Experience Academic Training McGill University, Mila-Quebec AI Insititute, Montreal, Canada Doctor of Philosophy (Ph.D.) in Computer Science • January 2023 to May 2027 (Expected) - Direct Entry into the Ph.D. program in Computer Science. MBZUAI - Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, UAE Visting Scholar • October 2025 to January 2026 Faculty Host: Prof. Steve Liu, Associate Vice President of Research and Professor of Computer Science and Machine Learning. Mila-Quebec AI Insititute, Montreal, Canada Mentor of Master Students • May 2024 to December 2024; May 2025 to December 2025; May 2026 to December 2026 - Supervised Master of Science students for their internships projects at Deep River, Bell Canada, Watchout, and Bauer. - Provided guidance for entity-linking, fine-tuning, knowledge distillation, and RAG for LLMs. - Offered supervision for document extraction, named entity extraction, and coreference resolution. - Provided supervision for agentic systems and evaluation. McGill University, Montreal, Canada Bachelor of Science (B.Sc.) in Honours Computer Science • September 2019 to December 2022 - Studied in the program of Honours Computer Science. - Graduated as First Class Honours. - Dean's Honour List - SC. Industrial Experience RBC Borealis, Toronto, Canada Machine Learning Researcher • Incoming - I've accepted my returning offer from RBC Borealis and will be joining them again as a Full-Time Machine Learning Researcher. Amazon.com Services LLC, New York, USA Applied Scientist Intern • July 2026 to October 2026 - Researched about advanced visual reasoning with VLMs / MLLMs, continual learning, and knowledge distillation to build models that reason about pairs of products and the relationships between them. - Trained multimodal agentic systems to make decisions over the product graph and invest in efficient LLM inference systems that achieve order-of-magnitude cost reduction while processing millions of daily submissions at billions-of-products scale. - Formulated the adaptive orchestration policy in multi-agent system as an optimization problem and addressed it with a probabilistic level of efforts estimator and constraints-aware selection rules. RBC Borealis, Toronto, Canada Machine Learning Researcher Intern • May 2025 to October 2025 - Proposed and worked for the embedding base context aware reranker project. By integrating rerankers, RAG systems can strike a better balance between speed and precision, leading to more reliable and efficient outputs in various applications. - Proposed a novel agentic workflow for query-focused table summarization in a fast, accurate, and privacy-compliant manner. - This work is part of the RBC Borealis ML Research program. Advisor: Dr. Mohammad Amin Shabani, Dr. Siqi Liu, and Dr. Jiawei (Eric) He. Alexandria Team, Microsoft Research, London, UK MSR x Mila Student Researcher • March 2023 to May 2025 - Proposed a multi-stage architecture for extracting structured kowledge from plain texts with LLMs. - Proposed a new metric tailored for structured entity extraction. - Proposed a diffusion-based model for entity linking purpose. - This collaboration is supported by MSR-Mila Research Grant. Advisor: Dr. Bhaskar Mitra. Collaborators: Dr. James Hensman, Liana Mikaelyan, Pavel Myshkov, Dr. Alexander Meulemans (during his internship), Dr. Jan Tönshoff (during his internship), Dr. Taketomo Isazawa, and Dr. Tom Minka. Samsung Research America, Mountain View, USA Reseasrch Assistant • January 2025 to May 2025 - Academic research collaboration between McGill and Samsung Research for leveraging LLMs in communications scenarios. - This collaboration is supported by Samsung Global Research Outreach program. Collaborators: Dr. Hao Chen, Dr. Yan Xin, and Dr. Jianzhong (Charlie) Zhang. Noah's Ark Lab Canada , Montreal, Canada Associate Researcher Intern • April 2023 to March 2025 - Adapted the soft prompting to distribution shifts and empowered one model for multiple scenarios. - Explored model compression ideas like LoRA-pruning and Mixture of Depth model to save calculations. - Took strategy insights into cutting-edge LLM methods and techniques from leading unicorn startups. Advisor: Xi (Alex) Chen.