About Me

I am, Chiyu(Henry) Ma, a second-year Ph.D. student in Computer Science at Dartmouth College, advised by Prof. Soroush Vosoughi. My research focuses on trustworthy AI, with an emphasis on the interpretability of computer vision (CV) and natural language processing (NLP) models. I aim to design and develop intrinsically interpretable algorithms that enhance AI transparency and trustworthiness. Prior to Dartmouth, I earned a Master’s in Statistical Science from Duke University, where I was a member of the Interpretable Machine Learning Lab, advised by Prof. Cynthia Rudin. I also collaborated with Prof. Chaofan Chen from UMaine. Before that, I completed a B.S. in Statistics with honors from Carnegie Mellon University, concentrating in Computational Finance, and worked with Prof. Zach Branson on statistical analysis in biological applications.

I am always open to collaboration and enjoy doing research! If you are interested in working on some projects together, feel free to send me an email!

Preprints

Juding the Judges: A Systematic Investigation of Position Bias in Pairwise Comparative Assessments by LLMs

Lin Shi, Chiyu Ma, Wenhua Liang, Weicheng Ma, Soroush Vosoughi

In Submission

Paper / Video / Code

Selected Publications

Interpretable Image Classification with Adaptive Prototype-based Vision Transformers

Chiyu Ma, Jon Donnelly, Wenjun Liu, Soroush Vosoughi, Cynthia Rudin, Chaofan Chen

Neural Information Processing Systems (NeurIPS 2024) , Poster

Paper / Video / Code

Achieving Domain-Independent Certified Robustness via Knowledge Continuity

Alan Sun, Chiyu Ma, Kenneth Ge, Soroush Vosoughi

Neural Information Processing Systems (NeurIPS 2024) , Poster

Paper / Video / Code

This Looks Like Those: Illuminating Prototypical Concepts Using Multiple Visualizations

Chiyu Ma*, Brandon Zhao*, Chaofan Chen, Cynthia Rudin

Neural Information Processing Systems (NeurIPS 2023) , Poster

Paper / Video / Code

Teaching Experiences

• Duke Decision 618/521: Decision Analytics and Modeling TA: Fall 2021
• Duke CS 617: Introduction to Machine Learning TA: Fall 2022
• Dartmouth COSC 070: Foundations of Applied Computer Science TA: Fall 2023

Reviewer Services

• Conference: AAAI-AISI track 2023, ICML 2024, NeurIPS 2024, ICLR 2025
• Workshop: NeurIPS IAI workshop 2024
• Journal: TMLR 2024

Education History

• Ph.D. in Computer Science, Dartmouth College, 2028 (expected)
• M.S. in Statistical Science, Duke University, 2023
• B.S. in Statistics (with Honors), Carnegie Mellon University, 2021