 2016) appears either in a physical or psychological way based on race, ethnicity, culture, religion,…. can lead to severe disorders like post-traumatic stress disorder (PTSD) Discrimination Research Question 1 What are the main differences in Leadership of Teams in Austria compared to Taiwan? Research Question 2 Do employees and leaders perceive discrimination as a present challenge in companies in Austria and Taiwan? Research Question 3 Which steps have to be taken in order to reduce or eliminate discrimination at a workplace in Austria and Taiwan? Research Questions Research Questions Literature review 3 Hofstede`s Cultural Concept Trompenaars Cultural Theory Hall Globe Study Criticism on Theories Culture Culture Hofstede`s Indices Hofstede`s Indices Lewins Leadership Styles Globe Study Leadership Styles Leadership and Cross- Cultural Teamwork Leadership in Taiwan (R.O.C) and Austria Leadership in Taiwan (R.O.C) and Austria Democratic/Participative Leadership Style (Morgan,2013,p.1) Leadership in Austria Leadership in Austria Leadership in Taiwan (R.O.C) Leadership in Taiwan (R.O.C) Discrimination at the workplace Discrimination at the workplace Discrimination is the unfavorable treatment of an individual or a group of individuals based on personal characteristics such as gender, race, color or ethnic or national origin, age, or because of any requirements or conditions that confront the principles of fairness at the workplace. In addition, direct and indirect discrimination as well as harassment and victimization are also included. (edited by the author) Definition Definition created upon the following definitions: United Nations` International Labor Organization (ILO) (‘Convention C111’, 2016); UNESCO (‘Discrimination’, 2017); The Human Rights Commission (Santana, 2017); (Sue et al., 2007); (Marchiondo, Ran, & Cortina, 2015); (Cheung et al., 2016, p. 122); Austrian Equal Treatment Act (GIBG) Austria Austria wealthy modern welfare state about 8 million inhabitants German recognized minorities: Slovenes, Croats, Slovaks, Hungarians, Czechs as well as Roma late 1960s: attracted young workers from Turkey and earlier Yugoslavia early 1990s: Balkan crises with 150000 Bosnian refugees since 1990`s: political rise of FPÖ - openly communicated the idea of a “natural” dominance by so called “true-born” Austrians and “open hostility towards immigrants of Islamic faith” (Publications Office of the European Union, 2016, p. 4) Public Anti-Semitism remains a taboo Age discrimination Homosexuality Disability Gender related discrimination Education and training Income gap Parental leave Discrimination in Austria Discrimination in Austria increasing awareness two separated but correlated legal regimes deal with employment discrimination (foreign workers, gender equality) Women in workforce Gender pay gap Sexual harassment Pregnancy discrimination - “fetal protection policies” Race-based employment discrimination Aborigines Language / Rural dialects Disability Discrimination based on religious belief is seldom Taiwan Taiwan Methodology 4 Research Design Research Design - Secondary Research Secondary Research Anonymous Online Survey Questions: 41 (open questions, Likert-Scale) Language: English, German, Taiwanese based on 42 companies doing business in Austria and Taiwan (list provided by chamber of commerce) Further companies included after intense research 30 respondents Quantitative Analysis Comparisons and Correlations Qualitative

Defense Presentation - Master Thesis

Transcript: Introduction Developments in Labor Governance Approaches to the Study of Compliance with International Labor Standards Literature Review state hybrid Theory and Hypotheses Institute for Labor Studies Fostering Voluntary Compliance: An Assessment of the Labor Laws Compliance System 2015 Theory: Performance Assessment of Labor Governance Regimes Historical Comparison Research problem and objectives Relevance and importance of the study Summary and Conclusions "Why do firms comply (or do not comply) with international labor standards?" Developments in Labor Governance Findings and Analysis Approaches to the Study of Compliance with International Labor Standards Normative Framework on Workers' Rights and Labor Standards Methodology SINGLE CASE STUDY The operation of the normative framework tightens the network of rules and reduces labor laws circumvention... However, it has not yet fully pushed enforcement of ILS to a regime that goes beyond self and voluntary regulatory strategies as typified in the Philippines... The Changing Behavior of Firms Findings and Analysis self Literature Review Limitations Anke Hassel and Nicole Helmerich Institutional Change in Transnational Labor Governance: Implementing Social Standards in Public Procurement and Export Credit Guarantees 2016 Performance Assessment of Labor Governance Regimes Research hypotheses Rationale (Relevance and Importance of the Study) How the behavior of firms changed in the points of transition to a new labor governance regime despite the existence of international labor standards... even with sophistication of compliance systems... the horrors of the Kentex tragedy still continue to haunt workers under precarious working conditions... Hypotheses Research Design Hypothesis 2 The Philippine government transitioned to a voluntary labor governance regime because of the increasing pressure from transnational standard-setting institutions. This served as a window of opportunity for the ruling administration at the time of transition to re-establish its credibility and relevance in labor governance. Further, contrary to theory (Hurd 2003, Hassel 2008), firms comply more with the traditional regime of labor regulation than the private regime. Further Research Further research should look at the use of other methods Observational methods can be used to establish a causal link on the effect or impact of labor governance regime (mandatory, voluntary or hybrid) to the behavior of firms A transition to another regime may provide the opportunity to use econometric tools such as difference-in-differences to establish the effect of transnational regime (treatment) to the behavior of firms versus the effect of voluntary regime (control/counterfactual). Researchers can also look at the aspect of corruption in analyzing why labor laws compliance systems fail to protect the rights of workers. Rapid evolution of the labor market due to technological change and the consequent increase of non-standards forms of employment (worthwhile field of further research: labor laws compliance) THANK YOU Hypothesis 1 The normative framework on workers’ rights and labor standards demands different levels of commitment from firms addressed at so many levels – global, national and firm – that tightens the web of rules and reduces the possibility of circumventing labor laws. However, this normative framework did not push state enforcement to a regime that goes beyond self and voluntary regulatory strategies. Contributions Different factors induced the transition from one labor governance regime to another. Firms comply more with the traditional regime of labor regulation than the private labor governance regime. Literature Review How do international and domestic level standards, rules and regulations affect labor governance at the level of state enforcement? Anke Hassel The Evolution of a Global Labor Governance Regime 2008 Case Selection 1. The extent the country has mainstreamed ILS to the national level 2. Prevalence of work-related accidents 3. Transition from a mandatory to a voluntary labor governance regime How international and domestic level standards, rules and regulations affect labor governance at the level of state enforcement Summative Assessment of Firms' Compliance with International Labor Standards Normative Framework on Workers' Rights and Labor Standards The Evolution of Labor Governance and the Changing Behavior of Firms Mechanisms of Enforcement and Compliance with International Labor Standards: What Do They Demand from and Offer to Firms? Summative Assessment of Firms' Compliance with International Labor Standards Miguel Luis U. Arias Why do firms comply with international labor standards? How the mechanisms induced compliance with ILS Theory and Hypotheses Case Selection and Limitations How the demands of the mechanisms correspond with the behavior of firms Unit(s) of Analysis: Labor governance regimes (VEF, LSEF and LLCS) Research Design The Evolution of Labor

