aalto master thesis computer science

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Department of Computer Science

• Aalto University
• School of Science
• Website https://www.aalto.fi/en/department-of-computer-science

Konemiehentie 2 , Computer Science building

Organisation profile

Profile information.

Department of Computer Science provides world-class research and education in modern computer science to foster future science, engineering and society. The work combines fundamental research with innovative applications.

The Department of Computer Science (CS) is the largest department at Aalto University and the largest CS unit in Finland with 44 professors, 20 lecturers and more than 500 employees. The department is part of the School of Science in Aalto University, located on the Otaniemi campus.

The department is known for its innovative and consistently high-quality work matching the very best teams in the world, and is a coveted partner in international collaborations. Research at the department addresses and solves challenging problems of high practical relevance with revolutionary applications.

Research.aalto.fi - our staff profiles and publications

• Professors of Practice (PoP)
• Academic staff
• Publications

Computer Science Research areas

Research in the Department of Computer Science is divided into 14 research areas.

Algorithms and Theoretical Computer Science ( Web-page ) - Fundamental methods and mathematics of computation. 

Artificial Intelligence and Machine Learning ( Web-page ) - Fundamentals and practical impact of AI on businesses and societies.

Complex Systems ( Web-page ) - Network science, stochastic processes and nonlinear dynamics.

Computational Life Sciences ( Web-page ) - Research on Computational modelling, data analysis and design of biological systems.

Computing education research and educational technology ( Web-page ) - Computer science, psychology, and education.

Computing Systems ( Web-page ) - The study, design and development of modern computing systems.

Digital Ethics, Society and Policy ( Web-page ) - Engaging the societal impact of technologies through transdisciplinary inquiry and ethical practices.

• Engineering Psychology

Human-Computer Interaction and Design ( Web-page ) - Intersection of computing, interaction technologies and human-centred design research.

Large-scale Computing and Data Analysis ( Web-page ) - Large-scale distributed/parallel systems and big data analysis and management.

• Quantum Software and Algorithms

Security and Privacy ( Web-page ) - Secure and private computing and communication systems.

Software and Service Engineering ( Web-page ) - Designing, developing, and operating software systems and digital services.

Visual Computing ( Web-page ) - Creation and understanding of images, shapes, and 3D spaces.

UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. Our work contributes towards the following SDG(s):

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• Models Computer Science 100%
• User Computer Science 58%
• Networks Computer Science 49%
• Algorithms Computer Science 46%
• Application Computer Science 40%
• Design Computer Science 35%
• Service Computer Science 23%
• Contexts Computer Science 22%

Collaborations and top research areas from the last five years

Dive into details.

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Mustapha Abdullahi

• Department of Computer Science - Doctoral Researcher
• School common, SCI

Person: Doctoral students, Doctoral Student

Shamsiiat Abdurakhmanova

• Department of Computer Science - Postdoctoral Researcher
• Professorship Jung Alexander - Postdoctoral Researcher

Person: Postdoctoral researchers

• Professorship Guckelsberger Christian - Postdoctoral Researcher
• 1 Not started
• 365 Finished

Projects per year

MATINE 3D-mallinnus/Kannala: Sisätilojen ja avoimen ympäristön 3D-mallinnus maanpuolustuksessa

Kannala, J.

01/04/2024 → 31/12/2025

Project : Other external funding: Other government funding

Mobility COSMAGG/Korpi-Lagg: Investigating COSmic MAGnetism with GPU-accelerated codes

Korpi-Lagg, M.

01/04/2024 → 31/03/2026

Project : Academy of Finland: Other research funding

• Star Formation 100%
• Calculation 100%
• Parameter 100%
• Interstellar Matter 100%
• Magnetohydrodynamic Generator 100%

-: FCAI Flag R5 research/HM

Mannila, H.

