PeopleofSuperintelligence

Researcher

Dhinakaran Vinayagamurthy

Dhinakaran Vinayagamurthy is a researcher whose work applies machine learning to quantum error correction and generative models. He grew up in Erode, studied in Chennai and Toronto, and completed a computer science PhD at Waterloo in 2019. His research spans early cryptography, encrypted databases and privacy-preserving exchange markets. In October 2026, he coauthored an IBM post on Qiskit’s C API; he is Manager, IBM Quantum India at IBM Research India in Bengaluru.

Now at
IBM
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Timeline

  1. By 2015

    Early education and cryptography

    He grows up in Erode, lives there through high school, then moves to Chennai to study computer science and engineering at College of Engineering, Guindy. He completes a master's with the University of Toronto's Computer Science Theory Group, advised by Vinod Vaikuntanathan. His papers include “ID Based Signcryption in Standard Model” in 2012, “Fully Key-Homomorphic Encryption, Arithmetic Circuit ABE and Compact Garbled Circuits” in 2014, and “Riding on Asymmetry: Efficient ABE for Branching Programs” in 2015.

  2. 2015–2019

    Waterloo PhD and StealthDB

    He starts a computer science PhD at the University of Waterloo in September 2015, where he works in the CrySP group and Institute for Quantum Computing with advisers David Jao and Sergey Gorbunov. He coauthors StealthDB in 2017, an Intel SGX encrypted database whose PostgreSQL prototype supports the full TPC-C benchmark, defends his thesis at the David R. Cheriton School of Computer Science in December 2018, and completes the degree in 2019.

  3. 2021

    The Rialto exchange

    In 2021, he coauthors Rialto, a decentralized privacy-preserving exchange marketplace for matching trade orders, settling trades on a blockchain and discovering market prices.

  4. 2022

    Machine learning for heavy hex

    In 2022, he coauthors a machine-learning decoder for heavy hexagonal quantum error-correcting codes. Across several noise models, it reaches thresholds about five times higher than minimum weight perfect matching (MWPM).

  5. 2023

    A quantum-enhanced VAE

    In 2023, he coauthors QeVAE, a quantum-classical generative model that uses quantum correlations to improve fidelity over classical VAEs. Tests on four-qubit and eight-qubit quantum circuit states report more than double the fidelity for some states.

  6. October 2026

    Qiskit beyond Python

    In October 2026, he coauthors the IBM Quantum post “Qiskit beyond Python: Fortran, C++, and Julia,” which explains how Qiskit's C API connects the SDK to those languages for native circuit work.

  7. As of October 2026

    Manager, IBM Quantum India

    As of October 2026, he is Manager, IBM Quantum India at IBM Research India in Bengaluru and Quantum Innovation Centers Lead for India and Singapore. He also serves as Engagement Manager for the IIT Madras-IBM Quantum partnership; his research interests include quantum error mitigation, cryptography and security.

Career

  1. NowIBMManager

Education

  1. 2019University of WaterlooPhD
  2. College of Engineering, GuindyUndergraduate study in computer science and engineering
  3. University of TorontoMaster's

From the biography.

  1. 23% of people shaping AI who left a university for a company later returned to a universityIncludes IBM. We estimate that 468 of the 2,011 people shaping AI who left a university for a company (23%) later returned to a university after a median of 5 years, and 163 of 829 (20%) made the reverse round trip.
  2. Google alumni have founded or led 133 other organizations, more than any other AI labIncludes IBM. We estimate that alumni of 17 major AI labs went on to found or lead 350 other organizations, including 226 they founded, and we trace 472 career moves directly between 23 labs since 2010.
  3. Universities keep AI researchers for a median of 6 years, compared with 2 years at frontier labsIncludes IBM. Across 15,811 dated work stays (6,529 people), median role tenure runs from 6 years at universities to 2 years at frontier labs. We compare all five organization types, starting decades from the 1970s to the 2020s, and the organizations that keep people longest.
  4. People shaping AI work at a median of 3 organizations over a career: 3 for university starters and institute and lab starters, versus 2 for company startersIncludes IBM. Across 6,853 people shaping AI with a dated work role, we estimate a median of 3 parent organizations over a career (mean 3.6), comparing role groups, starting sectors and starting decades from the 1950s to 2020–2026.

Sources and credits

Photo: We have no published photo of Dhinakaran Vinayagamurthy yet. Send us a free-licensed photo.

  1. Dhinakaran Vinayagamurthy cs.toronto.edu. Checked 22 October 2026.
  2. Dhinakaran Vinayagamurthy - IBM Research research.ibm.com. Checked 22 October 2026.
  3. Sergey Gorbunov sergeyg.tech. Checked 22 October 2026.
  4. PhD Defence • Cryptography, Security, and Privacy (CrySP) — User-Controlled Computations in Untrusted Computing Environments | Cheriton School of Computer Science | University of Waterloo uwaterloo.ca. Checked 22 October 2026.
  5. StealthDB: a Scalable Encrypted Database with Full SQL Query Support arxiv.org. Checked 22 October 2026.
  6. Privacy-Preserving Decentralized Exchange Marketplaces arxiv.org. Checked 22 October 2026.
  7. Efficient Syndrome Decoder for Heavy Hexagonal QECC via Machine Learning arxiv.org. Checked 22 October 2026.
  8. Learning hard distributions with quantum-enhanced Variational Autoencoders arxiv.org. Checked 22 October 2026.
  9. Qiskit beyond Python: Fortran, C++, and Julia | IBM Quantum Computing Blog ibm.com. Checked 22 October 2026.
  10. Dr. Dhinakaran Vinayagamurthy | Wadhwani School of Data Science and Artificial Intelligence wsai.iitm.ac.in. Checked 22 October 2026.