Majeed Kazemitabaar
PhD Candidate
Department of Computer Science
University of Toronto
# Bio
I'm Majeed, a PhD candidate in Computer Science at the University of Toronto, where I've been fortunate to be advised by Prof. Tovi Grossman. My research in Human-Computer Interaction focuses on addressing fundamental challenges surrounding interaction and cognition within the evolving landscape of programming with generative AI.
My work includes (a) studying the implications of AI on over-reliance when learning to code [C.6] and [C.7], (b) designing novel interfaces and interventions that cognitively engage programmers with AI-generated solutions [C.10], (c) developing human-AI interactions that involve users in editing the AI's chain-of-thought reasoning [C.9], and (d) deploying pedagogical AI assistants that promote independent problem-solving [C.8].
Prior to my PhD, I earned a master's degree in Computer Science from the University of Maryland, where I worked with Prof. Jon Froehlich at the Makeability Lab and the HCIL. During that time, I led the two-year design, development, and evaluation of MakerWear—a tangible electronic construction kit that enables young children in creating their own interactive wearables. This work received a Best Paper Award at CHI 2017 [C.2] and a Best Late Breaking Work Award at CHI 2016 [EA.2].
I have been fortunate to collaborate with leading researchers in academia and industry, including two internships at Microsoft Research, where I was hosted by Dr. Jack Williams in 2023 and Dr. Rob DeLine in 2017. Additionally, I was a visiting research scholar at UC Berkeley, hosted by Prof. Bjoern Hartmann in 2017.
To date, I have published 10 full conference research papers in top-tier HCI venues, includingCHI, UIST, IUI, SIGCSE, and IDC. My recent work in human-AI interaction is among the most highly cited within the HCI and Computer Science Education Research community.
# Latest Updates
- JAN '25 Our $300,000 LEAF Impact Grant to develop the next generation of CodeAid [C.8] has been approved!
- DEC 2024 My paper about "cognitive engagement with AI-generated code" is accepted to IUI 2025. [C.10]
- NOV 2024 Our workshop about "AI tools that augment instead of replacing human cognition" is accepted to CHI 2025. [EA.3]
- AUG 2024 Passed PhD thesis proposal exam and advanced to candidacy!
# Upcoming Talks
- JAN 24 2025 Apple Research "Balancing Productivity and Cognitive Engagement in AI-Assisted Programming".
- JAN 30 2025 Univ. Maryland "Learning to Code with AI" at the HCIL BBL Speaker Series.
- FEB 22 2025 ACSE 2025 Conf. "AI in Computing Education" keynote speaker at ACSE 2025.
- MAR 19 2025 Microsoft Research "Cognitive Engagement with AI-generated code" at the HCI Talk Series.
# Full Conference Papers
[C.10] Exploring the Design Space of Cognitive Engagement Techniques with AI-Generated Code for Enhanced Learning
IUI 2025 • ACM Conference on Intelligent User Interfaces
[C.9] Improving Steering and Verification in AI-Assisted Data Analysis with Interactive Task Decomposition
UIST 2024 • ACM Symposium on User Interface Software Technology
[C.8] CodeAid: Evaluating a Classroom Deployment of an LLM-based Programming Assistant that Balances Student and Educator Needs
CHI 2024 • ACM Conference on Human Factors in Computing Systems
[C.7] How Novices Use LLM-Based Code Generators to Solve CS1 Coding Tasks in a Self-Paced Learning Environment
Koli Calling 2023 • ACM Koli Calling Conference on Computing Education Research
[C.6] Studying the effect of AI Code Generators on Supporting Novice Learners in Introductory Programming
CHI 2023 • ACM Conference on Human Factors in Computing Systems
[C.5] Scaffolding Progress: How Structured Editors Shape Novice Errors When Transitioning from Blocks to Text
SIGCSE 2023 • ACM Technical Symposium on Computer Science Education
[C.4] CodeStruct: Design and Evaluation of an Intermediary Programming Environment for Novices to Transition from Scratch to Python
IDC 2022 • ACM Conference on Interaction Design and Children
[C.3] Bifröst: Visualizing and Checking Behavior of Embedded Systems across Hardware and Software
UIST 2017 • ACM Symposium on User Interface Software Technology
[C.2] MakerWear: A Tangible Approach to Interactive Wearable Creation for Children
CHI 2017 • ACM Conference on Human Factors in Computing Systems
Best Paper Award
[C.1] Activities Performed by Programmers while Using Framework Examples as a Guide
SAC 2014 • ACM Symposium of Applied Computing
# Extended Abstracts
[EA.3] Tools for Thought: Research and Design for Understanding, Protecting, and Augmenting Human Cognition with Generative AI
CHI 2025 Workshop • (Accepted) ACM Conference on Human Factors in Computing Systems
[EA.2] ReWear: Early Explorations of a Modular Wearable Construction Kit for Young Children
CHI 2016 Late-Breaking Work • ACM Conference on Human Factors in Computing Systems
Best Late-Breaking Work Award
[EA.1] MakerShoe: Towards a Wearable E-Textile Construction Kit to Support Creativity, Playful Making, and Self-Expression
IDC 2015 Demo • ACM Conference on Interaction Design and Children
# Theses
Balancing Productivity and Cognitive Engagement in AI-Assisted Programming
PhD Thesis • University of Toronto • Advisor: Tovi Grossman
MakerWear: A Tangible Construction Kit for Young Children to Create Interactive Wearables
MSc Thesis • University of Maryland, College Park • Advisor: Jon E. Froehlich
# Advising
Sepehr Hosseini • 2024 • MSc Computer Science • University of Toronto
Lead the design, development, and evaluation of an AI-powered semantic mini-map to enhance navigation in computational notebooks.
Oliver Huang • 2023 - 2024 • BSc Computer Science • University of Toronto
Design and implementation of cognitive engagement techniques with AI-generated code.
Research Papers [C.10]
Chase McDougall • 2023 - 2024 • BSc Engineering Sciences • University of Toronto
EngSci Thesis Supervisor "Personalized Gamification to Increase Student Engagement in Self-Paced Introductory Programming."
Harry Ye • 2023 • BSc Computer Science • University of Toronto
Qualitative analysis of student queries from CodeAid and survey responses.
Research Papers [C.8]
Justin Chow • 2022 • BSc Engineering Sciences • University of Toronto
Conducting user studies to compare learning to code with and without AI code generators.
Research Papers [C.6]
Carl Ka To Ma • 2022 • BSc Engineering Sciences • University of Toronto
Conducting user studies to compare learning to code with and without AI code generators.
Research Papers [C.6]
Viktar Chyhir • 2021 - 2022 • BSc Computer Science • University of Toronto
Design and development of CodeStruct and conducting user studies.
Research Papers [C.4][C.5]
Alex Jiao • 2016 • BSc Electrical Engineering • University of Maryland
Development of MakerWear and conducting user studies.
Research Papers [C.2]
Jason McPeak • 2016 • BSc Computer Engineering • University of Maryland
Design and development of MakerWear and conducting user studies.
Research Papers [C.2]
Katie Wang • 2015 • BSc Computer Science • University of Maryland
Design and development of ReWear and conducting user studies.
Research Papers [EA.2]
Tony Cheng • 2015 • BSc Computer Science • University of Maryland
Design and development of ReWear and conducting user studies.
Research Papers [EA.2]
Chloe Aloimonos • 2015 • High School Student
Design and development of ReWear and conducting user studies.
Research Papers [EA.2]