Rahul Rachuri

Rahul Rachuri

Staff Research Scientist

About Me

I'm currently a Research Scientist at Visa Research, in the Advanced Cryptography team.

Previously, I was a PhD student in the Crypto Group from 2019 to 2022 at Aarhus University, Denmark under Prof. Peter Scholl and Prof. Claudio Orlandi. My research was mainly focused on building protocols for Secure Multiparty Computation for different use cases. More specifically, my work was geared towards the domain of Privacy-Preserving Machine Learning.

I received my iMTech (BTech + MTech) degree in Information Technology from International Insitute of Information Technology, Bangalore in 2019. As a part of my thesis, I worked on building an efficient framework to perform Privacy-Preserving Machine Learning using Secure Multiparty Computation. I worked under the guidance of Prof. Ashish Choudhury, along with members of the CrIS Lab.

Publications
  1. Is Passive Security Reasonable in Privacy-Preserving Machine Learning?

    Matthew Jagielski, Rahul Rachuri, Peter Scholl

    In Submission
  2. Cheater Identification on a Budget: MPC with Identifiable Abort from Pairwise MACs

    Carsten Baum, Nikolas Melissaris, Rahul Rachuri, Peter Scholl

    Crypto 2024
  3. Ramen: Souper Fast Three-Party Computation for RAM Programs

    Lennart Braun, Mahak Pancholi, Rahul Rachuri, Mark Simkin

    ACM CCS 2023
  4. Le Mans: Dynamic and Fluid MPC for Dishonest Majority

    Rahul Rachuri, Peter Scholl

    Crypto 2022
  5. Tetrad: Actively Secure 4PC for Secure Training and Inference

    Nishat Koti, Arpita Patra, Rahul Rachuri, Ajith Suresh

    NDSS 2021
  6. Adversarial Attacks and Countermeasures on Private Training in MPC

    Daniel Escudero, Matthew Jagielski, Rahul Rachuri, Peter Scholl

    PPML@NeurIPS 2021
  7. Improved Primitives for MPC over Mixed Arithmetic-Binary Circuits

    Daniel Escudero, Satrajit Ghosh, Marcel Keller, Rahul Rachuri, Peter Scholl

    Crypto 2020
  8. Trident: Efficient 4PC Framework for Privacy Preserving Machine Learning

    Harsh Chaudhari, Rahul Rachuri, Ajith Suresh

    NDSS 2020
  9. Modeling Confirmation Bias Through Egoism and Trust in a Multi Agent System

    Seetarama Raju Pericherla, Rahul Rachuri, Shrisha Rao

    IEEE SMC 2018
Teaching
  1. Computability and Logic

    Course Code: 520171U005

    Spring 2021: Teaching Assistant
  2. Computability and Logic

    Course Code: 520171U005

    Spring 2020: Teaching Assistant
  3. Foundations of Cryptography

    Course Code: CS616

    Spring 2019: Teaching Assistant
  4. Introduction to Automata Theory and Computability

    Course Code: CS551

    Fall 2018: Teaching Assistant

Find out more


CV

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Education
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Research Experience
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