01/03/2024 → 31/12/2026

• Artificial Intelligence 100%
• Modeling 25%
• Materials of Design 25%
• Academia 25%
• Medical Treatment 25%

Research output

• 6695 Conference article in proceedings
• 4250 Article
• 844 Working paper
• 638 Chapter
• 372 Doctoral Thesis
• 162 Anthology
• 138 Software
• 105 Abstract
• 90 Review Article
• 64 Conference article
• 55 Editorial
• 38 Commissioned report
• 34 Licenciate's thesis
• 31 Other contribution
• 28 Meeting Abstract
• 28 Special issue
• 18 Master's thesis
• 15 Comment/debate
• 12 Foreword / postscript
• 7 Digital or Visual Products
• 6 Exhibition
• 4 Literature review
• 4 Blog article
• 3 Data Article
• 2 Entry for encyclopedia / dictionary
• 2 Other chapter contribution
• 1 Book/Film/Article review
• 1 Performance

Research output per year

A comparative study of clinical trial and real-world data in patients with diabetic kidney disease

Research output : Contribution to journal › Article › Scientific › peer-review

• Real-World Data 100%
• Randomized Controlled Trial 100%
• Data Set 33%
• Cluster Analysis 22%
• Control 11%

Advancing Self-Determination Theory With Computational Intrinsic Motivation: The Case of Competence

Research output : Other contribution › Scientific

• Self-Determination Theory 100%
• Verbal Definition 25%
• Psychological Research 25%
• Seeking Behavior 25%
• Novelty 12%

"AI enhances our performance, I have no doubt this one will do the same": The Placebo effect is robust to negative descriptions of AI

Research output : Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

• Expectations 100%
• Discrimination 14%
• Bayesian Analysis 14%
• Cognitive Modeling 14%

References to Qing China Technology and Industry in Finnish Technical Journals 1880-1912

La Mela, M. (Creator) & Fridlund, M. (Creator), Zenodo, 2019

DOI : 10.5281/zenodo.2607892

This is accompanying conference participation datasets for the PLoS ONE 2016/11(2) publication "A Theoretical Model for the Associative Nature of Conference Participation"

Smiljanić, J. (Creator), Chatterjee, A. (Creator), Kauppinen, T. (Creator) & Mitrović-Dankulov, M. (Creator), figshare, 2016

DOI : 10.6084/m9.figshare.2066907.v2 , https://figshare.com/articles/Conference_Datasets/2066907

IoT devices captures

Marchal, S. (Creator), Aalto University, 3 Apr 2017

DOI : 10.24342/285a9b06-de31-4d8b-88e9-5bdba46cc161

2016 CPHC/BCS Academy of Computing Distinguished Dissertation runner-up

Micallef, Luana (Recipient), 2016

Prize : Award or honor granted for a specific work

• Computing 100%

2016 De Groot Prize

Vehtari, Aki (Recipient), 16 Jun 2016

2016 Learning Contribution Achievement Award 2016

Kauppinen, Tomi (Recipient) & Malmi, Lauri (Recipient), 20 May 2017

• Teaching 100%
• Contribution 100%
• Achievement 100%
• Learning 100%
• Awards 100%
• 1063 Visiting an external academic institution
• 1061 Hosting an academic visitor
• 604 Membership of a scientific or program committee of a conference or seminar
• 420 Invited academic talk
• 393 Membership of an editorial board
• 373 Position of trust in a society or network
• 367 Conference presentation
• 257 Reviewer of scientific journal
• 188 Pre-examination of doctoral thesis or acting as opponent to doctoral students or membership of doctoral thesis committee or board
• 129 Participant of a conference, workshop, session, tutorial or event
• 123 Organization of a workshop, panel, session, tutorial or event
• 111 Membership of an organizing committee or other positions of trust of a conference or a seminar
• 104 Position of trust in an academic community
• 102 Chair or participant of a conference, workshop, panel, session, tutorial or event
• 99 Reviewer of conference article
• 84 Academic keynote or plenary lecture
• 57 Evaluation of funding applications
• 54 Statement of assessment of professorship
• 34 Non-academic public talk (public outreach)
• 31 Regular membership of a society or network
• 23 Position of trust in a funding organization
• 16 Evaluation of significant academic activities
• 14 Statement of assessment of docentship
• 14 Membership of a competition jury
• 12 Work for advisory/policy/evaluation group or panel (public/government/UN/EU)
• 7 Organization of an event for a non-academic audience (public outreach)
• 7 Other expert tasks or merit
• 6 Consultancy and expert advice (including statements)
• 6 Evaluation of other academic activities
• 6 Studying in an external academic institution
• 5 Appointed supervisor or advisor of postgraduates at Higher Education Institutions.
• 4 Statement of assessment of other positions
• 4 Academic qualification (e.g. title of docent)
• 4 Teaching merits
• 3 Work for advisory/policy/evaluation group or panel (non-public/non-government/industry)
• 2 School engagement
• 2 Reviewer of other manuscript
• 2 Appointed supervisor or advisor of undergraduates at Higher Education Institutions.
• 1 Editor-in-chief in a journal or in a book series

