Ananth Raghunathan

Meta

Principal Engineer

Product Risk & Compliance, Meta

Google

Senior Research Scientist

Google Brain

Stanford

Doctor of Philosophy

Stanford University

Ananth Raghunathan

Bio

I am a Principal Engineer in Meta's Privacy Org working on technical, research, and regulatory aspects of anonymization that serve Meta's compliance obligations around user data. My work protects several critical large revenue workstreams under the Ads and Whatsapp orgs ensuring their compliance under relevant legislation like GDPR, DMA, and CCPA. I have also incubated several privacy-enhancing technologies at Meta such as scaled de-identified authentication and privacy-preserving password protection. More broadly, my interests lie in the intersection of cryptography, privacy, and ML.

Before Meta, I spent half a decade at Google working on privacy and machine learning research as part of Google Brain. Some of the projects I worked on or helped with include local differential privacy, the the Shuffle Model of privacy and its privacy amplification guarantees, the Chrome Privacy Sandbox proposals, algorithms to privately train ML models, Chrome's Password Check tool, and post-quantum crypto. I was part of the FrodoKEM team that designed and submitted the Frodo Key Encapsulation Mechanism to the NIST competition on post-quantum crypto.

I received my Ph.D. from the Department of Computer Science at Stanford University advised by Prof. Dan Boneh. My thesis focused on modeling and building secure deterministic and searchable encryption schemes. I also worked on building lattice-based cryptographic primitives, among other topics in cryptography.

During my Ph.D., I spent summers with Dirk Balfanz and the security engineering team doing research on the Security Key at Google, and at Microsoft Research (Silicon Valley) working with Gil Segev and Ilya Mironov. Earlier, I graduated from the Computer Science and Engineering Department at IIT Madras with a Bachelors of Technology in Computer Science.

Patents & Publications

Authenticating Anonymous Information, US Patent #12,316,621B1, 2025
Methods for Protecting Privacy, US Patent #2024/0204991A1, 2024
Oblivious Revocable Functions and Encrypted Indexing
With Kevin Lewi, Jon Millican, Arnab Roy
IACR ePrint Archive 2022
Dit: De-identified authenticated telemetry at scale
With Sharon Huang, Subodh Iyengar, Sundar Jeyaraman, Shiv Kushwah, Chen-Kuei Lee, Zutian Luo, Payman Mohassel, Shaahid Shaikh, Yen-Chieh Sung, Albert Zhang
Real World Crypto 2021
Information Leakage in Embedding Models
With Congzheng Song
ACM CCS 2020
Encode, Shuffle, Analyze Privacy Revisited: Formalizations and Empirical Evaluation
With Úlfar Erlingsson, Vitaly Feldman, Ilya Mironov, Shuang Song, Kunal Talwar, and Abhradeep Guha Thakurta
Privacy Preserving Machine Learning Workshop at ACM CCS 2020
That Which We Call Private
With Úlfar Erlingsson, Ilya Mironov, and Shuang Song
Poster at USENIX Security 2019
Protecting accounts from credential stuffing with password breach alerting
With Kurt Thomas, Jennifer Pullman, Kevin Yeo, Patrick Gage Kelley, Luca Invernizzi, Borbala Benko,
Sarvar Patel, Dan Boneh, and Elie Burzstein
Distinguished Paper Award Winner
USENIX Security 2019
Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity
With Úlfar Erlingsson, Vitaly Feldman, Ilya Mironov, Kunal Talwar, and Abhradeep Guha Thakurta
SODA 2018
Scalable Private Learning with PATE
With Nicolas Papernot, Shuang Song, Ilya Mironov, Kunal Talwar, and Úlfar Erlingsson
ICLR 2018
Prochlo: Strong Privacy for Analytics in the Crowd
With Andrea Bittau, Úlfar Erlingsson, Petros Maniatis, Ilya Mironov, David Lie, Mitch Rudominer, Ushasree Kode,
Julien Tinnes, and Bernhard Seefeld
ACM SOSP 2017
Frodo: Take off the ring! Practical, Quantum-Secure Key Exchange from LWE
With Joppe Bos, Craig Costello, Léo Ducas, Ilya Mironov, Michael Naehrig, Valeria Nikolaenko, and Douglas Stebila
ACM CCS 2016 

PhD Work

Improved Constructions of PRFs Secure Against Related-Key Attacks
With Kevin Lewi and Hart Montgomery
ACNS 2014
Function-Private Subspace-Membership Encryption and Its Applications
With Dan Boneh and Gil Segev
ASIACRYPT 2013 
Function-Private Identity-Based Encryption: Hiding the Function in Functional Encryption
With Dan Boneh and Gil Segev
CRYPTO 2013 
Message-Locked Encryption for Lock-Dependent Messages
With Martín Abadi, Dan Boneh, Ilya Mironov, and Gil Segev
CRYPTO 2013 
Key-Homomorphic PRFs and Their Applications
With Dan Boneh, Kevin Lewi, and Hart Montgomery
CRYPTO 2013 
Deterministic Public-Key Encryption for Adaptively Chosen Plaintext Distributions
With Gil Segev and Salil Vadhan
EUROCRYPT 2013 
Journal of Cryptology 2018
Algebraic PRFs with Improved Efficiency from the Augmented Cascade
With Dan Boneh, Hart Montgomery
ACM CCS 2010 
Obfuscating Straight Line Arithmetic Programs
With Srivatsan Narayanan, Ramarathnam Venkatesan
DRM Workshop at ACM CCS 2009 

Service

I have recently served on the program committees for the following conferences: IEEE S&P (Oakland) 2023, CRYPTO 2020, PETS 2025, 2023.

In the past, I have served on PCs or reviewed papers for the following conferences: EUROCRYPT, Usenix Security, PKC, TCC, PODS, ICALP, Financial Crypto, and ICISC.

Teaching

I helped my advisor with this excellent online course! in the Winter of 2012.
I was a Course Assistant (CA) for CS255: Introduction to Cryptography in Winter 2012 and 2011.

Personal

My sister Aditi Raghunathan is also a computer scientist.
My Erdös number is 3: Paul Erdös → Peter Montgomery → Ramarathnam Venkatesan → me.
A short write-up on the Gödel prize-winning Toda's theorem—one of my favorite results in complexity theory—as a project report for Prof. Luca Trevisan's CS254.

(Last Updated: Aug 2026)