Ajith Suresh

ENCRYPTO · TU Darmstadt · (49) 1625122156 · suresh@encrypto.cs.tu-darmstadt.de

I am a chronic talker and lifelong learner who enjoys what I do. I was born in a remote village in Kerala, India's beautiful state known as "God's Own Country." My parents instilled in me the importance of following my dreams. I earned a Bachelor of Science in Computer Science and Engineering (CSE) from the College of Engineering (CET), Trivandrum. I pursued my passion at the Indian Institute of Science (IISc), where I earned my Masters (Research) and Ph.D in CSE under the guidance of Prof. Arpita Patra. During my doctoral studies, I investigated the field of MPC for a small population, with applications to Privacy-Preserving Machine Learning (PPML).

Under the supervision of Prof. Thomas Schneider, I am currently conducting post-doctoral research at the Cryptography and Privacy Engineering (ENCRYPTO) group at the Department of Computer Science at the Technical University of Darmstadt. My work orbits around the development of large-scale privacy-preserving protocols for the Internet.

I have been awarded a Google PhD Fellowship for 2019. When you're bored, go to World Through My Eyes.


Experience

Technical University of Darmstadt, Germany

Post-doctoral Researcher (At ENCRYPTO)
October 2021 - present

Indian Institute of Science (IISc), Bangalore, India

Research Associate (At CrIS)
August 2021 - September 2021

Technical University of Darmstadt, Germany

Research Intern (At ENCRYPTO)
November 2019

Amazon Development Centre, Bangalore, India

Software Development Engineer (SDE) Intern
July 2013 - August 2013

Education

Indian Institute of Science (IISc), Bangalore, India

Doctor of Philosophy (Ph. D.)
Computer Science - Secure Multi-party Computation

CGPA: 9 / 10

September 2017 - July 2021

Indian Institute of Science (IISc), Bangalore, India

Master of Technology (M.Tech, Research)
Computer Science - Secure Multi-party Computation

CGPA: 6.83 / 8

August 2014 - June 2017

College of Engineering (CET), Trivandrum, India

Bachelor of Technology (B.Tech)
Computer Science and Engineering

CGPA: 8.81 / 10

June 2010 - April 2014

Research

Preprints
  • Privadome: Protecting Citizen Privacy from Delivery Drones.
    Authors: Vinod Ganapathy, Eikansh Gupta, Arpita Patra, Gokulnath Pillai and Ajith Suresh. (Under Submission)
  • MPClan: Protocol Suite for Privacy-Conscious Computations.
    Authors: Nishat Koti, Shravani Patil, Arpita Patra and Ajith Suresh. (Under Submission)

Publications
  • Tetrad: Fair and Robust 4PC Framework for Privacy-Preserving Machine Learning.
    Authors: Nishat Koti, Arpita Patra, Rahul Rachuri and Ajith Suresh.
    NDSS'22 [CORE - A*]
  • SynCirc: Efficient Synthesis of Depth‑Optimized Circuits for Secure Computation.
    Authors: Arpita Patra, Thomas Schneider, Ajith Suresh and Hossein Yalame.
    IEEE HOST'21
  • SWIFT: Super-fast and Robust Privacy-Preserving Machine Learning.
    Authors: Nishat Koti, Mahak Pancholi, Arpita Patra and Ajith Suresh.
    USENIX Security'21 [CORE - A*]
  • ABY2.0: Improved Mixed-Protocol Secure Two-Party Computation.
    Authors: Arpita Patra, Thomas Schneider, Ajith Suresh and Hossein Yalame.
    USENIX Security'21 [CORE - A*]
  • BLAZE: Blazing Fast Privacy-Preserving Machine Learning.
    Authors: Arpita Patra and Ajith Suresh.
    NDSS'20 [CORE - A*]
  • Trident: Efficient 4PC Framework for Privacy Preserving Machine Learning.
    Authors: Harsh Chaudhari, Rahul Rachuri and Ajith Suresh.
    NDSS'20 [CORE - A*]
  • FLASH: Fast and Robust Framework for Privacy-preserving Machine Learning.
    Authors: Megha Byali, Harsh Chaudhari, Arpita Patra and Ajith Suresh.
    PoPETS'20 [CORE - A]
  • ASTRA: High Throughput 3PC over Rings with Application to Secure Prediction.
    Authors: Harsh Chaudhari, Ashish Choudhury, Arpita Patra and Ajith Suresh.
    ACM CCSW'19
  • Fast Actively Secure OT Extension for Short Secrets.
    Authors: Arpita Patra, Pratik Sarkar and Ajith Suresh.
    NDSS'20 [CORE - A*]

