Om ThakkarGraduate Student
Department of Computer Science
Email : omthkkr "at" bu.edu
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Security group, and the Theoretical Computer Science group, at the Department of Computer Science, Boston University. My interest areas include differential privacy, private machine learning, and private deep learning. I am very fortunate to be advised by Dr. Adam Smith.
I completed the first 3.5 years of my Ph.D. at the Department of Computer Science and Engineering in
- Summer 2018: I am working with Úlfar Erlingsson, as an intern in Google Brain, Mountain View.
- Paper titled Towards Practical Differentially Private Convex Optimization accepted to appear in S&P 2019.
- Paper titled Differentially Private Matrix Completion Revisited accepted to appear in ICML 2018. To be presented as a long talk at the conference.
- Fall 2017: I worked with Dr. Dawn Song on practical differentially private convex optimization, as a Visiting Student Researcher at UC Berkeley.
- Summer 2017: I worked with Brendan McMahan on using adaptivity for differentially private federated learning without hyperparameter tuning, while interning at Google.
- My most recent resume (last updated in June, 2018) can be found here.
- Model-Agnostic Private Learning via Stability. Abstract▼ Joint work with Raef Bassily, and Abhradeep Thakurta.
- Towards Practical Differentially Private Convex Optimization. Joint work with Roger Iyengar, Joseph P. Near, Dawn Song, Abhradeep Thakurta, and Lun Wang. To appear in the 40th IEEE Symposium on Security and Privacy (S&P 2019).
- Differentially Private Matrix Completion Revisited. Abstract▼ Joint work with Prateek Jain, and Abhradeep Thakurta. In the 35th International Conference on Machine Learning (ICML 2018). Presented as a long talk at the conference.
- Max-Information, Differential Privacy, and Post-Selection Hypothesis Testing. Abstract▼ Joint work with Ryan Rogers, Aaron Roth, and Adam Smith. In the 57th Annual IEEE Symposium on Foundations of Computer Science (FOCS 2016).
- Summer 2018: Research Intern at Google Brain, Mountain View, CA. Mentor: Úlfar Erlingsson.
- Fall 2017: Visiting Student Researcher at University of California, Berkeley, CA. Host: Dr. Dawn Song.
- Summer 2017: Research Intern at Google, Seattle, WA. Mentors: Brendan McMahan, and Martin Pelikan.
- Summer 2016: Research Intern in the CoreOS: Machine Learning team at Apple, Cupertino, CA.
- Towards Practical Differentially Private Convex Optimization, on March 5, 2018 @ the Privacy Tools Project meeting, Harvard.
- Differentially Private Matrix Completion Revisited
- on May 2, 2018 @ the Mathematical Foundations of Data Privacy workshop, BIRS. (Talk video)
- on January 26, 2018 @ the BU Data Science (BUDS) Day, Boston University. (Poster)
- on December 12, 2017 @ the Privacy Tools Data Sharing workshop, Harvard University. (Poster)
- on October 9, 2017 @ the Security Seminar, UC Berkeley.
- A brief introduction to Concentrated Differential Privacy, on April 14, 2017 @ CSE Theory Seminar, Penn State.
- Max-Information, Differential Privacy, and Post-selection Hypothesis Testing
- on April 24, 2017 @ INSR Industry Day, Penn State. (Poster)
- on December 2, 2016 @ SMAC Talks, Penn State.
- on November 7, 2016 @ CSE Theory Seminar, UCSD.
- on October 14, 2016 @ CSE Theory Seminar, Penn State.
- Max-Information and Differential Privacy, on May 5, 2016 @ CSE Theory Seminar, Penn State.
- The Stable Roommates Problem with Random Preferences, on April 10, 2015 @ CSE Theory Seminar, Penn State.
- The Multiplicative Weights Update Method and an Application to Solving Zero-Sum Games Approximately, on November 3, 2014 @ CSE Theory Seminar, Penn State.
- Teaching assistant:
- CMPSC 465 Data Structures and Algorithms, Spring 2017 @ Penn State.
- CMPSC 360 Discrete Mathematics for Computer Science, Spring 2015 @ Penn State.
- IT 114 Object Oriented Programming, Spring 2014 @ DA-IICT.
- IT 105 Introduction to Programming, Fall 2013 @ DA-IICT.
PETS 2019, S&P 2019, CCS 2018, ICML 2018, PETS 2018, STOC 2018, ACSAC 2017, FOCS 2017, PETS 2017, S&P 2017, STOC 2016, WABI 2015.
- Received travel awards for ICML 2018, and FOCS 2014..
- Received a GSO Conference Travel Grant for Summer 2018.
- Report on Node-differentially Private Algorithms for Graph Statistics. It includes joint work with Ramesh Krishnan.