This is the homepage of Lisa Zhang.

Teaching
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Undergraduate Research/Project Courses
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Publications
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Contact
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CV

Hi!

I am an Assistant Professor, Teaching Stream at the Department of Mathematical and Computational Sciences (MCS), University of Toronto Mississauga. I hold non-budgetary cross-appointments at the Institute for the Study of University Pedagogy (ISUP) and at the Institute for Management and Innovation (IMI). My office is located at DH3072.

I held many roles during my career: startup founder, data scientist, machine learning researcher, pure math student, and now a computer science educator. I typically teach the machine learning and programming languages courses at UTM, and coordinate the Writing Across the Curriculum (WAC) initiative for our computer science students.

I am a member of the CS Education Research Group at the University of Toronto. My current research interest is in the teaching and learning of machine learning involving a range of learners and goals. I do not supervise graduate students. However, I frequently work with undergraduate students on Computer Science Education related projects.

News: I will be on sabbatical in the 2025-2026 academic year. Besides grant-funded work (RA postings to come soon), my work with undergraduate students will be limited during this time.

Awards
University of Toronto Cheryl Regehr Early Career Teaching Award (2025)
SIGCSE Outstanding Reviewer Award (2025)
UTM Teaching Excellence Award for Junior Faculty (2024)
Koli Calling Superb Reviewer (2024)
SIGCSE Best Paper, Experience Reports and Tools Track (2023)
EAAI New and Future AI Educator Award (2021)
Top 10% of Reviewers, Neural Information Processing Systems (2019)

Teaching

Past courses and archived course websites

Publications

Publications in AI/ML Education

Student Perspectives on the Challenges in Machine Learning Naaz Sibia, Amber Richardson, Alice Gao, Andrew Petersen, Lisa Zhang ITiCSE 2025 ⭐ To appear
Comparing Artificial Intelligence Curricula in Canadian and US Universities Rose Niousha, Lexie Jingruo Guo, Rick Kaifeng Li, Narges Norouzi, Lisa Zhang EAAI 2025 [paper]
Mapping the Pathways: A Comparative Analysis of AI/ML/DS Prerequisite Structures in R1 Institutions in the United States Rose Niousha, Dev Ahluwalia, Michael Wu, Lisa Zhang, Narges Norouzi Frontiers In Education 2024 [paper]
Common Errors in Machine Learning Projects: A Second Look Renato Zimmermann, Sonya Allin, Lisa Zhang Koli Calling 2023 [paper]
Just-In-Time Prerequisite Review for a Machine Learning Course Lisa Zhang, Sonya Allin The Western Canadian Conference on Computing Education 2023 [video]

Publications in CS Education

Show Me the Mastery Learning! Obstacles to Adoption and Opportunities for New Solutions Claudio Álvarez Gómez, Nickolas Falkner, Päivi Kinnunen, Jaromir Savelka, Lisa Zhang ITiCSE 2025 ⭐ To appear
Early Computer Science Students' Perspectives Towards The Importance Of Writing Rutwa Engineer, Naaz Sibia, Michael Kaler, Bogdan Simion, Lisa Zhang ITiCSE 2024 [paper]
Decomposed Prompting to Answer Questions on a Course Discussion Board Brandon Jaipersaud, Paul Zhang, Jimmy Ba, Andrew Petersen, Lisa Zhang, Michael R. Zhang International Conference on Artificial Intelligence in Education 2023 [paper]
"I Am Not Enough": Impostor Phenomenon Experiences of University Students Angela Zavaleta Bernuy, Anna Ly, Brian Harrington, Michael Liut, Sadia Sharmin, Lisa Zhang, Andrew Petersen Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education [paper]
Embedding and Scaling Writing Instruction Across First- and Second-Year Computer Science Courses Lisa Zhang, Bogdan Simion, Michael Kaler, Amna Liaqat, Daniel Dick, Andi Bergen, Michael Miljanovic, Andrew Petersen Proceedings of the 54th ACM Technical Symposium on Computer Science Education (2023) [paper] 🏆 Best Paper - Experience Reports and Tools Track
Exploring Common Writing Issues in Upper-Year Computer Science Rehmat Munir, Francesco Strafforello, Niveditha Kani, Michael Kaler, Bogdan Simion, Lisa Zhang Proceedings of the 53rd ACM Technical Symposium on Computer Science Education (2022) [paper]
Additional Evidence for the Prevalence of the Impostor Phenomenon in Computing Angela Zavaleta Bernuy, Anna Ly, Brian Harrington, Michael Liut, Andrew Petersen, Sadia Sharmin, Lisa Zhang Proceedings of the 53rd ACM Technical Symposium on Computer Science Education (2022) [paper]
Experience Report: Mini Guest Lectures in a CS1 Course via Video Conferencing Lisa Zhang, Michelle Craig, Mark Kazakevich, Joseph Jay Williams CompEd 2019 [paper]

