Research

I am interested in the area of representation learning. More recently, I have developed an interest in diffusion models.

Please refer to my Google Scholar profile for details on the publications I have been a part of.

Tutorials

• Practical Adversarial Robustness in Deep Learning: Problems and Solutions (CVPR’21)
• Foundational Robustness of Foundation Models (NeurIPS’22)
• All Things ViTs: Understanding and Interpreting Attention in Vision (CVPR’23)

Invited talks, demos, etc.

• Controlling Text-to-Image Diffusion Models, BigMAC ICCV Workshop (October 02, 2023). Slides are here. Recording is here.
• Demo of 🧨 diffusers at ICCV 2023 (Tweet).

Teaching assistance

Served as a TA for Full Stack Deep Learning’s 2022 cohort.

Reviewing

ML Safety Workshop (NeurIPS’22), AAAI’23, UDL workshop (ICML’21), ICASSP’21 (sub-reviewer), Artificial Intelligence (Elsevier), IEEE Access.

Misc

• Released a dataset for large-scale multi-label text classification (joint work with Soumik Rakshit).
• Exploration on instruction-tuning Stable Diffusion.