Activities per year

Crowd-sensing commuting patterns using multi-source wireless data

Zhiren Huang (Speaker), Charalampos Sipetas (Contributor), Alonso Espinosa Mireles de Villafranca (Contributor) & Tri Quach (Contributor)

Activity : Talk or presentation types › Conference presentation

Data Science for Transportation (Journal)

Zhiren Huang (Reviewer)

Activity : Publication peer-review and editorial work types › Reviewer of scientific journal

Suomalaisen uutismediakentän käsitykset disinformaatiosta

Minttu Tikka (Speaker) & Henna Paakki (Contributor)

Press/Media

Moni luopui äly­puhelimestaan – näin kävi.

Janne Lindqvist

1 item of Media coverage

Press/Media : Media appearance

Koetellaanko kyberturvallisuutta, kun eurovaalit lähestyvät?

Mikko Kiviharju

Vaalit ja kybervaikuttaminen

MyCourses out of service on today 2.5.2024 from 10:00 to 17:00 due to update. Please save your work before 10:00

SCI Master's Thesis Guide 2023-

1. where can i find a supervisor for my thesis.

• As a default, the master’s thesis is written on a topic related to the student’s chosen major. The supervisor should be a professor or lecturer from the field of the chosen major. See the list of possible supervisors below. 
• Contact details of professors and lecturers are usually [email protected] and can be found  here.

2. Who are the supervisors in IEM?

3. exceptions for topic & supervisor.

• Operations Management: Lauri Saarinen, [email protected]
• Organization Design and Leadership: Jari Ylitalo, [email protected]
• Product and Innovation Management: Mikko Jääskeläinen, [email protected]
• Strategy: Kimmo Karhu, [email protected]
• Study Coordinator: Jasmin Seppälä, [email protected]
• B)  If supervision would benefit from the specific expertise of a professor or lecturer who is not from the field of the chosen major, instead of acting as a supervisor, this person may also act as an advisor. In this case the supervisor is a professor or lecturer in the field of the chosen major. He or she and the advisor agree on the actual supervision and evaluation, but the supervisor is ultimately responsible for the evaluation. 
• Send an email to the program director and add as CC the proposed supervisor and study coordinator. 
• Program Director: Jens Schmidt, [email protected]
• NB! Even if you are writing your thesis on a topic related to your chosen minor, you must complete a maturity test according to these instructions . 

4. Evaluation

• All master’s theses must be evaluated according to the SCI guidelines for master’s thesis evaluation. 
• For all master’s theses written on a topic related to the student’s chosen major where the supervising professor is not a professor at the IEM department, the professor responsible for the major will need to approve and sign the evaluation form in addition to the supervising professor. 
• For all master’s theses written on a topic related to the student’s chosen minor, the program director will need to approve and sign the evaluation form in addition to the supervising professor. 

 5. DIEM Master's Thesis Info

Iem masters thesis event 2023 pp-slides   iem masters thesis event video from 14.11.2022 , https://mycourses.aalto.fi/pluginfile.php/2106636/mod_page/content/79/iem%20masters%20thesis%20event%2014.11.2022.mp4  .

Aalto computer scientists in CHI 2024

The ACM (Association of Computing Machinery) CHI conference on Human Factors in Computing Systems is the premier international conference in the field of Human-Computer Interaction. This year the conference takes place in Honolulu, Hawaii, USA from May 11th-16th, 2024.

Best Paper award for Jaakko Väkevä, Elisa D. Mekler and Janne Lindqvist for the paper " From Disorientation to Harmony: Autoethnographic Insights into Transformative Videogame Experiences ". Honorable Mention award for Solip Park, Perttu Hämäläinen and Annakaisa Kultima for the paper " Comic-making to Study Game-making: Using Comics in Qualitative Longitudinal Research on Game Development".

Researchers develop a new way to instruct dance in Virtual Reality

The researchers started by experimenting with visualisation techniques familiar from previous dance games. But after several prototypes and stages, they decided to try out the audience wave, familiar from sporting events, to guide the dance.

