Senior PhD Student
Om is a Ph.D. student in the Security group, and the Theoretical Computer Science group, at the Department of Computer Science, Boston University. His research is in privacy-preserving data analysis, with a specific focus on differential privacy and its applications to machine learning, deep learning, and adaptive data analysis. He is very fortunate to be advised by Dr. Adam Smith.
Om completed the first 3.5 years of my Ph.D. in the Department of Computer Science and Engineering at the Pennsylvania State University, advised was by Dr. Adam Smith. Before joining Penn State, he completed his B.Tech. in Information and Communication Technology in 2014 from the Dhirubhai Ambani Institute, India.
Publications
Towards Practical Differentially Private Convex Optimization.
Joint work with Roger Iyengar, Joseph P. Near, Dawn Song, Abhradeep Thakurta, and Lun Wang.
In the 40th IEEE Symposium on Security and Privacy (S&P 2019).
Model-Agnostic Private Learning.
Joint work with Raef Bassily, and Abhradeep Thakurta.
In the 32nd Conference on Neural Information Processing Systems (NeurIPS 2018). Accepted for an oral presentation.
Differentially Private Matrix Completion Revisited.
Joint work with Prateek Jain, and Abhradeep Thakurta.
In the 35th International Conference on Machine Learning (ICML 2018). Presented as a long talk.
Max-Information, Differential Privacy, and Post-Selection Hypothesis Testing.
Joint work with Ryan Rogers, Aaron Roth, and Adam Smith.
In the 57th Annual IEEE Symposium on Foundations of Computer Science (FOCS 2016).