Welcome!
I received my Ph.D. from the MIT Media Lab in 2020.
Prior to this, I earned dual Master's degrees in Computer Science and Transportation Engineering from MIT.
My research has been supported by National Science Foundation (NSF), National Institutes of Health (NIH), Marketing Science Institute, UT Good Systems, Texas Global, UT Research & Creative Grants, and UT McCombs.
My research focuses on:
- Interpretable Machine/Deep Learning on Networks
- Network Spillovers and Dynamics
- Human-Centric Interpretability in Generative AI
Teaching
At McCombs, I designed and teach the school's first foundational
Generative AI course for business students, covering
transformers, RAG, fine-tuning (SFT, DPO, RLHF),
activation engineering, LLM-powered data operations, and model risks.
Teaching Awards
- Trammell/CBA Foundation Teaching Award for Assistant Professors (2023-2024).
- McCombs BBA Faculty Honor Roll, five-time recipient (2021, 2023-2026).
Research Awards
- CBA Foundation Research Excellence Award for Assistant Professors (2026).
- Best Paper Runner-up at INFORMS Data Science Workshop (2025).
- Best Associate Editor for the ICIS 2024 Track: Data Analytics for Business and Societal Challenges (2025).
- Best Student Paper Award at INFORMS Data Science Workshop (2024).
- Finalist for Meta People’s Expectations & Experiences with Digital Privacy Request for Proposals (2022).
- INFORMS ISS Cluster Best Paper Award (2022).
- Second Prize in INFORMS Revenue Management and Pricing Data-Driven Challenge (2021).
Research Grants