Transcript: Give space to lead Prioritize Staff Care Encourage self-reflection Prioritize National Staff Make leadership training practical Prioritize Leadership Coach the leaders Recommendations Staff Mental Health in Emergencies How to Care in a Cowboy Culture? Background Methodology/Set-up Theoretical Framework Interview Results Recommendations "Leadership in-country, that provides a clear vision and objectives for the humanitarian response to a specific crisis (whether at the program, organizational or system-wide level, focussed on the affected population and building a consensus that brings aid workers together around that vision and objectives. It also means finding ways of collectively realizing that vision for the benefits of the affected population, often in challenging and hostile environments." (ALNAP 2011) Methodology Results of the Interviews How do operational humanitarian leaders perceive their role regarding duty of care? Which challenges have they experienced and which good practices are they applying? How do operational humanitarian leaders perceive organizational support? Unstructured, depending on the individual Operational Humanitarian Leadership 7 semi-structured Interviews transcribed, coded & analyzed Software used: Skype, F5 Addition: Short field trip to Sierra Leone Qualitative study about staff care in humanitarian missions Research angle: Operational humanitarian leaders/Organizational change Main Research question: How can humanitarian organizations strengthen operational leadership to provide better staff care? Why? Legal/Ethical Master Thesis Defense Carla Weymann Critical Incident Management Team Culture Resonable Workplace Living space Recognition, Motivation Duty of Care Staff Care Background Thank you! Theoretical Framework Security, Psychological safety Lack of funding Lack of training Humanitarian Culture National Staff

Master thesis defense

Transcript: Master thesis defense Pricing process of other works of art How do specialists working at auction houses determine the price estimates of paintings? General conclusion Method Qualitative research method Semi-structured interview Interview questions Collection of data Empirical research Velthuis (2002, 2005) Hypotheses Hypothesis one: specialists working at auction houses use pricing scripts to determine the estimates of paintings. Hypothesis two: specialists pay attention to different price determinants to determine the price estimates of paintings. Hypothesis three: specialists pay attention to different price determinants when they need to determine the price estimates of Old Master paintings and Contemporary paintings. Hypothesis four: specialists pay more attention to artist- or artwork or market- or macro level factors. Hypothesis five: the personal taste of specialists has an influence on the price estimates of paintings. Hypothesis six: potential buyers have the biggest influence on the hammer prices fetched at auction. 'a set of routines which function as a cognitive manual for the variety of pricing decisions that a dealer needs to make in different stages of an artist’s career’ (Velthuis, 2002, p.52). Research questions Confirmed: Pricing scripts are helpful tools to determine price estimates, but potential buyers will always have the final word when it comes to the hammer prices fetched at auction. Hypothesis two: specialists pay attention to different price determinants to determine the price estimates of paintings. Hypothesis three: specialists pay attention to different price determinants when they need to determine the price estimates of Old Master paintings and Contemporary paintings. 1. Do specialists working at auction houses use pricing scripts when they determine the price estimates of paintings? 2. Do experts pay attention to different price determinants when they determine the price estimates of paintings? 3. Do specialists pay attention to different price determinants when they determine the price estimates of Old Master paintings and Contemporary paintings? 4. Which factor has the most influence on the price estimates of paintings according to the specialists? 5. Does the taste of experts has an influence on the price estimates of paintings? 6. How is it possible that hammer prices are not always in line with the price estimates stated by art specialists? Hypothesis one: specialists working at auction houses use pricing scripts to determine the estimates of paintings. Hypothesis five: the personal taste of specialists has an influence on the price estimates of paintings. Hypothesis six: potential buyers have the biggest influence on the hammer prices fetched at auction. Pricing scripts Primary art market versus secondary art market Limitations and recommendations for further research Socially and academically relevant Find out if these experts use ‘pricing scripts’ and if differences can be found in the decision-making process between specialists working at different auction houses. Hypothesis four: specialists pay more attention to artist- or artwork or market- or macro level factors. Determine estimates during the interview Limitation of the research Inspiration and motivation Not entirely confirmed: Priceless or worthless? A qualitative research on how price estimates are determined in the secondary art market Aim and relevance Manou Lourens 319142 Conclusion empirical research Provide a better insight in the pricing process that specialists run through to determine the price estimates, before a painting is put up for auction. Rejected: How do specialists working at auction houses determine the price estimates of paintings? Auction houses in the Netherlands Specialists Interviews Auction houses operating in the UK or China Thank you for your attention!

Transcript: Investment in Student Housing in Europe with a focus on Germany Understanding students’ preferences in terms of student housing and the potential of micro-units for student housing Master Thesis Defense Summary Camille Wajsblat - 24.10.2017 Introduction Why student housing ? Why student housing ? 1st reason Personal and direct interest in the topic (being confronted to it directly in different markets/places/contexts) 2nd reason Awareness of the interest of professionals for this expanding market 3rd reason Already a good inside-knowledge about the German student housing market Literature review Literature review Decision-making process Decision-making process Abundant literature and research about irrationality of investors Irrationality in real estate inevitable because of the limitation of models In real estate, research about: influence of sentiments/feelings and past experience challenges and "best practices" for investors influence of mental accounting and false reference points Student Housing Student Housing Main research conducted towards: expected outcomes and negative aspects of on-campus living the meaning of "home" and housing pathways impact of socio-physiological background of students on their housing preferences single vs. collective housing Very little research conducted about off-campus housing Studies are not linked to the supply/investment side Micro apartments Micro apartments GBH Mikroapartments - Körnerstraße, Hannover Extensive literature about: reasons for attractiveness: price, location, mobility expected benefits: attract students and young professionnals, efficiency , sustainability Barriers to development: potential negative social effects regulations financing Still have a strong potential for students Research preparation decision-making models not applicable in concrete life studies about SH are rarely linked to the supply/investors side reconcile the supply and the demand side of the student housing market What did I want to find out ? Preparation of research Preparation of research Which method(s) fit(s) best ? What are current students’ expectations regarding student accomodation ? Are investors aware of these expectations ? Students: direct questions through survey Real estate professionals: direct questions through interviews Timeline Timeline 1 5 10 15 20 25 30 May August July June Reading academic papers/research Running survey Creating survey Writing Form registration Creating interviews Running interviews Review Handover e7143f Field Research Field Research Questionnaire Benchmark to select the best channel Questionnaire Premium subscription: unlimited questions, unlimited questionnaires, analysis tools, Excel/PDF exports Channel used: After collection of results, own analysis on excel with pivot tables Goals: 1. identify patterns between preferences of respondents given three parameters: gender, country of study and level of study 2. Confront answers of respondents and answers of interviewees Interviews Interviews Elaborated following the analysis of the questionnaires’ results Breached the topic of micro units Q1. SH has become a real asset class, it is not a niche market anymore for investors. What do you think triggered this new attractivity ? Q2. How do you think investments in SH will evolve on a short/middle term ? Q3. How are the most active investors in SH in Germany ? Q4. Are you aware of micro-units as one of the latest trends in development ? Q5. Why would you consider a micro-apartment an attractive investment for developers/investors ? Q6. What potential have micro-units into the SH market ? Q7. Can you order the following characteristics in order of what you think is more important for a student who has to select a student accommodation ? (1- most important, 12- least important) Q8. Can you order the following list of amenities by level of importance what a student housing should offer according to you ? (1- most important, 5- least important) Q9. What would you say is a reasonable budget for rent per month for a student in Germany ? Q10. 24% of students who still live with their parents in Germany say they are dissatisfied with their situation and would like to move out but cannot. What do you think is the biggest obstacle for finding a suitable student housing in Germany ? Results Results of the study Mean Ranking MK MS Amount of rent 3,53 1 1 4 Short walking distance to 3,31 2 2 2 public transportation Proximity to a grocery store 3,30 3 6 9 Possibility to easily end the 3,17 4 8 6 renting contract Proximity to the university 3,14 5 3 1 Proximity to the city center 3,02 6 4 11 Furnished accommodation 2,96 7 7 5 Quiet location 2,84 8 12 7 Proximity to green areas 2,60 9 10 8 Interaction with the landlord 2,23 10 11 12 Proximity to night-life district 2,18 11 5 3 Possibility to park in the area 2 ,08 12 9 10 Analysis Analysis regarding the general backroung of respondents Gender: girl students live closer to university, male students used more often a

