I’m on the job market! Please reach out, if you have any research opportunity you think I’d be a good fit for.

I am currently a 4th year Ph.D at CS Department in University of Maryland, College Park. I previously spent 2 years as a Master’s student here. I am advised by Prof. Tom Goldstein and Prof. David Jacobs.

My research interests center on multimodal learning, robustness, and responsible AI. Recently, I have focused on developing improved text+image datasets and addressing safety and privacy risks associated with generative models, particularly in text-to-image generation.

News

• Started a part-time internship at Google, working on multimodal learning for climate change!
• From Pixels to Prose: A Large Dataset of Dense Image Captions is up on arXiv and HuggingFace!
• PUP 3D-GS: Principled Uncertainty Pruning for 3D Gaussian Splatting is up on arXiv!
• What Can We Learn from Unlearnable Datasets? was accepted at NeurIPS 2023!
• Understanding and Mitigating Copying in Diffusion Models was accepted at NeurIPS 2023!
• Diffusion Art or Digital Forgery? Investigating Data Replication in Diffusion Models was accepted at CVPR 2023!
• Started a part-time internship at Cruise! Excited to work on self-driving cars :D
• Learning with noisy labels using low-dimensional model trajectory was accepted at NeurIPS 2022 DistShift Workshop!
• Autoregressive Perturbations for Data Poisoning was accepted at NeurIPS 2022! I’m really excited for my first in-person conference :)
• I finished my internship, and I’m back at UMD!
• I’ll be interning at Mitsubishi Electric Research Laboratories (MERL) hosted by Ye Wang focusing on robust machine learning.
• Poisons that are learned faster are more effective was accepted to CVPR 2022 The Art of Robustness Workshop!