Srinivas Devadas

Srinivas Devadas

Massachusetts Institute of Technology

H-index: 107

North America-United States

About Srinivas Devadas

Srinivas Devadas, With an exceptional h-index of 107 and a recent h-index of 56 (since 2020), a distinguished researcher at Massachusetts Institute of Technology, specializes in the field of Applied cryptography, Computer security, Computer architecture, Computer-Aided Design.

His recent articles reflect a diverse array of research interests and contributions to the field:

Citadel: Side-Channel-Resistant Enclaves with Secure Shared Memory on a Speculative Out-of-Order Processor

A theory to instruct differentially-private learning via clipping bias reduction

Remote direct memory introspection

PAC Privacy: Automatic Privacy Measurement and Control of Data Processing

Geometry of Sensitivity: Twice Sampling and Hybrid Clipping in Differential Privacy with Optimal Gaussian Noise and Application to Deep Learning

Trellis: Robust and Scalable Metadata-private Anonymous Broadcast

Robust Near-Optimal Arm Identification With Strongly-Adaptive Adversaries

An Architecture to Accelerate Computation on Encrypted Data

Srinivas Devadas Information

University

Position

Edwin Sibley Webster Professor of Electrical Engineering and Computer Science

Citations(all)

46926

Citations(since 2020)

16285

Cited By

36644

hIndex(all)

107

hIndex(since 2020)

56

i10Index(all)

324

i10Index(since 2020)

147

Email

University Profile Page

Massachusetts Institute of Technology

Google Scholar

View Google Scholar Profile

Srinivas Devadas Skills & Research Interests

Applied cryptography

Computer security

Computer architecture

Computer-Aided Design

Top articles of Srinivas Devadas

Title

Journal

Author(s)

Publication Date

Citadel: Side-Channel-Resistant Enclaves with Secure Shared Memory on a Speculative Out-of-Order Processor

arXiv preprint arXiv:2306.14882

Jules Drean

Miguel Gomez-Garcia

Thomas Bourgeat

Srinivas Devadas

2023/6/26

A theory to instruct differentially-private learning via clipping bias reduction

Hanshen Xiao

Zihang Xiang

Di Wang

Srinivas Devadas

2023/5/21

Remote direct memory introspection

Hongyi Liu

Jiarong Xing

Yibo Huang

Danyang Zhuo

Srinivas Devadas

...

2023/8

PAC Privacy: Automatic Privacy Measurement and Control of Data Processing

Hanshen Xiao

Srinivas Devadas

2023

Geometry of Sensitivity: Twice Sampling and Hybrid Clipping in Differential Privacy with Optimal Gaussian Noise and Application to Deep Learning

Hanshen Xiao

Jun Wan

Srinivas Devadas

2023/11/15

Trellis: Robust and Scalable Metadata-private Anonymous Broadcast

The Network and Distributed System Security Symposium (NDSS)

Simon Langowski

Sacha Servan-Schreiber

Srinivas Devadas

2023

Robust Near-Optimal Arm Identification With Strongly-Adaptive Adversaries

IEEE Transactions on Signal Processing

Mayuri Sridhar

Srinivas Devadas

2023/11/7

An Architecture to Accelerate Computation on Encrypted Data

IEEE Micro

Axel Feldmann

Nikola Samardzic

Aleksandar Krastev

Srinivas Devadas

Ron Dreslinski

...

2022/4/28

Designing Hardware for Cryptography and Cryptography for Hardware

Srinivas Devadas

Simon Langowski

Nikola Samardzic

Sacha Servan-Schreiber

Daniel Sanchez

2022/11/7

ShorTor: Improving Tor Network Latency via Multi-hop Overlay Routing

Kyle Hogan

Sacha Servan-Schreiber

Zachary Newman

Ben Weintraub

Cristina Nita-Rotaru

...

2022/5/22

Differentially Private Deep Learning with ModelMix

arXiv preprint arXiv:2210.03843

Hanshen Xiao

Jun Wan

Srinivas Devadas

2022/10/7

Shanrang: Fully asynchronous proactive secret sharing with dynamic committees

Cryptology ePrint Archive

Yunzhou Yan

Yu Xia

Srinivas Devadas

2022

Guest Editors’ Introduction: Special Issue on 2021 Top Picks in Hardware and Embedded Security

IEEE Design & Test

Srini Devadas

Jeyavijayan Rajendran

2022/6/22

Spectrum: High-bandwidth anonymous broadcast

Zachary Newman

Sacha Servan-Schreiber

Srinivas Devadas

2022

CraterLake: a hardware accelerator for efficient unbounded computation on encrypted data.

Nikola Samardzic

Axel Feldmann

Aleksandar Krastev

Nathan Manohar

Nicholas Genise

...

2022/6/18

Private Approximate Nearest Neighbor Search with Sublinear Communication

Proceedings of the IEEE Symposium on Security and Privacy

Sacha Servan-Schreiber

Smion Langowski

Srinivas Devadas

2022

Litmus: Towards a Practical Database Management System with Verifiable ACID Properties and Transaction Correctness

Yu Xia

Xiangyao Yu

Matthew Butrovich

Andrew Pavlo

Srinivas Devadas

2022/6/11

F1: A fast and programmable accelerator for fully homomorphic encryption

Nikola Samardzic

Axel Feldmann

Aleksandar Krastev

Srinivas Devadas

Ronald Dreslinski

...

2021/10/18

The Art of Labeling: Task Augmentation for Private (Collaborative) Learning on Transformed Data

Hanshen Xiao

Srinivas Devadas

2021/5/7

Robomorphic computing: a design methodology for domain-specific accelerators parameterized by robot morphology

Sabrina M Neuman

Brian Plancher

Thomas Bourgeat

Thierry Tambe

Srinivas Devadas

...

2021/4/19

See List of Professors in Srinivas Devadas University(Massachusetts Institute of Technology)

Co-Authors

H-index: 101
Kurt Keutzer

Kurt Keutzer

University of California, Berkeley

H-index: 74
Sharad Malik

Sharad Malik

Princeton University

H-index: 69
Farinaz Koushanfar

Farinaz Koushanfar

University of California, San Diego

H-index: 50
Larry Rudolph

Larry Rudolph

Massachusetts Institute of Technology

H-index: 43
Edward Suh

Edward Suh

Cornell University

H-index: 36
Christopher W. Fletcher

Christopher W. Fletcher

University of Illinois at Urbana-Champaign

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