Transcript: Changing the world to what it should be Lower debt ratios, because: - Threatening liquidation is bad for the image of the CEO (Hirshleifer & Thakor, 1992) - More control over the company (not bonded by debt covenants). But is this really true in reality? Mastery Agenda Thinking as an individual Where does the CEO come from? Conservatism Autonomy 97.35% Results & discussion Inequality Conservatism 2.65% Hierarchy Egalitairianism Mastery Harmony Research question Review of academic studies Results & discussion Conclusion Equality  Lower debt ratios, because: - Less agency problems - CEOs are more concerned with liquidation costs (Titman, 1984) - Threatening liquidation is bad for the image of the firm (Chui et al., 2002) - More uncertainty and therefore more risk averse (Offermann & Hellmann, 1997; Riddle, 1992) CEOs are afraid of bankruptcy and care about either their own image or the image of the firm CEOs from countries with a high mastery value use more debt in their firm Tenure and age of the CEO are not related to each other but are also of an important factor by capital structure decisions Older CEOs use more debt in their firm - Less willing to take risk - Younger people hang more onto a target debt ratio CEOs with a longer tenure use less debt in their firm. - More worried about their long-term relationship with stakeholders Through the Eyes of Schwartz: How Cultural Background Influences Capital Structure in the United States Nationality Accept the world as it is 98.44% Schwartz value types No evidence that the conservatism-autonomy dimension is related to capital structure CEOs from countries with a high mastery value use more debt in their firm. However, this result is not significant for CEOs with a foreign educational background More debt is more control over the shareholders, so more space to change the firm to what you think it should be! Thinking as a group Where does the CEO come from? Conclusion How does cultural background influence capital structure in the United States? Educational background Martijn den Blanken Master thesis defense – MSc Finance & Investments 14 March 2013 1.56% Results & discussion

Defense Master Thesis

Transcript: Master Thesis Project "A master thesis focused on discovering balanced scorecard categories to be implemented within the elderly/home care organizational context to foster business process innovation" 1. Introduction Introduction A research within MeanderGroep Trends Trends & Developments Elderly/home care organization Shift to more care at home Technology & Innovation Small sclare care giving environments Trends up to 2020 E-health solution Effects Business process restructuring Manage employees Higher effiency in use of resources Implment innovation and many more... Effects BPM Business Process management BPM & Innovation BPM Performance Measures Enabler of Business Process Innovation Strategic management tool Balanced Scorecard (BSC) Significant part within is... Specific context Elderly/home care organization context Non-profit & additional characteristics Non - Profit Different purpose Different ownership Different control Accountability Additional characteristics Non-standard B2C situation Stakeholders Research question Main research question & sub research questions “Which balanced scorecard categories have to be implemented within the business pro-cess landscape of the elderly/home care organization MeanderGroep to foster business process innovation?” 1. “What is the current business maturity level of MeanderGroep” 2. “Which performance measures are desired by MeanderGroep” 3. “Which BSC categories substantiates the desired performance measures” 4. “Which issues have to be concerned when implementing these BSC categories” 5. “How are these BSC categories implemented within current or new business pro-cesses to create innovative practices?” Business relevant sub-research questions; 2. Literature Literature General BPM Business process management Business process management contextual factors & Six core elements Goal-dimension Process-Dimension Organization-dimension Enviroment-dimension BPM contextual factors** **"Schmiedel, Vom Brocke, & Recker, 2013" Six core elements*** 1. Stretgic allignment 2. Governance 3. Methods 4. Information Technology 5. People 6. Culture ***"Schmiedel, Vom Brocke, & Recker, 2013" BPM lifecycle* **"Dumas, La Rosa, Mendling, & Reijers, 2013" BPMM Business Process Maturity Model (BPMM) Context + core elements = BPMM *"Business Process Maturity Model (BPMM), (OMG, 2008)" Level 5: Innovating Level 4: Predictable Level 3: Standardized Level 2: Managed Level 1: Initial Innovation management Capability management Process management Work-Unit management Inconsistentmanagement Innovative practices Optimized practices Standardized practices Repeatable practices BSC Process identification Process discovery Process analysis Process redesign Process implementation Process monitoring and controlling Process architecture A-is process model Insigth on weakenesses and their impact To-be process model Executable process model Conformance and performance insigths BSC combi-nation Balanced Scorecard Combination 3. Methodology Finance Results Results Upcoming Events Upcoming Events 4. Results HR New Faces New Faces Upcoming Events Upcoming Events 5. Advice for Implmentation Other... Results Results PHASE 1: PHASE 2: PHASE 3: Upcoming Events Upcoming Events 6. Discussion Other... Results Results PHASE 1: PHASE 2: PHASE 3: Upcoming Events Upcoming Events 7. Future research & Limitations Other... Results Results PHASE 1: PHASE 2: PHASE 3: Upcoming Events Upcoming Events

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Digital Commons @ USF > College of Engineering > Computer Science and Engineering > Theses and Dissertations

Computer Science and Engineering Theses and Dissertations

Theses/dissertations from 2023 2023.

Refining the Machine Learning Pipeline for US-based Public Transit Systems , Jennifer Adorno

Insect Classification and Explainability from Image Data via Deep Learning Techniques , Tanvir Hossain Bhuiyan

Brain-Inspired Spatio-Temporal Learning with Application to Robotics , Thiago André Ferreira Medeiros

Evaluating Methods for Improving DNN Robustness Against Adversarial Attacks , Laureano Griffin

Analyzing Multi-Robot Leader-Follower Formations in Obstacle-Laden Environments , Zachary J. Hinnen

Secure Lightweight Cryptographic Hardware Constructions for Deeply Embedded Systems , Jasmin Kaur

A Psychometric Analysis of Natural Language Inference Using Transformer Language Models , Antonio Laverghetta Jr.

Graph Analysis on Social Networks , Shen Lu

Deep Learning-based Automatic Stereology for High- and Low-magnification Images , Hunter Morera

Deciphering Trends and Tactics: Data-driven Techniques for Forecasting Information Spread and Detecting Coordinated Campaigns in Social Media , Kin Wai Ng Lugo

Automated Approaches to Enable Innovative Civic Applications from Citizen Generated Imagery , Hye Seon Yi

Theses/Dissertations from 2022 2022

Towards High Performing and Reliable Deep Convolutional Neural Network Models for Typically Limited Medical Imaging Datasets , Kaoutar Ben Ahmed

Task Progress Assessment and Monitoring Using Self-Supervised Learning , Sainath Reddy Bobbala

Towards More Task-Generalized and Explainable AI Through Psychometrics , Alec Braynen

A Multiple Input Multiple Output Framework for the Automatic Optical Fractionator-based Cell Counting in Z-Stacks Using Deep Learning , Palak Dave

On the Reliability of Wearable Sensors for Assessing Movement Disorder-Related Gait Quality and Imbalance: A Case Study of Multiple Sclerosis , Steven Díaz Hernández

Securing Critical Cyber Infrastructures and Functionalities via Machine Learning Empowered Strategies , Tao Hou

