Hirad Daneshvar

I am a Postdoctoral Research Fellow at the INRS-UQO UMR research lab, where I study uncertainty quantification with a focus on LLMs and foundation models. I received my Ph.D. in Computer Engineering from Toronto Metropolitan University (2025), where my research focused on advancing trustworthy applications of Deep Learning in healthcare, during which I worked closely with researchers from McMaster University and clinicians/experts from both Hamilton Health Sciences (HHS) and the University of British Columbia (UBC). My doctoral work emphasized mental health outcome prediction, model calibration, and uncertainty quantification. I previously completed my M.Sc. in Computer Engineering in 2020, conducting research on recommender systems with a focus on Deep Learning–based approaches. My broader research interests include recommendation systems, machine learning, graph neural networks, uncertainty quantification, and the development of reliable AI methods.

In addition to my academic research, I have experience with several programming languages, including Python, PHP, and JavaScript. I have 5+ years of experience as a Full-Stack/Back-end and Database Developer working with relational and NoSQL databases. This experience taught me to work both individually and in teams. I have also taught programming and software architecture courses at Toronto Metropolitan and Carleton Universities.