Xiaotian Liu
PhD Candidate, Dartmouth CS
Hi, I’m Xiaotian Liu, a third-year Ph.D. candidate at Dartmouth College, advised by Dr. Yaoqing Yang. My research interests include scientific machine learning, generative models, reinforcement learning for algorithm discovery, and optimization theory.
Before coming to Dartmouth, I received both my B.S. in Mathematics and Computer Science and my M.S. in Computer Science from Wake Forest University (Go Deacs!) where I was advised by Dr. Grey Ballard.
From June to September 2026, I am a Research Intern on Adobe’s Firefly team. My research focuses on OPD for few-step text-to-image generation, developing methods to distill multi-step teachers into few-step students.
Outside of research, I enjoy snowboarding and am currently learning how to ski.
news
| Sep 14, 2026 | I am a Research Intern on Adobe’s Firefly team (June–September 2026). My research focuses on OPD for few-step text-to-image generation, developing methods to distill multi-step teachers into few-step students. |
|---|---|
| Apr 30, 2026 | Two papers accepted at ICML 2026! IRNO received a Spotlight distinction. |
| Nov 21, 2025 | Passed my Ph.D. qualification exam! |
| Sep 25, 2024 | Paper accepted at NeurIPS 2024: Sharpness-Diversity Tradeoff: Improving Flat Ensembles with SharpBalance. |
| Jun 12, 2024 | Paper accepted at Kobe Journal of Mathematics: Bounding Crossing Numbers in Hexagonal Mosaics. |
| Sep 15, 2023 | Started my Ph.D. at Dartmouth College, advised by Dr. Yaoqing Yang. |
| May 15, 2023 | Paper accepted at Numerical Linear Algebra with Applications: CP Decomposition for Tensors via Alternating Least Squares with QR Decomposition. |
selected publications
academic service
Reviewer
- Conference: ICLR (2025, 2026), ICML (2026), AISTATS (2025, 2026), ACL (2024)
- Journal: IEEE TNNLS, IEEE TPAMI