Social Media Time Series Forecasting and User-Level Activity Prediction with Gradient Boosting, Deep Learning, and Data Augmentation , Fred Mubang

A Study of Deep Learning Silhouette Extractors for Gait Recognition , Sneha Oladhri

Analyzing Decision-making in Robot Soccer for Attacking Behaviors , Justin Rodney

Generative Spatio-Temporal and Multimodal Analysis of Neonatal Pain , Md Sirajus Salekin

Secure Hardware Constructions for Fault Detection of Lattice-based Post-quantum Cryptosystems , Ausmita Sarker

Adaptive Multi-scale Place Cell Representations and Replay for Spatial Navigation and Learning in Autonomous Robots , Pablo Scleidorovich

Predicting the Number of Objects in a Robotic Grasp , Utkarsh Tamrakar

Humanoid Robot Motion Control for Ramps and Stairs , Tommy Truong

Preventing Variadic Function Attacks Through Argument Width Counting , Brennan Ward

Theses/Dissertations from 2021 2021

Knowledge Extraction and Inference Based on Visual Understanding of Cooking Contents , Ahmad Babaeian Babaeian Jelodar

Efficient Post-Quantum and Compact Cryptographic Constructions for the Internet of Things , Rouzbeh Behnia

Efficient Hardware Constructions for Error Detection of Post-Quantum Cryptographic Schemes , Alvaro Cintas Canto

Using Hyper-Dimensional Spanning Trees to Improve Structure Preservation During Dimensionality Reduction , Curtis Thomas Davis

Design, Deployment, and Validation of Computer Vision Techniques for Societal Scale Applications , Arup Kanti Dey

AffectiveTDA: Using Topological Data Analysis to Improve Analysis and Explainability in Affective Computing , Hamza Elhamdadi

Automatic Detection of Vehicles in Satellite Images for Economic Monitoring , Cole Hill

Analysis of Contextual Emotions Using Multimodal Data , Saurabh Hinduja

Data-driven Studies on Social Networks: Privacy and Simulation , Yasanka Sameera Horawalavithana

Automated Identification of Stages in Gonotrophic Cycle of Mosquitoes Using Computer Vision Techniques , Sherzod Kariev

Exploring the Use of Neural Transformers for Psycholinguistics , Antonio Laverghetta Jr.

Secure VLSI Hardware Design Against Intellectual Property (IP) Theft and Cryptographic Vulnerabilities , Matthew Dean Lewandowski

Turkic Interlingua: A Case Study of Machine Translation in Low-resource Languages , Jamshidbek Mirzakhalov

Automated Wound Segmentation and Dimension Measurement Using RGB-D Image , Chih-Yun Pai

Constructing Frameworks for Task-Optimized Visualizations , Ghulam Jilani Abdul Rahim Quadri

Trilateration-Based Localization in Known Environments with Object Detection , Valeria M. Salas Pacheco

Recognizing Patterns from Vital Signs Using Spectrograms , Sidharth Srivatsav Sribhashyam

Recognizing Emotion in the Wild Using Multimodal Data , Shivam Srivastava

A Modular Framework for Multi-Rotor Unmanned Aerial Vehicles for Military Operations , Dante Tezza

Human-centered Cybersecurity Research — Anthropological Findings from Two Longitudinal Studies , Anwesh Tuladhar

Learning State-Dependent Sensor Measurement Models To Improve Robot Localization Accuracy , Troi André Williams

Human-centric Cybersecurity Research: From Trapping the Bad Guys to Helping the Good Ones , Armin Ziaie Tabari

Theses/Dissertations from 2020 2020

Classifying Emotions with EEG and Peripheral Physiological Data Using 1D Convolutional Long Short-Term Memory Neural Network , Rupal Agarwal

Keyless Anti-Jamming Communication via Randomized DSSS , Ahmad Alagil

Active Deep Learning Method to Automate Unbiased Stereology Cell Counting , Saeed Alahmari

Composition of Atomic-Obligation Security Policies , Yan Cao Albright

Action Recognition Using the Motion Taxonomy , Maxat Alibayev

Sentiment Analysis in Peer Review , Zachariah J. Beasley

Spatial Heterogeneity Utilization in CT Images for Lung Nodule Classication , Dmitrii Cherezov

Feature Selection Via Random Subsets Of Uncorrelated Features , Long Kim Dang

Unifying Security Policy Enforcement: Theory and Practice , Shamaria Engram

PsiDB: A Framework for Batched Query Processing and Optimization , Mehrad Eslami

Composition of Atomic-Obligation Security Policies , Danielle Ferguson

Algorithms To Profile Driver Behavior From Zero-permission Embedded Sensors , Bharti Goel

The Efficiency and Accuracy of YOLO for Neonate Face Detection in the Clinical Setting , Jacqueline Hausmann

Beyond the Hype: Challenges of Neural Networks as Applied to Social Networks , Anthony Hernandez

Privacy-Preserving and Functional Information Systems , Thang Hoang

Managing Off-Grid Power Use for Solar Fueled Residences with Smart Appliances, Prices-to-Devices and IoT , Donnelle L. January

Novel Bit-Sliced In-Memory Computing Based VLSI Architecture for Fast Sobel Edge Detection in IoT Edge Devices , Rajeev Joshi

Edge Computing for Deep Learning-Based Distributed Real-time Object Detection on IoT Constrained Platforms at Low Frame Rate , Lakshmikavya Kalyanam

Establishing Topological Data Analysis: A Comparison of Visualization Techniques , Tanmay J. Kotha

Machine Learning for the Internet of Things: Applications, Implementation, and Security , Vishalini Laguduva Ramnath

System Support of Concurrent Database Query Processing on a GPU , Hao Li

Deep Learning Predictive Modeling with Data Challenges (Small, Big, or Imbalanced) , Renhao Liu

Countermeasures Against Various Network Attacks Using Machine Learning Methods , Yi Li

Towards Safe Power Oversubscription and Energy Efficiency of Data Centers , Sulav Malla

Design of Support Measures for Counting Frequent Patterns in Graphs , Jinghan Meng

Automating the Classification of Mosquito Specimens Using Image Processing Techniques , Mona Minakshi

Models of Secure Software Enforcement and Development , Hernan M. Palombo

Functional Object-Oriented Network: A Knowledge Representation for Service Robotics , David Andrés Paulius Ramos

Lung Nodule Malignancy Prediction from Computed Tomography Images Using Deep Learning , Rahul Paul

Algorithms and Framework for Computing 2-body Statistics on Graphics Processing Units , Napath Pitaksirianan

Efficient Viewshed Computation Algorithms On GPUs and CPUs , Faisal F. Qarah

Relational Joins on GPUs for In-Memory Database Query Processing , Ran Rui

Micro-architectural Countermeasures for Control Flow and Misspeculation Based Software Attacks , Love Kumar Sah

Efficient Forward-Secure and Compact Signatures for the Internet of Things (IoT) , Efe Ulas Akay Seyitoglu

Detecting Symptoms of Chronic Obstructive Pulmonary Disease and Congestive Heart Failure via Cough and Wheezing Sounds Using Smart-Phones and Machine Learning , Anthony Windmon

Toward Culturally Relevant Emotion Detection Using Physiological Signals , Khadija Zanna

Theses/Dissertations from 2019 2019

Beyond Labels and Captions: Contextualizing Grounded Semantics for Explainable Visual Interpretation , Sathyanarayanan Narasimhan Aakur

Empirical Analysis of a Cybersecurity Scoring System , Jaleel Ahmed

Phenomena of Social Dynamics in Online Games , Essa Alhazmi

A Machine Learning Approach to Predicting Community Engagement on Social Media During Disasters , Adel Alshehri

