š¢I am on the job market! I am looking for a full-time position in industry as a Research Scientist/Engineer, or in academia as faculty. Feel free to reach out.
About Me
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.
Our paper What CLIP Knows but Cannot Say: Recovering Negation from Frozen Intermediate Features has been accepted to ECCV 2026 as an oral! See the project page.
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.