Mohammad-Javad Darvishi-Bayazi

Montreal, Qc, Canada
Javad Bayazi is an Artificial Intelligence (AI) Research Scientist at Hydro-Québec Research Institute (IREQ) where he focuses on developing innovative AI solutions for the renewable energy sector, with particular emphasis on foundation models and time series forecasting. Prior to this role, he was a PhD student at Mila - Quebec Artificial Intelligence Institute (Mila) and the Université de Montréal (UdeM), working under the supervision of Jocelyn Faubert and Irina Rish. Javad’s research focuses on robustness and transfer learning in artificial neural networks, with recent work evaluating and developing foundation models and time series forecasting (Google scholar profile). He has dedicated his academic career to exploring the frontiers of AI, aiming to develop models that are not only accurate but also reliable and adaptable. Javad’s contributions to the field are poised to make significant impacts on both theoretical research and practical applications in AI and cognitive science.
news
Jul 26, 2024 | Presented our paper 'VFA' at ICML 2024 FM-Wild Workshop |
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Jun 07, 2024 | Generative AI with Large Language Models |
Apr 15, 2024 | New Paper: Pathological Detection in EEG with Transfer Learning |
Mar 01, 2024 | Diving Deep into AI: My Experience at AAAI 2024 |
latest posts
Sep 27, 2024 | Time Series Forecasting demo |
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Apr 08, 2024 | Psycho-LLaVA: Psychology of Large Language and Vision Assistant |