Empowering learners through AI-assisted tools designed for cognitive growth and creative mastery in computer science.

Majeed is a Computer Science Professor at the University of Alberta and a Fellow at Amii. As a tool builder, his research in Human-AI Interaction explores the design of tools and interaction techniques that deliberately protect and augment human cognition rather than replacing it. By focusing on programming as a medium for research on learning, productivity, and creativity, his goal is to develop AI-assisted programming tools that engage programmers in the iterative process of problem-solving and task decomposition while nurturing curiosity, experimentation, and the confidence to take risks and push boundaries. This vision takes different forms for different audiences. For young learners, he aims to empower them to build AI-powered computational artifacts and become creators with AI rather than passive users of it. For emerging and professional developers, he aims to design AI-powered programming tools that balance productivity with deep cognitive engagement. Tools that help experts retain control, make informed trade-offs, and strengthen their software design and architectural expertise as they collaborate with AI.

Majeed earned his Ph.D. from the University of Toronto in 2025 and completed his MSc at the University of Maryland. His doctoral research included one of the first studies exploring the impact of over-reliance on AI with novices learning to code, specifically examining what happens when AI support is later removed and its effect on learning outcomes. This work informed the design of (a) interventions that cognitively engage programmers in AI's problem-solving process and solutions, (b) novel human-AI interactions that make the AI's chain-of-thought reasoning editable to improve control and verification of its process, and (c) pedagogical AI assistants that promote independent problem-solving without revealing code solutions, studied in large-scale and longitudinal deployments.

Majeed frequently publishes at CHI, UIST, and other top HCI conferences. His work is among the most highly cited papers at CHI 2023 and 2024, and he received a Best Paper Award at CHI 2017.