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Resume (English only)
Academic Achievements
- Published papers including 'OptiMUS-0.3: Using Large Language Models to Model and Solve Optimization Problems at Scale' (Major Revision at Management Science), 'Fair Minimum Representation Clustering' (Reject & Resubmit at Operations Research), and 'LLMs for Cold-Start Cutting Plane Separator Configuration' (Under review at INFORMS Journal on Computing). Involved in multiple research projects, such as using LLMs to configure cutting plane separators for MILP problems.
Research Experience
- Worked remotely with the Applied AI group at IBM Research on interpretable clustering during the summer of 2021; Spent the summer of 2023 at Microsoft Research with the Human Understanding and Empathy Group and the Office of Applied Research, focusing on LLMs for Constraint Programming.
Education
- PhD: Cornell University, Operations Research and Information Engineering, advised by Oktay Gunluk; Undergraduate: University of Toronto, Industrial Engineering.
Background
- I am currently a Human-Centered AI postdoctoral fellow at Stanford, with research interests in machine learning, computational optimization, and human-computer interaction. Before joining Cornell for my PhD, I completed my undergraduate studies in industrial engineering at the University of Toronto and spent a year working at the Royal Bank of Canada, developing deep reinforcement learning-based trade execution algorithms.
Miscellany
- Passionate about training the next generation of data scientists through programs like iXperience, teaching introductory practical data science tools in Python and R to students worldwide. Outside of work, I enjoy hiking and have visited 27 national parks so far.
Co-authors: 0 (list not available)