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.
- 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)
Served as a TA for Full Stack Deep Learning’s 2022 cohort.
ML Safety Workshop (NeurIPS’22), AAAI’23, UDL workshop (ICML’21), ICASSP’21 (sub-reviewer), Artificial Intelligence (Elsevier), IEEE Access.
- Released a dataset for large-scale multi-label text classification (joint work with Soumik Rakshit).
- Exploration on instruction-tuning Stable Diffusion.