Interactive Fitness Domains in Competitive Coevolutionary Algorithm , ATM Golam Bari

Measuring Influence Across Social Media Platforms: Empirical Analysis Using Symbolic Transfer Entropy , Abhishek Bhattacharjee

A Communication-Centric Framework for Post-Silicon System-on-chip Integration Debug , Yuting Cao

Authentication and SQL-Injection Prevention Techniques in Web Applications , Cagri Cetin

Multimodal Emotion Recognition Using 3D Facial Landmarks, Action Units, and Physiological Data , Diego Fabiano

Robotic Motion Generation by Using Spatial-Temporal Patterns from Human Demonstrations , Yongqiang Huang

A GPU-Based Framework for Parallel Spatial Indexing and Query Processing , Zhila Nouri Lewis

A Flexible, Natural Deduction, Automated Reasoner for Quick Deployment of Non-Classical Logic , Trisha Mukhopadhyay

An Efficient Run-time CFI Check for Embedded Processors to Detect and Prevent Control Flow Based Attacks , Srivarsha Polnati

Force Feedback and Intelligent Workspace Selection for Legged Locomotion Over Uneven Terrain , John Rippetoe

Detecting Digitally Forged Faces in Online Videos , Neilesh Sambhu

Malicious Manipulation in Service-Oriented Network, Software, and Mobile Systems: Threats and Defenses , Dakun Shen

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Bachelor and Master's Theses

Interested in doing a thesis with us?

Great news, many of our graduates were able to publish a paper based on their bachelor or master thesis or they even received a best thesis award from TU Berlin and our scientific research communities.

Please do us a favor carfully reading the following information - this shows that you are really interested working with us!

These are the steps required to successfully register a thesis with TKN:

• See what we offer for your Bachelor curriculum here .
• See what we offer for your Master curriculum here .
• There is already a fit in the list of available topics ? Great! Contact the responsible supervisor to discuss next steps.
• There is no immediate fit? There might still be a team member working on an interesting topic. Feel free to contact her or him directly to discuss how you could contribute.

When contacting the potential advisor, please clearly indicate the topic you are interested in and the time schedule you have in mind for working on the thesis. To introduce yourself, attach a transcript of your studies so far and mention any previous experience relevant for the thesis. Also please indicate which programming languages you are familiar with. If you have (relevant) research experience, you can add a brief summary of your previous work.

Please note, we do not support external theses with companies we do not collaborate with

Helpful information

• We have a bi-weekly meeting for all bachelor and master students to shortly discuss the current status of each thesis and to help with problems.
• Some information on " how to write a thesis " can be found here
• TKN proposal LaTeX template (zip) for your thesis proposal.
• TKN thesis LaTeX template (zip) for your thesis.
• TKN Powerpoint presentation template (pptx) for your initial and final talk.

Open Topics for Bachelor and Master's Theses

The listed topics are to be considered as examples. Please visit us to discuss potential topics in detail.

• Performance evaluations of various cooperative spectrum sensing algorithms (Bachelor/Master's Thesis) Advisor(s): Rathinamala Vijay
• Fine-grained QoS management for Mixed-criticality Traffic in Wi-Fi 7 (Master's thesis) Advisor(s): Doganalp Ergenc
• Implementing Synchronous Wi-Fi Multi-link Operation (MLO) in OMNeT++ (Bachelor's thesis) Advisor(s): Doganalp Ergenc
• Towards Ultra-reliable Wi-Fi: Adaptive Redundancy for Mixed-criticality Traffic via Wi-Fi 7 Multi-link Operation (MLO) (Master's thesis) Advisor(s): Doganalp Ergenc
• Enabling Fault Tolerance over Wi-Fi Multi-link Operation (MLO) in OMNeT++ (Bachelor's thesis) Advisor(s): Doganalp Ergenc
• Combining IEEE 802.1 Time-sensitive Networking (TSN) Scheduling with Multi-link Channel Access in Wi-Fi 7 (Bachelors's thesis) Advisor(s): Doganalp Ergenc
• Evaluation of a hybrid LiFi/PLC communication system (Bachelor/Master’s Thesis) Advisor(s): Anatolij Zubow
• Mobile Target Detection via Integrated Sensing and Communication (Master's Thesis) Advisor(s): Atefeh Rezaei
• Distributed Object Detection for Cooperative Perception (Master's Thesis) Advisor(s): Varun Pandey and Agon Memedi
• Channel Modeling for Vehicular Optical Camera Communications (Master’s Thesis) Advisor(s): Agon Memedi and Anatolij Zubow
• Modeling of Outdoor Vehicular Visible Light Communication Channel (Master’s Thesis) Advisor(s): Agon Memedi and Anatolij Zubow
• Impact of Interference by Reconfigurable Intelligent Surfaces on Inter-Vehicle Communication (Master's Thesis) Advisor(s): Joana Angjo and Tolja Zubow
• Classifying WiFi FTM with the help of channel state information (Bachelor's Thesis) Advisor(s): Sascha Rösler and Anatolij Zubow
• Byzantine Fault-Tolerant Federated Reinforcement Learning (Bachelor’s/ Machelor’s Thesis) Advisor(s): Youming Tao
• Federated Reinforcement Learning with Heavy-Tailed Rewards (Bachelor’s/ Machelor’s Thesis) Advisor(s): Youming Tao
• Communication-Efficient Federated Reinforcement Learning under Differential Privacy (Bachelor’s/ Machelor’s Thesis) Advisor(s): Youming Tao
• Machine Unlearning for Online Federated Learning (Bachelor’s/ Machelor’s Thesis) Advisor(s): Youming Tao

Ongoing Bachelor and Master's Theses

• Developing a Time-Varying Ultrasonic Channel Model for Nanosensor-to-Gateway Communication (Bachelor's thesis) Advisor(s): Saswati Pal
• Improving Multiple Factors of Bicycling Illusion of a Virtual Cycling Environment (Master's thesis) Advisor(s): Lukas Stratmann and Marie-Christin H. Oczko
• Implementation of an Energy Efficient Coded Flooding Algorithm for Wireless Sensor Networks (WSNs) using ESP NOW (Bachelor Thesis) Advisor(s): Anatolij Zubow and Falko Dressler
• An experimental study of FTM over VLC (Bachelor's Thesis) Advisor(s): Kai Habel and Anatolij Zubow
• mmLoRa: Towards long-range omnidirectional mmWave communication (Bachelor's Thesis) Advisor(s): Sascha Rösler and Sigrid Dimce
• Extension of the ns3 network simulator to support intelligent reflecting surfaces (Bachelor's Thesis) Advisor(s): Sascha Rösler and Joana Angjo
• Thompson Sampling for a passive spectrum monitoring system (Bachelor's Thesis) Advisor(s): Sascha Rösler
• A Software-based Prototype for Integration of LiFi in Heterogeneous Layer-2 Networks (Bachelor’s Thesis) Advisor(s): Lennert Bober and Falko Dressler
• Packet based Cross-Technology Communication playground (Bachelor's Thesis) Advisor(s): Sascha Rösler and Anatolij Zubow
• Improving Accuracy of WiFi-FTM-based Ranging with Frequency Diversity (Bachelor's Thesis) Advisor(s): Sascha Rösler
• Intelligent UAV Network for Monitoring Fruit Trees in Greenhouses (Bachelor Thesis) Advisor(s): Jorge Torres Gómez
• Evaluation of IEEE 802.11 with a CRAN-FTTR-based Fronthaul (Master's Thesis) Advisor(s): Anatolij Zubow
• Analysis of environmental influence on WiFi FTM with ESP32 hardware (Bachelor's Thesis) Advisor(s): Sascha Rösler and Anatolij Zubow
• Simulation of cell-free WiFi (Bachelor's Thesis) Advisor(s): Anatolij Zubow
• When ns-3 meets Sionna: Towards a more realistic channel simulation in indoor scenarios (Bachelor's Thesis) Advisor(s): Sascha Rösler
• Hiding cross technology communication from technology specific jamming attacks (Bachelor's Thesis) Advisor(s): Sascha Rösler and Anatolij Zubow

