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About me

I am an Assistant Professor of computer science at Arizona State University. My research interests are in the area of cryptography and security, with a specific focus on secure computation and its applications such as private set intersection, private database queries, and privacy-preserving machine learning.

Before joining ASU, I was a postdoc at UC Berkeley under the mentorship of Prof. Dawn Song. I received my PhD and Master's degrees from Oregon State University under the supervision of Prof. Mike Rosulek (big shout-out to Mike, who brought me to the field of crypto!). During my graduate studies, I spent several summers as a research intern at Bell Labs, Visa Research, and Google. I got a B.S. degree from St.Petersburg State Polytechnic University.

Teaching & Advising

I will be teaching CSE 598 (Special Topics: Secure Computation for Machine Learning) in Spring 2021. In this course, we will focus mainly on some new & exciting techniques in secure multi-party computation with a specific focus on operations used in popular machine learning algorithms.

I am currently mentoring:
I am looking for motivated students of all levels, postdocs, and visitors to join my group! If you are interested, please click here for more information. Due to COVID-19, I am happy to work remotely with prospective students and researchers.


Articles in refereed conferences
12. Catalic: Delegated PSI Cardinality with Applications to Contact Tracing
11. Practical Privacy-Preserving K-means Clustering
10. PSI from PaXoS: Fast, Malicious Private Set Intersection
9. Scalable Private Set Union from Symmetric-Key Techniques
8. SpOT-Light: Lightweight Private Set Intersection from Sparse OT Extension
7. Attacks Only Get Better: How to Break FF3 on Large Domains
6. The Curse of Small Domains: New Attacks on Format-Preserving Encryption
5. Private Contact Discovery at Scale
4. SWiM: Secure Wildcard Pattern Matching From OT Extension
3. Practical Multi-party Private Set Intersection from Symmetric-Key Techniques
2. DUPLO: Unifying Cut-and-Choose for Garbled Circuits
1. Efficient Batched Oblivious PRF with Applications to Private Set Intersection

Journal articles
2*. BeeTrace: A Unified Platform for Secure Contact Tracing that Breaks Data Silos;
1*. Epione: Lightweight Contact Tracing with Strong Privacy

Other writtings
4. Private Join and Compute from PIR with Default; submitted to Oakland 2021
3. MPC for Edge Computing: (TBA); submitted to USENIX 2020
2. Towards Business Cryptography (TBA); to be resubmitted
1. Private Set Intersection (TBA); submitted to Asiacrypt 2020


Summer 2019
Research Intern
Appril, May 2019
  • Badger Labs - NSW, Australia (Online)
Summer 2018
Research Intern
  • Visa Research - Palo Alto, CA
  • Mentor: Dr. Payman Mohassel
    • Verifiable Computation, and Privacy-Preserving Machine Learning
Summer 2016, 2017
Research Intern
  • Bell Labs, Nokia - Murray Hill, NJ
  • Mentor: Dr. Vladimir Kolesnikov
    • Garbled Circuits, and Private Set Intersection (Summer 2016)
    • Private Database (Summer 2017)
2014 - 2015
Research Assistant
  • Singapore University of Technology and Design (SUTD)
    • Machine Learning, Financial Market Prediction, Life Chain Event Extraction


Professional Services
  • Program committee: WWW 2021, CCS-CCSW 2020, Indocrypt 2020, ProvSec 2020, CSCML 2020
  • Reviewer/external reviewer: CRYPTO 2020, CCS 2020, Asiacrypt 2020, IJIS 2020, JCEN 2019, NeurIPs 2019, CCS 2019, PPML 2018 (NeurIPs workshop), IEEE Access, TCC 2018, Asiacrypt 2018, SCN 2018, PKC 2018, Eurocrypt 2017, Asiacrypt 2017, CCS 2016
  • Conference talk: PETS 2020, Asiacrypt 2019, CRYPTO 2019, CCS 2017, CCS 2016
US Patents
  • Two-Server Privacy-Preserving Clustering; at Visa Research with Payman Mohassel; Filed: November 06th 2019.
  • Applications to Private Set Intersection; at Google with Karn Seth, Tancrède Lepoint, Sarvar Patel, Mariana Raykova; Submitted: April 20th, 2020.
Resume |LinkedIn | GitHub | DBLP| Google Scholar