معرفی
Dr. Ali Etemad is an Associate Professor and Mitchell Professor in AI for Human Sensing & Understanding at the Department of Electrical and Computer Engineering, Queen's University (Smith Engineering). He holds a PhD and M.A.Sc. from Carleton University and has held visiting faculty roles at the University of Cambridge and Google Research. His research focuses on human-centered AI, affective computing, deep learning, and wearables, with over 190 publications in top venues like NeurIPS, ICLR, and CVPR. His work emphasizes fairness, bias mitigation, and health analytics. Awards include Queen's Excellence in Research and multiple Best Paper Awards. His lab is funded by NSERC, CFI, and industry partners.
Research interests span AI-driven human understanding, including emotion recognition, cognitive load analysis, and medical signal processing. Recent work addresses challenges in multimodal learning, domain generalization, and representation learning under distribution shifts. He leads the Aiim lab, advancing interactive machines and healthcare technologies.
Publications reflect contributions to vision-language models, medical AI, and self-supervised learning. Professional service includes editorial roles at IEEE Transactions and organizing key conferences like AAAI and FG. His invited talks highlight industry-academia collaboration in AI ethics and healthcare applications.
Grants and collaborations fund projects on wearable health monitoring and AI fairness. He advises students on topics like ECG synthesis and continual learning, fostering a pipeline of research impacting both academia and industry.