Completed Bachelor and Master's Theses (since 2020)

• Stefan William Böhm, " Analysis of environmental influence on WiFi FTM with ESP32 hardware ," Bachelor Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), March 2024. (Advisor: Sascha Rösler ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• Nikolaos Athanasiadis, " Multi-IRS-Assisted Multi-Operator Networks ," Bachelor Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), March 2024. (Advisors: Joana Angjo and Anatolij Zubow ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• Onur Erbil, " Investigation of Greedy Algorithms for Multiband Splicing ," Bachelor Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), February 2024. (Advisor: Sigrid Dimce ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• Naitian Wang, " Study of Frequency Reuse Strategies for Compensation of Base Station Outage ," Master's Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), January 2024. (Advisor: Anatolij Zubow ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• Alonso Fernandez Mira, " An adaptive triggering algorithm for FTM ," Bachelor Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), January 2024. (Advisor: Sascha Rösler ; Referee: Falko Dressler ) [ BibTeX , Details... ]
• Muhammad Elhwawshy, " Development of a low-cost joint communication and sensing platform ," Bachelor Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), December 2023. (Advisor: Anatolij Zubow ; Referees: Anatolij Zubow and Thomas Sikora) [ BibTeX , Details... ]
• Alexander Wessels, " Passive Sensing of Mechanical Vibrations using COTS 802.11 Hardware ," Bachelor Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), December 2023. (Advisor: Anatolij Zubow ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• Georg Schwarzkopf, " When ns3-gym meets gr-gym: a cross-layer machine learning approach ," Bachelor Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), December 2023. (Advisor: Sascha Rösler ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• Christos Laskos , " Mobile mmWave Beam Tracking using Deep Q-Network Learning ," Master's Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), December 2023. (Advisors: Anatolij Zubow and Sigrid Dimce ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• Arno Bock, " Design and Comparative Analysis of a Continuously-Reassigning Platoon Formation Algorithm ," Bachelor Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), December 2023. (Advisor: Julian Heinovski ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• Isabel von Stebut, " Resilience through Cross-Technology-Communication ," Bachelor Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), October 2023. (Advisor: Anatolij Zubow ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• Alexey Hramov, " Device-free Indoor Localization based on Wi-Fi Fine Timing Measurements ," Bachelor Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), September 2023. (Advisor: Anatolij Zubow ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• Emirali Caferzade, " Modeling and Simulating Chemotaxis Bacteria Networks with Drift in MATLAB ," Master's Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), September 2023. (Advisor: Jorge Torres Gómez ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• Daniel Neumann, " Reliable Data Storage within Vehicular Micro Clouds (VMCs) ," Bachelor Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), July 2023. (Advisors: Max Schettler and Fabian Missbrenner ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• Xueting Zhang, " Load management in a Distributed Intrusion Detection System ," Master's Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), July 2023. (Advisor: Hossein Doroud ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• Xin Li, " Explainability of NN-based Detectors in MIMO Molecular Channels ," Master's Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), July 2023. (Advisor: Jorge Torres Gómez ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• Min He Jo, " Intelligent Container Migrations in an Urban Vehicular Virtual Edge ," Master's Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), July 2023. (Advisor: Gurjashan Singh Pannu ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• Saarujan Sritharan, " Reacting to Intra-Platoon Mobility Problems using Follower Feedback ," Bachelor Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), July 2023. (Advisor: Julian Heinovski ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• Eric Gu, " Realistic Simulation of Emergency Vehicles in SUMO ," Bachelor Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), July 2023. (Advisors: Julian Heinovski and Tobias Hardes ; Referees: Falko Dressler and Christoph Sommer ) [ BibTeX , Details... ]
• Qing Miao, " Improved Emergency Vehicle Pass-through Using V2V Communication ," Master's Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), June 2023. (Advisors: Julian Heinovski and Tobias Hardes ; Referees: Falko Dressler and Christoph Sommer ) [ BibTeX , Details... ]
• Wenyuan Hou, " Simulative study of envisioned LiFi-PLC network ," Master's Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), May 2023. (Advisor: Anatolij Zubow ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• Kim Felix Petto, " Presence Detection using Channel State Information from 802.11 WiFi ," Bachelor Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), May 2023. (Advisor: Anatolij Zubow ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• Rebecca Corinna Pampu, " Identification of the Signal Source among Multiple Simultaneous Senders in an Air-based Molecular Communication Channel ," Bachelor Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), January 2023. (Advisor: Lukas Stratmann ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• Abdalrhman Mhrok, " Abnormality Detection in Blood Vessels via Mobile Nanosensors ," Bachelor Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), January 2023. (Advisor: Jorge Torres Gómez ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• " On Time Constraints for Internet-Connected Virtual Cycling Environments ," Master's Thesis, Department of Computer Science, Paderborn University (UPB), December 2022. (Advisors: Falko Dressler and Lukas Stratmann ; Referees: Florian Klingler and Falko Dressler )
• Nils Einfeldt, " Design of a Low-Cost Software-Defined Radio System Based on Waveform Emulation ," Bachelor Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), November 2022. (Advisor: Anatolij Zubow ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• Yago Agustin Illing Arizti, " Feasibility Study of the DyMoNet Approach ," Bachelor Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), November 2022. (Advisors: Gurjashan Singh Pannu and Fabian Missbrenner ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• Sascha Rösler , " Opportunistic Routing in LoRa-based Wireless Mesh Networks ," Master's Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), October 2022. (Advisor: Anatolij Zubow ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• Arndt Busse, " Simulation Model of the DyMoNet Architecture ," Bachelor Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), October 2022. (Advisor: Gurjashan Singh Pannu ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• Tian Xia, " Strategies for Coexistence of 802.11 Wi-Fi and LTE in Context of Low Latency Communications ," Master's Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), September 2022. (Advisor: Anatolij Zubow ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• Martin Kappen, " A Software-based Prototype for Integration of LiFi in Heterogeneous Layer-2 Networks ," Bachelor Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), September 2022. (Advisor: Kai Lennert Bober ; Referees: Falko Dressler and Volker Jungnickel) [ BibTeX , Details... ]
• Clemens Henrich Pago, " Opt-LTE: LTE over an Optical Wireless Channel ," Master's Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), August 2022. (Advisor: Anatolij Zubow ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• Thanh Son Tran, " Study of IRS Assignment Strategies in Cooperative IRS-Aided Communication ," Bachelor Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), August 2022. (Advisor: Anatolij Zubow ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• Niels Raddatz, " Evaluation of a reinforcement learning approach for interference management in WiFi ," Master's Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), July 2022. (Advisor: Anatolij Zubow ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• Robert Jaschek, " Using Reinforcement Learning for Management of Fixed Wireless Access Networks ," Bachelor Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), July 2022. (Advisor: Sebastian Bräuer ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• Jonathan Simon Burggraf, " Modeling and Simulating Chemotaxis Bacteria Networks in MATLAB ," Master's Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), July 2022. (Advisor: Jorge Torres Gómez ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• Hendrik Bojan Lottermoser, " Experimentelle Evaluation des 802.11 FTM Protokolls mit COTS WiFi Hardware ," Bachelor Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), June 2022. (Advisor: Anatolij Zubow ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• Waldemar Faist, " Coordinated Coexistence of LoRa and Wi-Fi in Unlicensed 2.4 GHz ISM Radio Band ," Bachelor Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), June 2022. (Advisor: Anatolij Zubow ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• Lukas Tim Karal, " Development of a Virtual IP Overlay Network for experimental Investigations of Routing-Protocols for Teaching Purposes ," Bachelor Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), June 2022. (Advisor: Berthold Rathke ; Referees: Falko Dressler and Wilko Reichwein) [ BibTeX , Details... ]