Workshops / Posters
  • MPClan: Protocol Suite for Privacy-Conscious Computations.
    Authors: Nishat Koti, Shravani Patil, Arpita Patra and Ajith Suresh.
    NDSS'22 (Poster)
  • Tetrad: Fair and Robust 4PC Framework for Privacy-Preserving Machine Learning.
    Authors: Nishat Koti, Arpita Patra, Rahul Rachuri and Ajith Suresh.
    PPML'21 (ACM CCS'21 Workshop)
  • ABY2.0: Improved Mixed-Protocol Secure Two-Party Computation.
    Authors: Arpita Patra, Thomas Schneider, Ajith Suresh and Hossein Yalame.
    PriML'21 (NeurIPS'21 Workshop), PPML'21 (ACM CCS'21 Workshop)
    PPML'21 (CRYPTO'21 Workshop)
  • MPCLeague: Robust and Efficient Mixed-protocol Framework for 4-party Computation.
    Authors: Nishat Koti, Arpita Patra and Ajith Suresh.
    IEEE S&P 2021 (Poster), DPML'21 (ICLR Workshop 2021)
  • SWIFT: Super-fast and Robust Privacy-Preserving Machine Learning.
    Authors: Nishat Koti, Mahak Pancholi, Arpita Patra and Ajith Suresh.
    ARCS'22 (Symposium), DPML'21 (ICLR Workshop 2021)
    PriML/PPML'20 (NeurIPS 2020 Workshop)
  • ASTRA: High Throughput 3PC over Rings with Application to Secure Prediction.
    Authors: Harsh Chaudhari, Ashish Choudhury, Arpita Patra and Ajith Suresh.
    PPML'19 (ACM CCS'19 Workshop)


Awards & Certifications


Talks / Presentations

  • SWIFT: Super-fast and Robust Privacy-Preserving Machine Learning.
    30th USENIX Security Symposium, Virtual Event - August 2021.
  • SWIFT: Super-fast and Robust Privacy-Preserving Machine Learning.
    CNI Networks Seminar Series, Virtual Event, India - June 2021.
  • MPC for small population with applications to Privacy‑Preserving Machine Learning.
    EECS Research Students' Symposium 2021, Virtual Event, India - May 2021.
  • MPCLeague: Robust and Efficient Mixed‑protocol Framework for 4‑party Computation.
    Distributed and Private Machine Learning (DPML), ICLR Workshop 2021,, Virtual Event - May 2021.
  • ABY2.0: Improved Mixed-Protocol Secure Two-Party Computation.
    ARCS Symposium 2021, Virtual Event, India - February 2021.
  • BLAZE: Blazing Fast Privacy-Preserving Machine Learning.
    ARCS Symposium 2021, Virtual Event, India - February 2021.
  • MPC MEETS ML: Efficient Privacy Preserving Machine Learning Techniques.
    EECS Research Students' Symposium 2020, Virtual Event - July 2020.
  • MPC MEETS ML: Efficient Privacy Preserving Machine Learning Techniques.
    International Symposium on Current Trends in Research and Innovation (ISCTRI’20), Virtual Event - July 2020.
  • BLAZE: Blazing Fast Privacy-Preserving Machine Learning.
    NDSS'20, San Diego - February 2020.
  • Trident: Efficient 4PC Framework for Privacy Preserving Machine Learning.
    NDSS'20, San Diego - February 2020.
  • ASTRA: High Throughput 3PC over Rings with Application to Secure Prediction.
    IRISS 2020, IIT Gandhinagar - February 2020.
  • ASTRA: High Throughput 3PC over Rings with Application to Secure Prediction.
    Techincal University, Darmstadt, Germany - November 2019.
  • MPC MEETS ML: High Throughput Secure ML Prediction.
    Amazon Project Review, IISc - March 2019.
  • Cryptography Basics.
    QIP STC on Foundations of Cryptography, IISc - August 2018
  • Fast Actively Secure OT Extension for Short Secrets.
    EECS Symposium, IISc - April 2017.
  • Fast Actively Secure OT Extension for Short Secrets.
    NDSS'17, San Diego - February 2017.
  • Oblivious Transfer (OT) and OT Extensions.
    Workshop on Cryptography, Information Security Education and Awareness Project Phase II, IISc - February 2016.
  • Two party computation (GMW construction).
    Workshop on Cryptography, Information Security Education and Awareness Project Phase II, IISc - February 2016.
  • Message Authentication Codes.
    Workshop on Cryptography, Information Security Education and Awareness Project Phase II, IISc - February 2016.
  • Efficient Actively Secure Oblivious Transfer Extension.
    IRISS 2016, Trivandrum, Kerala - January 2016.

Curriculum vitae

My CV is available here - [CV] [CV-Short].