Scholar
Trenton Chang
Google Scholar ID: q0nk27MAAAAJ
University of Michigan
Citations & Impact
Citations
2,107
H-index
6
i10-index
4
Publications
17
Co-authors
0
Publications
Resume (English only)
Academic Achievements
- Published papers in top conferences such as ICML 2024, NeurIPS 2024, etc. Involved in various research projects, including evaluation framework development and application of causal inference methods. Some research results have been open-sourced.
Research Experience
- Interned at Microsoft Research Redmond's Augmented Reasoning & Learning Group during Summer 2024, mentored by Adith Swaminathan and Tobias Schnabel. Research projects include aligning ML models with fairness criteria, measuring LLM steerability, and ensuring ML model resistance to abuse post-deployment.
Education
- PhD: Computer Science, University of Michigan, advised by Jenna Wiens; MS: Computer Science, Stanford (2021); BA: American Studies (2020). Previously worked with HazyResearch and the Stanford NLP Group, and contributed to Google BIG-bench.
Background
- PhD Candidate in Computer Science at the University of Michigan AI lab, focusing on aligning ML with domain-specific values throughout the entire ML lifecycle, from training to post-deployment. His work is inspired by healthcare and policy.
Miscellany
- In his free time, he performs as a jazz pianist and has written about jazz and generative AI.
Co-authors