Along the way
Experience.
My work spans industry, academia, and national laboratories—from machine learning for scientific discovery to graph learning and personalization.
02 / Along the way
Across research & industry.
Present Snap ResearchResearch Scientist
User modeling and personalization, with a focus on generative and graph-based recommendation systems.
Snap ResearchDoctoral research University of MichiganComputer Science & Engineering
Graph representation learning with Danai Koutra. Supported by an NSF Graduate Research Fellowship and a Rackham Merit Fellowship.
University of MichiganSummer 2025 AmazonResearch internship
Investigating large language models for graph reasoning.
Summer 2024 Snap ResearchResearch internship
Efficient collaborative filtering and popularity bias in recommendation systems.
Snap ResearchSummers 2022 & 2023 MIT Lincoln LaboratoryResearch internships
Combinatorial optimization over networks and applied machine learning for graph-structured data.
MIT Lincoln LaboratoryBefore my Ph.D. Lawrence Livermore National LaboratoryStaff Scientist
Graph learning for molecular modeling, inverse design, and interpretable machine learning for scientific discovery.
Lawrence Livermore National Laboratory