• Qi Yu, " Investigating Cooperative Join and Merge Maneuvers for Platoons on Freeways ," Master's Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), May 2022. (Advisor: Julian Heinovski ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• Maximilian W. Gotthardt, " Evaluation of protocols for control stage lighting ," Bachelor Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), March 2022. (Advisor: Anatolij Zubow ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• Matis Tartié, " Modelling the Human Circulatory System with Electric Circuits ," Bachelor Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), March 2022. (Advisor: Jorge Torres Gómez ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• Timo Schlegel, " Design of a V2V-based Cooperative Re-Ordering Maneuver for Platoons on Freeways ," Bachelor Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), February 2022. (Advisor: Julian Heinovski ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• Paola Cecilia Torrico Morón, " UWB Mesh Network and Positioning for Multi-robot Systems ," Master's Thesis, Telecommunication Networks Group (TKN), TU Berlin (TUB), January 2022. (Advisor: Tomi Westerlund; Referees: Falko Dressler and Tomi Westerlund) [ BibTeX , Details... ]
• Shuangrui Liu, " Predicting V2X mmWave Link-State at Intersections ," Master's Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), January 2022. (Advisor: Max Schettler ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• Leon Winkelmann, " A Framework for Generation of Typical Experiment Scenarios for VRU Safety within the VCE ," Bachelor Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), November 2021. (Advisor: Julian Heinovski ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• Julia Mandana Horvath, " Analysing the Proposed Communication Protocol for Multi-Brand Truck Platooning in Europe ," Bachelor Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), November 2021. (Advisors: Julian Heinovski , Dominik S. Buse and Max Schettler ; Referees: Falko Dressler and Thomas Sikora) [ DOI , BibTeX , Details... ]
• Ahmad Alaswad, " Encrypted Traffic Detection: Beyond The Port-number Era ," Master's Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), September 2021. (Advisor: Hossein Doroud ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• Alexander Mauren, " Simulation of a Hybrid Sensor Network ," Bachelor Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), September 2021. (Advisors: Johannes Blobel and Andreas Fischer; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• Thomas Kapp, " Speeding-Up Snort with Traffic Classification ," Bachelor Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), September 2021. (Advisor: Hossein Doroud ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• Omar Alkhateeb, " Adaptive Anomaly Detection: Batch Learning ," Master's Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), September 2021. (Advisor: Hossein Doroud ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• Vivien Annabelle Jiranek, " Automatic Positioning of Street Signs from Map Data for Virtual Cycling Environment ," Bachelor Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), August 2021. (Advisor: Lukas Stratmann ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• " Dooring as a Hazard for Bicyclists - Modelling Hazard Scenarios in an Interactive Real-time 3D Simulation ," Master's Thesis, Department of Computer Science, Paderborn University (UPB), August 2021. (Advisors: Ingrid Scharlau and Falko Dressler ; Referees: Ingrid Scharlau and Falko Dressler )
• Tasaprom Suptongchai, " Data Management Strategies for Vehicular Micro Clouds using DSRC and D2D Hybrid Networks ," Master's Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), July 2021. (Advisor: Gurjashan Singh Pannu ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• Konstantin Köhler, " Modeling Cyclist Behavior in SUMO based on the SimRa Dataset ," Master's Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), July 2021. (Advisors: Ahmet-Serdar Karakaya and Julian Heinovski ; Referees: David Bermbach and Falko Dressler ) [ BibTeX , Details... ]
• Christos Laskos , " Extension of ns-3 Network Simulator to support WiFi-based Fine Time Measurement (FTM) for Indoor Ranging and Positioning ," Bachelor Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), June 2021. (Advisor: Anatolij Zubow ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• Julian Bilden, " A V2X-based Framework for Advanced Driver Assistance Systems for Vulnerable Road Users ," Bachelor Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), May 2021. (Advisors: Julian Heinovski and Lukas Stratmann ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• Nicolas Emanuel Burda, " Untersuchung der Eignung einer SDR/C-RAN-basierten Architektur für Wireless LAN ," Bachelor Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), March 2021. (Advisor: Anatolij Zubow ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• Jirapa Lapanant, " The Impact of Dynamicity while Placing Multi-Resolution Sensor Logs in a Cloud-Fog Topology ," Master's Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), March 2021. (Advisor: Daniel Happ ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• Pimpisa Watthanavarangkul, " Optimally Placing Multi-Resolution Sensor Logs and Brokers in a Cloud-Fog Topology ," Master's Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), March 2021. (Advisor: Daniel Happ ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• " Future-based Acceleration of V2X Simulation ," Bachelor Thesis, Department of Computer Science, Paderborn University (UPB), February 2021. (Advisor: Dominik S. Buse ; Referees: Falko Dressler and Christian Plessl)
• Dominic Simon, " Device-free Passive Localization using Millimeter Wave Radios ," Master's Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), January 2021. (Advisor: Anatolij Zubow ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• Julius Ostermann, " Analyzing and predicting Topic Behaviour on public MQTT Servers ," Bachelor Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), January 2021. (Advisor: Daniel Happ ; Referees: Falko Dressler and Thomas Sikora) [ BibTeX , Details... ]
• Martin Strunz, " Design of a Cooperative Overtaking Algorithm for Platoons on Freeways ," Bachelor Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), December 2020. (Advisor: Julian Heinovski ; Referees: Falko Dressler and Thomas Sikora) [ DOI , BibTeX , Details... ]
• Martin Fleischer, " Centralized Management of 802.11 Fixed Wireless Access Networks ," Master's Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), December 2020. (Advisor: Sebastian Bräuer ; Referees: Anatolij Zubow and Thomas Sikora) [ BibTeX , Details... ]
• " Provisioning radio fallback for directional wireless channels ," Master's Thesis, Department of Computer Science, Paderborn University (UPB), September 2020. (Advisor: Max Schettler ; Referees: Falko Dressler and Christian Scheideler)
• " Experimental Study on the Coexistence of legacy IEEE 802.11 WLAN and IEEE 802.11ba Wake-Up Radio (WUR) ," Master's Thesis, Department of Computer Science, Paderborn University (UPB), August 2020. (Advisor: Johannes Blobel ; Referees: Falko Dressler and Holger Karl)
• Anke Kuestner, " A Simulation Framework for Connecting In-Body Nano Communication with Out-of-Body Devices ," Bachelor Thesis, Department of Computer Science, Paderborn University (UPB), June 2020. (Advisors: Lukas Stratmann and Falko Dressler ; Referees: Falko Dressler and Holger Karl) [ DOI , BibTeX , Details... ]
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Thesis Proposal

In the thesis proposal, the PhD or DES student lays out an intended course of research for the dissertation.  By accepting the thesis proposal, the student’s dissertation proposal committee agrees that the proposal is practicable and acceptable, that its plan and prospectus are satisfactory, and that the candidate is competent in the knowledge and techniques required, and formally recommends that the candidate proceed according to the prospectus and under the supervision of the dissertation committee. It is part of the training of the student’s research apprenticeship that the form of this proposal must be as concise as those proposals required by major funding agencies.