Model AI Assignments

Model AI Assignment: Differential Privacy with MedMNIST Lisa Zhang, Sonya Allin, Mahdi Haghifam, Michael Pawliuk, Rutwa Engineer, Florian Shkurti EAAI 2025 [repository]
Model AI Assignment: Model Building and Risk Analysis with Health Survey Data Sonya Allin, Lisa Zhang, Mustafa Haiderbhai, Carolyn Quinlan, Rutwa Engineer, Michael Pawliuk EAAI 2025 [repository]
AI Education Matters: Text Denoising Autoencoder for News Headlines Lisa Zhang, Pouria Fewzee, Charbel Feghali AI Matters, Volume 7, Issue 1. September 2021 [paper]
Model AI Assignment: Text Denoising Autoencoder for News Headlines Lisa Zhang, Pouria Fewzee EAAI 2021 [repository][article]
Model AI Assignment: Gesture Recognition using Convolutional Neural Networks Lisa Zhang, Bibin Sebastian EAAI 2020 [repository] [article]
AI Education Matters: Building a Fake News Detector Michael Guerzhoy, Lisa Zhang, Georgy Noarov AI Matters, Volume 5, Issue 3. September 2019 [paper]
Model AI Assignment: Building a Fake News Detector Michael Guerzhoy, Lisa Zhang EAAI 2019 [repository] [ article]

Posters/Workshops in CS Education

Classifying Course Discussion Board Questions using LLMs Paul Zhang, Brandon Jaipersaud, Jimmy Ba, Andrew Petersen, Lisa Zhang, Michael Zhang ITiCSE 2023 Poster [paper]
Student Reactions to Bots on Course Q&A Platform Yu-Chieh Wu, Andrew Petersen, Lisa Zhang ITiCSE 2022 Poster [paper]
Using Deep Learning to Localize Errors in Student Code Submissions Shion Fujimori, Mohamed Harmanani, Owais Siddiqui, Lisa Zhang SIGCSE 2022 Technical Symposium Poster [paper]
CS1 Programming Feedback with Bug Localization. Lucas Roy, Haotian Yang, Lisa Zhang The 6th SPLICE Workshop at L@S (2020) [paper]
Recommending Personalized Review Questions using Collaborative Filtering Zain Kazmi, Wafiqah Raisa, Harsh Jhunjhunwala, Lisa Zhang The 6th SPLICE Workshop at L@S (2020) [paper]
Analyzing CS1 Student Code Using Code Embeddings Robert Bazzocchi, Micah Flemming, Lisa Zhang SIGCSE 2020 Technical Symposium Poster [paper] [poster]

Programing Languages Workshop

Fail Fast and Profile on: Towards a miniKanren Profiler Sloan Chochinov, Daksh Malhotra, Gregory Rosenblatt, Matthew Might, Lisa Zhang. miniKanren Workshop 2022 [paper]
Universal Quantification and Implication in miniKanren. Ende Jin, Gregory Rosenblatt, Matthew Might, Lisa Zhang. miniKanren Workshop 2021 [paper and talk]
Relational Floating-Point Arithmetics. Lucas Sandre, Malaika Zaidi, Lisa Zhang miniKanren Workshop 2021 [paper and talk]
A Relational Interpreter for Synthesizing JavaScript Artem Chirkov, Gregory Rosenblatt, Matthew Might, Lisa Zhang miniKanren Workshop 2020 [paper] [talk]
First-order miniKanren representation: Great for tooling and search Gregory Rosenblatt, Lisa Zhang, William E. Byrd, Matthew Might miniKanren Workshop 2019 [paper]

Machine Learning

Neural Guided Constraint Logic Programming for Program Synthesis Lisa Zhang, Gregory Rosenblatt, Ethan Fetaya, Renjie Liao, William E. Byrd, Matthew Might, Raquel Urtasun, Richard Zemel NeurIPS 2018 [paper] [github] [workshop]
Reviving and Improving Recurrent Back-Propagation Renjie Liao, Yuwen Xiong, Ethan Fetaya, Lisa Zhang, KiJung Yoon, Xaq Pitkow, Raquel Urtasun, Richard Zemel ICML 2018 [arxiv]
Inference in probabilistic graphical models by Graph Neural Networks KiJung Yoon, Renjie Liao, Yuwen Xiong, Lisa Zhang, Ethan Fetaya, Raquel Urtasun, Richard Zemel, Xaq Pitkow ICLR Workshop Track 2018 [paper]
Learning deep structured active contours end-to-end Diego Marcos, Devis Tuia, Benjamin Kellenberger, Lisa Zhang, Min Bai, Renjie Liao, Raquel Urtasun CVPR 2018 [arxiv]

Undergraduate Research/Project Courses

I frequently work with undergraduate computer science students at the University of Toronto Mississauga on research or implementation projects as part of CSC398/492/493 Independent Study Courses.

However, I will be on sabbatical for the 2025-2026 academic year and will not be supervising new independent studies students.

Contact

You can email me at lczhang [at] cs [dot] toronto [dot] edu. If you are emailing me regarding a course, please include the course code in the email subject. Please mention if you are a current or past student.