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 also designed and teach the first foundational
Generative AI course for business students,
covering transformers, retrieval-augmented generation (RAG),
fine-tuning (SFT, DPO, RLHF),
activation engineering (e.g., sparse autoencoders and steering vectors),
automated data operations using LLMs, and the
risks and limitations of large language models.
Teaching Awards
- 2023-2024 Trammell/CBA Foundation Teaching Award for Assistant Professors.
- McCombs BBA Faculty Honor Roll for Gen AI in Business and Social Sciences (April 2026).
- McCombs BBA Faculty Honor Roll for Intro to Problem Solving and Programming (April 2025).
- McCombs BBA Faculty Honor Roll for Intro to Problem Solving and Programming (April 2024).
- McCombs BBA Faculty Honor Roll for Intro to Problem Solving and Programming (Dec 2023).
- McCombs BBA Faculty Honor Roll for Intro to Problem Solving and Programming (May 2021).
Research Awards
- CBA Foundation Research Excellence Award for Assistant Professors (2026).
Research Grants