Emrul Hasan
I am an Applied Scientist Intern at Amazon, and a PhD candidate in Computer Science, specializing in Personalization and Recommendation Systems, NLP, and Responsible AI. My research focuses on aspect-aware multi-criteria recommendation systems, where I leverage NLP and deep learning techniques to improve both performance and explainability. I have published several papers in top-tier conferences and journals, including ACM Computing Surveys (ranked #1 out of 143 CS journals, with an impact factor of 23.8). Prior to joining Amazon, I worked as a Machine Learning Technical Specialist at the Vector Institute in Toronto, where I contributed to the development of Retrieval-Augmented Generation (RAG) agents for several of Vector’s partner companies. Before that, I also served as an Applied Machine Learning Intern at the same institute and contributed to the news media bias detection as part of broader efforts toward Responsible AI. In that role, I applied LLMs and multimodal LLMs to annotate news articles and developed a novel dataset. Additionally, I fine-tuned multimodal LLMs (e.g., PaliGemma, Phi-2 Vision) to build benchmark models. I hold several prestigious awards including the Ontario Graduate Scholarship (OGS), Ryerson Graduate Fellowship (RGF), International Graduate students Entrance Scholarship (IGSES), and achieved top rankings in AI competitions, including RecTour Challenge 2024. Before TMU, I earned an MS in Physics and Astronomy from the University of Manitoba. I am very passionate about AI and Innovations. I like traveling, fishing and gardening in his spare time.