The student proposes to a committee consisting of the student’s advisor and two other researchers who meet requirements for dissertation committee membership.  The advisor should solicit the prospective committee members, not the student. In cases where the research and departmental advisors are different , both must serve on the committee.

The student prepares a proposal document that consists of a core, plus any optional appendices. The core is limited to 30 pages (e.g., 12 point font, single spacing, 1 inch margins all around), and should contain sections describing 1) the problem and its background, 2) the innovative claims of the proposed work and its relation to existing work, 3) a description of at least one initial result that is mature enough to be able to be written up for submission to a conference, and 4) a plan for completion of the research. The committee commits to read and respond to the core, but reserves the right to refuse a document whose core exceeds the page limit. The student cannot assume that the committee will read or respond to any additional appendices.

The complete doctoral thesis proposal document must be disseminated to the entire dissertation committee no later than two weeks (14 days) prior to the proposal presentation. The PhD Program Administrator must be informed of the scheduling of the proposal presentation no later than two weeks (14 days) prior to the presentation. Emergency exceptions to either of these deadlines can be granted by the Director of Graduate Studies or the Department Chair on appeal by the advisor and agreement of the committee.

A latex thesis proposal template is available here .

PRESENTATION AND FEEDBACK

The student presents the proposal in a prepared talk of 45 minutes to the committee, and responds to any questions and feedback by the committee.

The student’s advisor, upon approval of the full faculty, establishes the target semester by which the thesis proposal must be successfully completed. The target semester must be no later than the eighth semester, and the student must be informed of the target semester no later than the sixth semester.

The candidacy   exam  must be successfully completed  before  the  proposal can be attempted.  The proposal must be completed prior to submitting the application for defense. [Instituted by full faculty vote September 16, 2015.]

Passing or failing is determined by consensus of the committee, who then sign the dissertation proposal form (sent to advisors by phd-advising@cs.  Failure to pass the thesis proposal by the end of the target semester or the eighth semester, whichever comes first, is deemed unsatisfactory progress: the PhD or DES student is normally placed on probation and can be immediately dismissed from the program. However, on appeal of the student’s advisor, one semester’s grace can be granted by the full faculty.

Last updated on October 16, 2023.

Find open faculty positions here .

Computer Science at Columbia University

Upcoming events, in the news, press mentions, dean boyce's statement on amicus brief filed by president bollinger.

President Bollinger announced that Columbia University along with many other academic institutions (sixteen, including all Ivy League universities) filed an amicus brief in the U.S. District Court for the Eastern District of New York challenging the Executive Order regarding immigrants from seven designated countries and refugees. Among other things, the brief asserts that “safety and security concerns can be addressed in a manner that is consistent with the values America has always stood for, including the free flow of ideas and people across borders and the welcoming of immigrants to our universities.”

This recent action provides a moment for us to collectively reflect on our community within Columbia Engineering and the importance of our commitment to maintaining an open and welcoming community for all students, faculty, researchers and administrative staff. As a School of Engineering and Applied Science, we are fortunate to attract students and faculty from diverse backgrounds, from across the country, and from around the world. It is a great benefit to be able to gather engineers and scientists of so many different perspectives and talents – all with a commitment to learning, a focus on pushing the frontiers of knowledge and discovery, and with a passion for translating our work to impact humanity.

I am proud of our community, and wish to take this opportunity to reinforce our collective commitment to maintaining an open and collegial environment. We are fortunate to have the privilege to learn from one another, and to study, work, and live together in such a dynamic and vibrant place as Columbia.

Mary C. Boyce Dean of Engineering Morris A. and Alma Schapiro Professor

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Thesis Topics in Computer Science - PowerPoint PPT Presentation

Thesis Topics in Computer Science

This presentation contains all the latest thesis topics in the field of computer science. find out what are those topics. – powerpoint ppt presentation.

• For M.Tech and PhD
• Computer Science is the most popular and thriving field of study these days due to a large number of career opportunities in this field of study. Nowadays, computer science finds its application in almost every field from healthcare to manufacturing. The number of job opportunities in this field is going to increase in the coming future since we are moving towards an era of digitization. For this digitization, there is a need for highly skilled computer science engineers.  There are various computer science topics and fields in which you can do mastery.
• Image Processing
• Mobile Cloud Computing
• Natural Language Processing
• Wireless Ad-hoc Network
• Data Mining
• Computer Vision
• Internet of Things(IoT)
• Machine Learning
• Wireless Body Area Network(WBAN)
• Image Processing is a technique for performing operations on digital images in order to alter their features and enhance their quality. Through image processing, we can also extract valuable statistics from the images. It is one of the rapidly growing fields these days and a hot topic for research and thesis in computer science. Image Processing is further divided into two types
• Analog Image Processing
• Digital Image Processing
• Mobile Cloud Computing or MCC is a technology which is a combination of mobile computing, cloud computing, and wireless networks to provide computational resources to mobile users, cloud providers, and network operators. In other words, we can say that mobile cloud computing delivers applications to mobile devices using the concept of cloud computing. It offers tremendous business opportunities for mobile network operators as well as cloud service providers. It is also a good topic for an M.Tech thesis in computer science.
• Natural Language Processing or NLP is an application area of Artificial Intelligence through which computers can understand and manipulate human language. It is also an important area for the thesis in computer science. It has the following two main components
• Natural Language Understanding - Mapping the natural language into useful representations
• Natural Language Generation - Generating meaningful sentences from the representations 
• Wireless Ad-hoc Network or WANET is a type of wireless network that does not use pre-existing infrastructure for communication. In this network, routing is initiated by a node that transfers the data packet to other nodes by following data routing algorithms. The nodes in the network communicate with each other directly without any central access point like a router.
• Data Mining is a process of extracting information and discovering patterns from the large data-sets. It is another trending technology these days and an important area of research. The information extracted from data-sets can be used for future predictions.
• Computer Vision is another important area of computer science. It is a sub-field of artificial intelligence that aims to provide human vision and perception to computers. For computer vision, real-world data is taken into consideration in order to make decisions. There are certain algorithms developed for the process of computer vision. It involves three main processes which are
• Image Acquisition
• Image Analysis and interpretation
• Big Data refers to the collection of a large amount of data generated through different sources and which may be structured or unstructured. This data is complex to manage and certain advanced techniques like predictive analytics are used in order to extract information from this data. There are various application areas of big data including government, healthcare, business analysis, e-commerce, meteorology etc.
• Internet of Things or IoT is a technology through which a number of physical devices are connected to each other through the internet. The devices are equipped with sensors and actuators to act according to their surrounding environment. This technology is constantly evolving. There are various applications of the Internet of Things (IoT) which includes home automation, smart cars, environment monitoring, smart traffic control, etc.
• Machine Learning is an application of Artificial Intelligence that provides computers and systems the capability to learn automatically from the previous data without being specifically programmed. It is currently the hot field both for research and thesis. There are algorithms designed for machine learning process such that the systems can identify patterns from data-sets and make decisions accordingly.
• Wireless Body Area Network or WBAN is a wireless network in which some computing devices are embedded inside the human body to monitor the health of a person and his day-to-day activities. The idea of WBAN originated from the concept of wireless personal area network(WPAN). It has paved the way for the new era of medical diagnosis.
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