Research

I am interested in a number of topics pertaining to Deep Learning:

• Self-supervised and semi-supervised representation learning
• Model robustness
• Model optimization

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)
• Upcoming: All Things ViTs: Understanding and Interpreting Attention in Vision (CVPR’23)

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.