For publications with students, see the Research page.
Grad Students
Sanjana Neelisetty Balaji,
Agentic Multi-Model Pipeline for Invoice Automation, MSc in Applied Computing industry project, 2025-2026
Dawn Duan,
LLMs for Information Extraction, UTIAS M. Eng. project and UTIAS reading course, 2023-2025
Kexin Chen,
Using Social Media Data to Explore Complex Disease, M. Eng. project, 2023-2024; Research and Development of an AI based Software to Recognize Realtime TV Commercials on Low-power Computing Equipment, Mitacs internship, 2024-2025
Chuyi Hou,
Research and Development of an AI based Software to Recognize Realtime TV Commercials on Low-power Computing Equipment, Mitacs internship, 2024-2025
Zixuan Wan,
Enabling Automatic Checking of Empirical Standards Criteria for Academic Publishers, M. Eng project, 2023-2024
Hauze Xu,
Text mining API for automated keywords extraction and tag analysis. Mitacs Business Partnership internship, 2023-2024 M.Eng
Vijaykumar Maraviya,
A Peer Reviewer Recommender System. MEng in Mechanical and Industrial Engineering project, University of Toronto, 2021 (co-supervised with Eldan Cohen).
Danting Ada Dong,
Object Detection and Image Segmentation for Receipt Images. MSc in Applied Computing, University of Toronto, 2021 (co-supervised with Lueder Kahrs).
Elisa Du,
Enriched Understanding of Retail Receipts for Personalized Financial Insights. MSc in Applied Computing, University of Toronto, 2021 (co-supervised with Rohan Alexander).
Thi Hai Van Do,
Merchandise Classification with Machine Learning for E-commerce. MSc in Applied Computing, University of Toronto, 2018.
Undergraduate Student Projects
Kane Pan, Automatic Utterance Labelling with a Local LLM, local Toronto supervisor of collaboration undergraduate student collaboration with Hasson Lab at Princeton University, 2025-2026
Rachel Chan, Learnability of Representability of Patient Time Series Data with Transformers and LSTMs, EngSci thesis, 2025-2026
Lucia Sun, LLMs for large-scale social media analysis for insights on career trajectories in computing, EngSci thesis, 2025-2026
Zhi (Whitney) Ji, Shape-Based Features Complement CLIP Features and Features Learned from Voxels in 3D Object Classification, EngSci thesis, Summer 2025
Minchan Kim, Machine learning for exploring perception of brilliance in music, EngSci thesis, 2024-2025
Paul Yan, Interpreting rotation-variant features in image classification using vision transformers, EngSci thesis, 2024-2025
Andy Cai, Learning representations of microstructures in spatial statistics space for materials design, EngSci thesis, 2024-2025
Ritvik Singh, Optimizing optical spectrometry-based measurement of soil nutrients, EngSci thesis, 2024-2025
Sophie Lee, Quantifying the Complexity of Literary Fiction, EngSci thesis, 2023-2025
Gary Liang, Ronaldo Luo, Cindy Liu, Adam Kabbara, Minahil Bakhtawar, Kina Kim, Undergraduate project on the cognitive science of the game of Wordle, 2024-
Sajjad Hashemi, Improving the cost function of variational autoencoders for material design, Argonne National Laboratory project, 2023-
Haani Ahmed, Speeding Up Reinforcement Learning by Selecting Pretrained Models using Guided Backpropagation, EngSci thesis, 2023-2024
Juho Kim, Exploring the "Honour Culture" Theory Using Social Media Data, EngSci thesis, 2023-2024
Kailyn Yoon, Exploring the Moral Foundations Theory Using Social Media Data, EngSci thesis, 2023-2024
Jasmine Zhang, Robustness in the context of text classification with Transformers, EngSci thesis, 2023-2024
Yiping Wang, Interpretability of ViT when Colour is an Important Cue, EngSci thesis, 2023-2024
Cameron Smith, Interpretability of ConvNets when Colour is an Important Cue, EngSci thesis, 2023-2024
Amy Saranchuk, Interpretability for Self-Supervised Models, EngSci thesis, 2023-2024
Jason Zuo, How do Transformers Use (And Don't Use) Positional Encoding?, EngSci thesis, 2023-2024
Tracy Qian, WGANs for Model Checking of Hierarchical Models for Small Datasets, EngSci thesis, 2023-2024
Niko Marinkovich, Analyzing the Observed Phenomenon that Computer Chess Beat Humans Much Earlier than Computer Go, EngSci thesis, 2023-2024
Kamron Zaidi, Machine Learning of Understanding Brilliant Moves in Board Games, EngSci thesis, 2023-2024
Sadam Alabed Alrazak, Talal Alaeddine, Kevin Karam, Omar Samman, Ahmad Khater, Data Collection on Youth Sports Participation in Canada, MIE capstone project 2023-2024 (client: Sasha Gollish, Faculty of Kinesiology, University of Toronto)
