About me
I am currently a 3rd year Ph.D student at CS Department in University of Maryland, College Park. I previously finished my M.S here as well. I am advised by Prof. Tom Goldstein and Prof. David Jacobs.
My research interests span multiple areas. Recently my work has been focused on generative models, security and attribution of machine learning systems.
Previously, I have also worked on visual recognition problems such as object detection and instance segmentation.
News
- 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!
- Shift Invariance Can Reduce Adversarial Robustness was accepted to NeurIPS 2021!
- I finished my internship and started my Ph.D!
- Low Curvature Activations Reduce Overfitting in Adversarial Training was accepted to ICCV 2021!
- Started summer internship at Apple.
- Low Curvature Activations Reduce Overfitting in Adversarial Training (short-version) was accepted to ICLR 2021 Security and Safety in Machine Learning Systems and recieved travel award!