I am a 3rd-year Ph.D. student at Purdue University, advised by Prof. Somali Chaterji.
My research focuses on adversarially robust and data-efficient learning algorithms for computer vision and multimodal tasks. I have worked on problems spanning image semantic segmentation, video understanding, text-to-image diffusion models, and video coherence metrics, with broader interests in generative modeling and robust multimodal learning.
In the summers of 2023 and 2024, I interned at Adobe Research, collaborating with Mehrab Tanjim. At Adobe, I developed methods for retrieval-augmented diffusion to improve inference efficiency, and designed a learned metric for multi-shot video coherence.
Before joining Purdue, I was a Research Assistant at National Taiwan University (NTU) with Prof. Ta-Te Lin. My work focused on precision agriculture, where I built embedded systems and ML algorithms for interpretable decision support, robust edge deployment, and real-world agricultural monitoring.
News
Mar 2025
Our paper SKALD has been accepted to ICCV 2025!
Feb 2025
Our paper on semi-supervised semantic segmentation accepted to CVPR 2025!
Jul 2024
Our paper ReCon has been accepted to ECCV 2024!
May 2024
Returned to Adobe Research for a second summer internship.