Yichen Mao, Michael Simunec, Jiaming Li, Mavis Chen, Qingyi Xia, Designing, Building, and Validating an App for Coaching Athletes at the University of Toronto, MIE capstone project 2023-2024 (client: Sasha Gollish, Faculty of Kinesiology, University of Toronto)
Pavlos Constas, Vikram Rawal, Matthew Honorio Oliveira, Andreas Constas, Aditya Khan, Kaison Cheung, Najma Sultani, Carrie Chen, Micol Altomare, Michael Akzam, Jiacheng Chen, Vhea He, Lauren Altomare, Heraa Murqi, Asad Khan, Nimit Amikumar Bhanshali, Youssef Rachad, Toward A Reinforcement-Learning-Based System for Adjusting Medication to Minimize Speech Disfluency, summer research project
Ian Wu and Youssef Rachad, Developing materials for introductory computer science courses, work-study students, 2023
Jackson Kaunismaa, Mechanistic Interpretation of Neural Networks, work-study researcher student, 2023
Mustajab Azam, Sajjad Hashemi, Shahzeb Ahmed, Variational Autoencoders for Material Design, MIE Capstone Project, 2023
Sajjad Hashemi, Variational Autoencoders for Material Design (with Noah Paulson)
Jackson Kaunismaa, Mechanistic Interpretation of Neural Networks (independent project, 2022-2023)
Shardul Ghuge, Multivariate Time Series Forecasting of Patient's Health using LSTM (UofT EngSci thesis, 2022-2023)
Jonathan Spraggett, Sim2Real Reinforcement Learning for Soccer skills (UofT EngSci thesis, 2022-2023)
Noelle Lim, Using Machine Learning Transformers to Detect Comorbid Anxiety and ADHD (UofT EngSci thesis, 2022-2023)
Vo Yoang, Investigating How Meaning is Stored and Manipulated by Transformers (UofT EngSci thesis, 2022-2023)
George Saad, Using Pre-Training to Speed Up Deep Reinforcement Learning (UofT EngSci thesis, 2022-2023)
Michael Ruan, Improving Sample Efficiency of Deep Reinforcement Learning With State Representation Learning (UofT EngSci thesis, 2021-2022)
Morgan Sun, Generating Novel Hypotheses from Complex Models of Clinical Data (UofT EngSci thesis, 2021-2022)
Jonathan Spragett, Learning robot soccer-ball-kicking behaviour with reinforcement learning (UofT EngSci thesis, 2021-2022)
Eric Wang, Learning robot walking behaviour with reinforcement learning (UofT EngSci thesis, 2021-2022)
Yize Zhao, Improving content-based video retrieval (UofT EngSci thesis, 2021-2022)
Chi-Chung Cheung, Learning to play Go by playing on smaller Go boards (UofT EngSci thesis, 2021-2022)
Daniel Pinheiro Leal, Pretraining to speed up reinforcement learning for control tasks (UofT EngSci thesis, 2020-2021)
Theodore Block, The Triple Descent Curve when Training Single-Hidden-Layer Neural Networks (UofT EngSci thesis, 2020)
Calvin Tan, Pretraining to speed up Q-learning for card games with large feature spaces (UofT EngSci thesis, 2020-2021)
Coco Zhang, Guided backpropagation and non-monotonic output functions (UofT EngSci thesis, 2020-2021)
Vydhourie Thiyageswaran, May Jiang, and Anthony Hein, Developing an agent for Gin Rummy (Princeton summer work)
Vydhourie Thiyageswaran, Pretraining Transformer Architectures for Q-learning (Princeton CSML IW)
Ryan Lee, Investigating the Double Descent Curve (Princeton Math junior paper, 2020)
Claire S. Lee, Classifying and Understanding Affective States in Bipolar Disorder from Video (Princeton COS498, 2020-)
Daniel K. Chae, Generating Novel Hypotheses from Complex Models of Clinical Data (Princeton COS498, 2020)
Niranjan Shankar, Text Classification for Small Datasets (Princeton COS498, 2020)
Max Piasevoli, Generative Adversarial Networks for Model Checking (Princeton COS498, 2020)
Preeti Iyer, Understanding Urban Mobility in NYC with Latent Factor Models (Princeton undergrad thesis, 2020)
Georgy Noarov, Collecting a Large-Scale Dataset of Fake News (Princeton CSML certificate project 2019-2020)
Ananya Joshi, Creating an Automated Ideological Transformer Using Moral Reframing (Princeton undergrad thesis, 2019)
Navid Korhani, Information Extraction with Small Datasets (UofT EngSci thesis, 2018-2019)
Yoonsun You, Classification of Cervical Spine Fractures in CT Images (UofT EngSci thesis, 2018-2019)
Sam Banning, Information Extraction from Clinical Notes (UofT CSC494, Fall 2017)
Joshua Samson-Seltzer, Computer Vision for Camera Trap Data (UofT GGR417, 2016-2017)
Omobola Okesanjo, Demonstration in Reinforcement Learning (UofT CSC494, Fall 2016)
Ujash Joshi, Photo Orientation Detection with ConvNets (UofT CSC494/CSC495, 2016)
Karo Castro-Wunsch, RNN and Spectral Feature Based Music Analysis and Generation (UofT CSC492, 2016)
Ramaneek Gill, Twitter Hashtag Recommendation and Analysis (UofT CSC494/495, 2015-2016)