Experience Alexandria Team, Microsoft Research, London, UK MSR x Mila Student Researcher • Feb. 2023 to Jun. 2024 Propose a multi-stage architecture for extracting structured kowledge from unstructured texts using LLMs. Propose a unified training paradigm with diffusion model applicable to various information retrieval tasks (i.e., KB Completion, Entity Linking, Information Extraction, KB-augmented Q&A). Advisor: Bhaskar Mitra Descartes Team, Google Research, Mountain View, USA Student Researcher • Aug. 2023 to Feb. 2024 Investigate knowledge localization in LLMs for both dense architectures and sparse architures (i.e., Mixture-of-Experts). Advisor: Cicero Nogueira dos Santos MuDcATs (Making Decisions with Activity-based, Temporal & Sequential Data) Team, Google Research, Mountain View, USA Research Intern • Nov. 2022 to Feb. 2023 Propose density-based user representation (DUR) through Gaussian Process Regression for better personalized multi-interest retrieval. Advisor: Craig Boutilier Dynamic Call Routing Team, Bell Canada, Montreal, Canada Mitacs Accelerate Fellow Researcher • Jul. 2022 to Jun. 2023 Propose a fairness-aware learning-to-rank framework for fair agent-customer matching in call center to balance agent workloads and improve global customer value. FATE (Fairness, Accountability, Transparency, and Ethics) Team., Microsoft Research, Montreal, Canada MSR x Mila Student Researcher • Sep. 2020 to Jun. 2021 Propose a multi-objective optimization framework for fairness-aware recommendation, Multi-FR, that adaptively balances accuracy and fairness for various stakeholders with Pareto ptimality guarantee. Advisor: Fernando Diaz