World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
73
Citations
19787
World Ranking
1602
National Ranking
833

Research.com Recognitions

  • 2018 - ACM Fellow For advancing computational complexity and cryptography, and for promoting public support for theoretical computer science
  • 2007 - Fellow of John Simon Guggenheim Memorial Foundation
  • 2002 - Fellow of Alfred P. Sloan Foundation

Overview

Salil P. Vadhan is a researcher affiliated with Harvard University in the United States. Their work is primarily situated within the field of Computer Science, with notable contributions across multiple subfields including Artificial Intelligence, Computational Theory and Mathematics, Statistics and Probability, Computer Networks and Communications, and Sociology and Political Science.

Their research topics encompass a range of areas with a strong focus on data privacy and security. Key themes in their work include Privacy-Preserving Technologies in Data, Cryptography and Data Security, Complexity and Algorithms in Graphs, Markov Chains and Monte Carlo Methods, Coding Theory and Cryptography, Adversarial Robustness in Machine Learning, and Advanced Causal Inference Techniques.

Salil P. Vadhan has published extensively, with some of the recent papers including:

  • Differentially Private Simple Linear Regression (2022) in Proceedings on Privacy Enhancing Technologies
  • Widespread Underestimation of Sensitivity in Differentially Private Libraries and How to Fix It (2022) in Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security
  • PCPs and the Hardness of Generating Synthetic Data (2020) in Journal of Cryptology
  • Harnessing the Known Unknowns: Differential Privacy and the 2020 Census (2022) in Harvard Data Science Review
  • A standardised differential privacy framework for epidemiological modeling with mobile phone data (2023) in PLOS Digital Health

Frequent co-authors in their research include Omer Reingold, Edward Pyne, Wanrong Zhang, Jack Murtagh, and Jayshree Sarathy. These collaborations reflect ongoing involvement in research communities focused on privacy, cryptography, and algorithms.

The venues in which they have frequently published reveal the breadth and focus of their scholarship. These include arXiv (Cornell University), Leibniz-Zentrum für Informatik (Schloss Dagstuhl), Proceedings on Privacy Enhancing Technologies, Theory of Computing, and Oberwolfach Reports.

Salil P. Vadhan has been recognized with several awards during their career, including being named an ACM Fellow in 2018 for advancing computational complexity and cryptography and for promoting public support for theoretical computer science. Earlier recognitions include fellowships from the John Simon Guggenheim Memorial Foundation in 2007 and the Alfred P. Sloan Foundation in 2002.

Best Publications

  • On the (im)possibility of obfuscating programs

    Boaz Barak;Oded Goldreich;Russell Impagliazzo;Steven Rudich

  • Boosting and Differential Privacy

    Cynthia Dwork;Guy N. Rothblum;Salil Vadhan

  • Verifiable random functions

    S. Micali;M. Rabin;S. Vadhan

  • Robust PCPs of Proximity, Shorter PCPs, and Applications to Coding

    Eli Ben-Sasson;Oded Goldreich;Prahladh Harsha;Madhu Sudan

  • Pseudorandom generators without the XOR lemma

    M. Sudan;L. Trevisan;S. Vadhan

  • Entropy Waves, the Zig-Zag Graph Product, and New Constant-Degree Expanders and Extractors

    Omer Reingold;Salil P. Vadhan;Avi Wigderson

  • Unbalanced expanders and randomness extractors from Parvaresh--Vardy codes

    Venkatesan Guruswami;Christopher Umans;Salil Vadhan

  • Proofs of Retrievability via Hardness Amplification

    Yevgeniy Dodis;Salil Vadhan;Daniel Wichs

  • Improved Delegation of Computation using Fully Homomorphic Encryption.

    Kai-Min Chung;Yael Tauman Kalai;Salil P. Vadhan

  • On the complexity of differentially private data release: efficient algorithms and hardness results

    Cynthia Dwork;Moni Naor;Omer Reingold;Guy N. Rothblum

  • Entropy waves, the zig-zag graph product, and new constant-degree expanders

    Omer Reingold;Salil Vadhan;Avi Wigderson

  • Notions of Reducibility between Cryptographic Primitives

    Omer Reingold;Luca Trevisan;Salil P. Vadhan

  • The Complexity of Counting in Sparse, Regular, and Planar Graphs

    Salil P. Vadhan

  • Computational Differential Privacy

    Ilya Mironov;Omkant Pandey;Omer Reingold;Salil Vadhan

  • The Complexity of Differential Privacy

    Salil P. Vadhan

  • The Limits of Two-Party Differential Privacy.

    Andrew McGregor;Ilya Mironov;Toniann Pitassi;Omer Reingold

  • Extracting all the randomness and reducing the error in Trevisan's extractors

    Ran Raz;Omer Reingold;Salil Vadhan

  • Randomness conductors and constant-degree lossless expanders

    Michael Capalbo;Omer Reingold;Salil Vadhan;Avi Wigderson

  • Extracting randomness from samplable distributions

    L. Trevisan;S. Vadhan

  • The power of a pebble: exploring and mapping directed graphs

    Michael A. Bender;Antonio Fernández;Dana Ron;Amit Sahai

  • Proceedings of the 43rd annual ACM symposium on Theory of computing

    Lance Fortnow;Salil Vadhan

  • Pseudorandom Generators without the XOR Lemma (Abstract).

    Madhu Sudan;Luca Trevisan;Salil P. Vadhan

Frequent Co-Authors

Omer Reingold
Omer Reingold Stanford University
Oded Goldreich
Oded Goldreich Weizmann Institute of Science
Luca Trevisan
Luca Trevisan Bocconi University
Amit Sahai
Amit Sahai University of California, Los Angeles
Boaz Barak
Boaz Barak Harvard University
Jonathan Ullman
Jonathan Ullman Northeastern University
Avi Wigderson
Avi Wigderson Institute for Advanced Study
David Zuckerman
David Zuckerman The University of Texas at Austin
Madhu Sudan
Madhu Sudan Harvard University
Kobbi Nissim
Kobbi Nissim Georgetown University

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Pursuing a Computer Science degree in the USA opens up diverse opportunities, especially with the rise of affordable and flexible online education. Many related online degrees help students tailor their expertise and boost employability in specialized fields.

For those interested in digital safety, an online cybersecurity degree provides a strong foundation in protecting data and systems against cyber threats. Students interested in the intersection of technology and the built environment may consider an online construction management degree, which blends project management with technical skills.

Another popular choice is the cheapest criminal justice degree online. This pathway is ideal for those looking to combine technology skills with public service roles such as cybersecurity within law enforcement. Similarly, students focused on business and technology may benefit from an online accountant degree, preparing them for data-driven decision-making in finance.

Exploring these related degrees can expand your knowledge and career options beyond traditional computer science roles.

Best Scientists Citing Salil P. Vadhan

Trending Scientists

Recently Published Articles