Keeping your data from Apple is harder than expected

New study shows that the default apps collect data even when supposedly disabled, and this is hard to switch off

Just believing that an AI is helping boosts your performance

People perform better if they think they have an AI assistant – even when they’ve been told it’s unreliable and won’t help them

Accepted papers

In alphabetical order. Click the title to see the authors and the abstract.

A Robot Jumping the Queue: Expectations About Politeness and Power During Conflicts in Everyday Human-Robot Encounters

Franziska Babel, Linda Miller, Sam Thellman, Robin Welsch, Philipp Hock, and Tom Ziemke 

Increasing encounters between people and autonomous service robots may lead to conflicts due to mismatches between human expectations and robot behaviour. This interactive online study (N = 335) investigated human-robot interactions at an elevator, focusing on the effect of communication and behavioural expectations on participants' acceptance and compliance. Participants evaluated a humanoid delivery robot primed as either submissive or assertive. The robot either matched or violated these expectations by using a command or appeal to ask for priority and then entering either first or waiting for the next ride. The results highlight that robots are less accepted if they violate expectations by entering first or using a command. Interactions were more effective if participants expected an assertive robot which then asked politely for priority and entered first. The findings emphasize the importance of power expectations in human-robot conflicts for the robot's evaluation and effectiveness in everyday situations.

"AI enhances our performance, I have no doubt this one will do the same": The Placebo Effect Is Robust to Negative Descriptions of AI

Agnes M. Kloft, Robin Welsch, Thomas Kosch, and Steeven Villa 

Heightened AI expectations facilitate performance in human-AI interactions through placebo effects. While lowering expectations to control for placebo effects is advisable, overly negative expectations could induce nocebo effects. In a letter discrimination task, we informed participants that an AI would either increase or decrease their performance by adapting the interface, when in reality, no AI was present in any condition. A Bayesian analysis showed that participants had high expectations and performed descriptively better irrespective of the AI description when a sham-AI was present. Using cognitive modeling, we could trace this advantage back to participants gathering more information. A replication study verified that negative AI descriptions do not alter expectations, suggesting that performance expectations with AI are biased and robust to negative verbal descriptions. We discuss the impact of user expectations on AI interactions and evaluation.

Comic-making to Study Game-making: Using Comics in Qualitative Longitudinal Research on Game Development

Received an Honorable Mention

Solip Park, Perttu Hämäläinen, and Annakaisa Kultima

This paper reports the research method of the “Game Expats Story (GES)” project that used qualitative longitudinal research (“QLR”) incorporated with art-based research (“ABR”) in the context of game research. To facilitate greater participant engagement and a higher retention rate of longitudinal participants, we created comic artwork simultaneously while researching the case of migrant/expatriate game developers (“game expats”) in Finland 2020-2023 in two phases: (i) art creation as part of the qualitative data analysis to supplement the researcher’s inductive abstraction of the patterns, and (ii) artwork as a communication and recall tool when periodically engaging with the informants over the multi-year project span. Our findings suggest that the method of QLR-ABR helps game research as it positively influences the researcher’s abstractions of longitudinal data and participants’ continuous engagement with a high retention rate of 89%. We conclude that incorporating artistic methods provides new opportunities for ethnographic research on game development.

From Disorientation to Harmony: Autoethnographic Insights into Transformative Videogame Experiences

Received a Best Paper Award

Jaakko Väkevä, Elisa D. Mekler, and Janne Lindqvist

Videogames can transform the perspectives and attitudes of players. Prior discussion on this transformative potential has typically been limited to non-entertainment videogames with explicit transformational goals. However, recreational gaming appears to hold considerable potential for igniting deeply personal experiences of profound transformation in players. Towards understanding this phenomenon, we conducted an explorative autoethnographic study. For this, the first author played five narrative-driven videogames while collecting self-observational and self-reflective data of his experience during and outside gameplay. Our findings offer intimate insights into the trajectory and emotional qualities of personally meaningful and transformative videogame experiences. For example, we found that gameplay experiences that were initially perceived as bewildering or disorienting could evolve into more harmonious experiences laden with personal meaning. This shift in experience developed through different forms of subsequent re-engagement with initially discrepant game encounters.

