Gias Uddin

Gias Uddin is an Associate Professor in the Electrical Engineering and Computer Science department at York University's Lassonde School of Engineering. He also holds an Adjunct Professor position at the University of Calgary. Previously, he served as an Assistant Professor at the University of Calgary from 2020 to 2023.

Dr. Uddin's research lies at the intersection of software engineering (SE) and artificial intelligence (AI), with specific focus areas including the assessment of AI trustworthiness using SE (SE4AI) and improving the productivity of software and knowledge professionals using AI-enabled software assistants. His work spans three key domains: Democratized Data Science (HCI → AI4DS, SE4DS), Modernized Software Issue Management (HCI → AI4SE), and Usable Cybersecurity Engineering (HCI → AI4CE). He is particularly interested in how AI can democratize the adoption of machine learning techniques across stakeholders during ML systems development.

His recent publications demonstrate a strong focus on practical applications of AI in software engineering, with particular emphasis on detecting hallucinations in LLMs, improving API documentation, and developing AI-assisted tools for software issue management. His research has resulted in numerous publications at top-tier software engineering conferences including ICSE, ASE, and FSE.

• Distinguished paper award at FSE 2025 for work on hallucination detection in LLMs
• York University Research Award (2025)
• IBM Champion recognition for 2024 and 2025
• CAS Project of the Year Award at IBM TechXChange 2024
• Multiple NSERC-funded research grants

Dr. Uddin has successfully secured multiple research grants including an NSERC Discovery Grant, NSERC Alliance International Catalyst Grant on 'Hallucination Detection in LLMs using Metamorphic Testing,' and several industry-funded projects with IBM. He has supervised numerous graduate students who have gone on to successful careers in both academia and industry, with many receiving prestigious scholarships and awards. As the founding director of the Data Intensive Software Analytics (DISA) Lab, he leads a team focused on developing innovative AI-assisted tools for software developers and data scientists.