Grand Challenges in SportsHCI

Don Samitha, Regina Bernhaupt, Armağan Karahanoğlu, Carine Lallemand, Daniel Harrison, Dennis Reidsma, Maria F. Montoya  Dees Postma, Elise van den Hoven, Florian Daiber, Lars Elbæk, Lisa Anneke Burr, Rakesh Patibanda, Michael D Jones, Paolo Buono, Perttu Hämäläinen, Xipei Ren, Robby van Delden, Vincent van Rheden, Fabio Zambetta, and Florian ‘Floyd’ Mueller

The field of Sports Human-Computer Interaction (SportsHCI) investigates interaction design to support a physically active human being. Despite growing interest and dissemination of SportsHCI literature over the past years, many publications still focus on solving specific problems in a given sport. We believe in the benefit of generating fundamental knowledge for SportsHCI more broadly to advance the field as a whole. To achieve this, we aim to identify the grand challenges in SportsHCI, which can help researchers and practitioners in developing a future research agenda. Hence, this paper presents a set of grand challenges identified in a five-day workshop with 22 experts who have previously researched, designed, and deployed SportsHCI systems. Addressing these challenges will drive transformative advancements in SportsHCI, fostering better athlete performance, athlete-coach relationships, spectator engagement, but also immersive experiences for recreational sports or exercise motivation, and ultimately, improve human well-being.

Graph4GUI: Graph Neural Networks for Representing Graphical User Interfaces

Yue Jiang, Changkong Zhou, Vikas Garg, and Antti Oulasvirta

Present-day graphical user interfaces (GUIs) exhibit diverse arrangements of text, graphics, and interactive elements such as buttons and menus, but representations of GUIs have not kept up. They do not encapsulate both semantic and visuo-spatial relationships among elements. To seize machine learning's potential for GUIs more efficiently, Graph4GUI exploits graph neural networks to capture individual elements' properties and their semantic-visuo-spatial constraints in a layout. The learned representation demonstrated its effectiveness in multiple tasks, especially generating designs in a challenging GUI autocompletion task, which involved predicting the positions of remaining unplaced elements in a partially completed GUI. The new model's suggestions showed alignment and visual appeal superior to the baseline method and received higher subjective ratings for preference. Furthermore, we demonstrate the practical benefits and efficiency advantages designers perceive when utilizing our model as an autocompletion plug-in.

Navigating the Virtual Gaze: Social Anxiety's Role in VR proxemics

Beatriz Mello, Robin Welsch, Marissa Christien Verbokkem, Pascal Knierim, and Martin Johannes Dechant

For individuals with Social Anxiety (SA), interacting with others can be a challenging experience, a concern that extends into the virtual world. While technology has made significant strides in creating more realistic virtual human agents (VHA), the interplay of gaze and interpersonal distance when interacting with VHAs is often neglected. This paper investigates the effect of dynamic and static gaze animations in VHAs on interpersonal distance and their correlation to SA. A Bayesian analysis shows that static-centered and dynamic-centering gaze led participants to stand closer to VHAs than static-averted and dynamic-averting gaze, respectively. In the static gaze conditions, this pattern was found to be reversed in SA: participants with SA traits kept larger distances for static-centered gaze than for averted gaze VHAs. These findings update theory, elucidate how nuanced interactions with VHAs must be designed, and offer renewed guidelines for pleasant VHA interaction.

Not All the Same: Understanding and Informing Similarity Estimation in Tile-Based Video Games

Sebastian Berns, Vanessa Volz, Sam Snodgrass, and Christian Guckelsberger

Similarity estimation is essential for many game AI applications, from procedural generation of distinct assets to automated exploration with game-playing agents. While similarity metrics often substitute human evaluation, their alignment with our judgement is unclear. Consequently, the result of their application can fail human expectations, leading to e.g. unappreciated content or unbelievable agent behaviour. We alleviate this gap through a multi-factorial study of two tile-based games in two representations, where participants (N=456) judged the similarity of level triplets. Based on this data, we construct domain-specific perceptual spaces, encoding similarity-relevant attributes. We compare 12 metrics to these spaces and evaluate their approximation quality through several quantitative lenses. Moreover, we conduct a qualitative labelling study to identify the features underlying the human similarity judgement in this popular genre. Our findings inform the selection of existing metrics, and highlight requirements for the design of new similarity metrics benefiting game development and research.

Privacy of Default Apps in Apple’s Mobile Ecosystem

Amel Bourdoucen, and Janne Lindqvist

Users need to configure default apps when they first start using their devices. The privacy configurations of these apps do not always match what users think they have initially enabled. We first explored the privacy configurations of eight default apps Safari, Siri, Family Sharing, iMessage, FaceTime, Location Services, Find My and Touch ID. We discovered serious issues with the documentation of these apps. Based on this, we studied users' experiences with an interview study (N=15). We show that: the instructions of setting privacy configurations of default apps are vague and lack required steps; users were unable to disable default apps from accessing their personal information; users assumed they were being tracked by some default apps; default apps may cause tensions in family relationships because of information sharing. Our results illuminate on the privacy and security implications of configuring the privacy of default apps and how users understand the mobile ecosystem.

WAVE: Anticipatory Movement Visualization for VR Dancing

Markus Laattala, Roosa Piitulainen, Nadia M. Ady, Monica Tamariz, and Perttu Hämäläinen

Dance games are one of the most popular game genres in Virtual Reality (VR), and active dance communities have emerged on social VR platforms such as VR Chat. However, effective instruction of dancing in VR or through other computerized means remains an unsolved human-computer interaction problem. Existing approaches either only instruct movements partially, abstracting away nuances, or require learning and memorizing symbolic notation. In contrast, we investigate how realistic, full-body movements designed by a professional choreographer can be instructed on the fly, without prior learning or memorization. Towards this end, we describe the design and evaluation of WAVE, a novel anticipatory movement visualization technique where the user joins a group of dancers performing the choreography with different time offsets, similar to spectators making waves in sports events. In our user study (N=36), the participants more accurately followed a choreography using WAVE, compared to following a single model dancer.

Department of Computer Science

cs.aalto.fi

School of Science

Science for tomorrow’s technology, innovations and businesses

Finnish Center for Artificial Intelligence FCAI (external link)

• Published: 6.5.2024
• Updated: 13.5.2024

Read more news

Professor Peter Hans Matthews works as a Fulbright-Aalto Distinguished Chair scholarship holder at the Department of Economics

Aalto ARTS Summer School explores the significance of water through the lens of art

Viktar Asadchy receives Young Scientist Award

Master’s Thesis Defense

Thesis Committee Members: Dr. Guanglan Zhang (Advisor), Dr. Lou Chitkushev (first reader) and Dr. Derin Keskin (second reader)

Monday, May 13th, 2024 10:00am EST 1010 Commonwealth Ave, Room 122

For those unable to attend in person, the thesis defense will be available through Zoom – http://www.bu.edu/metit/edu-technology/zoom-web-conferencing/

Select “Computer Science” from the drop down menu.

As MHC binding is considered the most selective step in T cell recognition, many existing bioinformatics systems focus on modeling this step to predict MHC binders. However, modeling MHC binding alone is insufficient for accurate immunogenicity predictions, often resulting in false positives. With the recent technological advancements, large amounts of mass spectrometry (MS)-identified MHC class I ligands became available to the public, making it possible to incorporate information from antigen processing steps before MHC binding. We collected >5,000 binding peptides and >4,000 eluted ligands for H2-Dᵇ, and>5,000 binding peptides and >5,000 eluted ligands for H2-Kᵇ. The thermostability assessment of MHC peptide binding evaluates the strength and duration of the interaction between the peptide and the MHC molecule under varying temperatures. Our collaborators at the Dana-Farber Cancer Institute performed temperature gradient experiments to investigate the stability of peptide-MHC complexes for H2-Dᵇ and H2-Kᵇ alleles under three temperature conditions, 37°C, 50°C, and 70°C, using the MS technique.  We ended up with over 3,000 H2-Dᵇ binding peptides and over 5,000 H2-Kᵇ binding peptides. The data enable us to perform a comprehensive thermostability analysis of MHC binding.

In this thesis project, we developed a computational system for identifying T-cell epitopes in C57BL/6 mice by integrating relevant contributing factors, such as the antigen processing steps before MHC binding and thermostability, with the MHC binding predictions. Utilizing deep learning methods, we first trained and rigorously validated the binding prediction models using naturally eluted H2-Kᵇ and H2-Dᵇ ligands collected from public resources. Then, we built Thermostability models using proprietary data generated by our collaborators. We compared the performance of our models with that of NetMHCPan-4.1, an online prediction tool validated by many benchmark studies to be one of the most accurate predictors. Our integrated model, combining the binding and the Thermostability models, exhibited superior predictive capabilities using an external validation dataset, surpassing the overall performance of the NetMHCPan-4.1 model.  We consolidated the models into a user-friendly web-based application named PREDBL6 to facilitate accurate predictions of immunogenic peptides that stably bind H2b molecules and stimulate immune responses in C57BL/6 mice. To our knowledge, this is the first online T cell epitope prediction system that simulates MHC binding and considers other antigen processing steps and thermostability in a model organism.

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Master’s Thesis Presentation • Systems and Networking • Parallel Transaction Execution in Public Blockchain Systems

Please note: this master’s thesis presentation will take place in dc 2310.

Rizwan Shahid, Master’s candidate David R. Cheriton School of Computer Science

Supervisors : Professors Bernard Wong and Samer Al-Kiswany

Public blockchain systems like Ethereum and Bitcoin suffer from poor transaction through-put, leading to delayed transaction execution and high transaction fees. They execute transactions one by one failing to extract inherent parallelism possible in executing the workload.

We present Block-X, a parallel transaction processing system with strictly serializable concurrency control for public blockchains. It pre-executes transactions that are waiting to be added to a block. Through this pre-execution, Block-X estimates the keys a transaction wants to read or write. It uses this information to create a parallel execution schedule and run transactions optimistically in parallel following the schedule. It also uses the pre-execution to prefetch data that will be accessed during the critical path transaction execution. If a smart contract transaction accesses data outside of its initially estimated read-write set of keys, Block-X detects and resolves any potential conflicts.

The final state is equivalent to the state produced after the sequential execution of transactions in the block order. Finally, Block-X also accelerates the process of validating blocks by providing the parallel execution schedule produced in the block execution step to validate transactions in parallel.

We implemented our system on Ethereum so it is compatible with EVM chains. Our evaluation demonstrates that Block-X achieves up to a 2.3× higher throughput than Ethereum. Moreover, our performance is comparable to other systems that perform pes-simistic execution. These systems require predefined read-write set and reject transactions that use data outside of it.

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David R. Cheriton School of Computer Science University of Waterloo Waterloo, Ontario Canada N2L 3G1 Phone: 519-888-4567 ext. 33293 Fax: 519-885-1208

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The University of Waterloo acknowledges that much of our work takes place on the traditional territory of the Neutral, Anishinaabeg and Haudenosaunee peoples. Our main campus is situated on the Haldimand Tract, the land granted to the Six Nations that includes six miles on each side of the Grand River. Our active work toward reconciliation takes place across our campuses through research, learning, teaching, and community building, and is co-ordinated within the Office of Indigenous Relations .

Abstract: Gaze-following is an important ability that allows us to understand what people are doing, and what are their intentions. Current research on gaze following is focused on using a single image and restricts the task based on whether the target is in frame or out of frame. A survey of gaze-following datasets revealed defects in the way they collect gaze point labels. Previous datasets rely on annotator votes for determining the actual gaze target location leading to ambiguous ground truths. Also, no existing method investigates cases of occlusion, a common phenomenon in real-world scenarios. Occlusion implies that the gaze target is in frame, but is obstructed by another object making the target unidentifiable. However, current approaches fail to differentiate between visible and occlusion cases when the target is in frame which could lead to incorrect predictions. In this work, we have collected a new dataset, MultiViewGaze, with precise point target annotations in six views for four scenes, that simulate an office, a restaurant kitchen, a shop and a lounge area. We also extend the gaze labels beyond the traditional in-frame and out-of-frame by handling cases of occlusion. We further introduce fine-grained labels for three categories of occlusions - Self-Occlusion, Occlusion due to another object and Occlusion due to subject. While occlusion is common in everyday situations, prior approaches have not delved into this task. We modify two single-view approaches primarily used for gaze following - the VideoAttentionTarget model and the ChildPlay model and train them for the task of Occlusion Detection, achieving good baseline results. Overall, we believe that classifying cases of occlusion and detecting obstructed targets to improve Gaze Following methods is a challenging and important problem and is instrumental in effective scene understanding.