PeopleofSuperintelligence

Researcher

Chandrashekar Lakshminarayanan

Chandrashekar Lakshminarayanan is an IIT Madras researcher whose work spans reinforcement learning, deep learning and stochastic control. Early work applied Markov decision processes to crowdsourcing prices; later papers studied reinforcement-learning algorithms, active subnetworks in deep networks and interpretable dynamic pricing. He earned a PhD at the Indian Institute of Science and held research posts at the University of Alberta and DeepMind before teaching at IIT Palakkad. As of October 2026, he is an assistant professor in computer science and engineering at IIT Madras.

Badges

Timeline

  1. 2014

    Pricing crowdsourcing jobs

    In 2014, he coauthors a Markov decision process framework for pricing crowdsourcing tasks to make job completion times more predictable.

  2. 2016

    An IISc doctorate

    He completes a PhD in computer science and automation at the Indian Institute of Science (IISc) in 2016. He earns a B.Tech. at NIT Trichy and a master's degree at IISc.

  3. 2016–2018

    From Alberta to DeepMind

    He works as a postdoctoral research fellow in the University of Alberta's Department of Computing Science from July 2016 to June 2017. He joins DeepMind in London as a research scientist in August 2017 and works there through July 2018.

  4. 2018

    Stochastic approximation for RL

    In a 2018 AISTATS paper, he and Csaba Szepesvari study constant-step-size linear stochastic approximation for reinforcement learning. They show that averaged TD(0) and CAGTD achieve an asymptotic fast rate.

  5. August 2018–August 2021

    Assistant professor at IIT Palakkad

    At IIT Palakkad, he serves as an assistant professor from August 2018 to August 2021.

  6. 2020

    Neural paths in deep networks

    In a 2020 paper, he and Amit Vikram Singh analyze active subnetworks in deep learning through neural path features. Experiments on MNIST and CIFAR-10 link learned features to generalization in standard ReLU networks.

  7. January 2026

    Dynamic pricing with ADEPT

    In January 2026, he and Srividhya Sethuraman coauthor a study of dynamic market pricing that introduces ADEPT, a projection-free online learning algorithm working directly in attribute space.

  8. As of October 2026

    Assistant professor at IIT Madras

    As of October 2026, he is an assistant professor in the Department of Computer Science and Engineering at IIT Madras. His research interests include reinforcement learning, stochastic control and deep learning.

Career

  1. NowIIT MadrasAssistant Professor
  2. 2018–2021Indian Institute of Technology PalakkadAssistant Professor
  3. 2017–2018Google DeepMindResearch Scientist
  4. 2016–2017University of AlbertaPostdoctoral Research Fellow

Education

  1. 2016Indian Institute of SciencePhD
  2. National Institute of Technology TiruchirappalliB.Tech.

From the biography.

  1. The median h-index is 48 at universities and 14 at frontier AI labsIncludes Chandrashekar Lakshminarayanan. The median h-index is 48 at universities and 14 at frontier AI labs. We compare publishing careers, recent citations, dual appointments and job moves across 2,420 university researchers and 308 frontier-lab researchers.
  2. 23% of people shaping AI who left a university for a company later returned to a universityIncludes Chandrashekar Lakshminarayanan. 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.
  3. Google had the most people shaping AI every year from 2014 to 2025Includes Google. Our estimates of which organizations employed the most people shaping AI each year from 1955 to 2025, tracing the shift from university labs to companies.
  4. Google has the highest combined h-index among AI organizationsIncludes Google. We estimate that Google holds the highest combined h-index at 8,016, while universities account for 73% of the deduplicated total across AI organizations.

Colleagues

People named in this biography, and people with dated positions at the same organization in the same years.

Sources and credits

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  1. A Markov Decision Process Framework for Predictable Job Completion Times on Crowdsourcing Platforms ojs.aaai.org. Checked 20 October 2026.
  2. Chandrashekar Lakshminarayanan | Wadhwani School of Data Science and Artificial Intelligence wsai.iitm.ac.in. Checked 20 October 2026.
  3. Chandrashekar Lakshminarayanan sites.google.com. Checked 20 October 2026.
  4. Linear Stochastic Approximation: How Far Does Constant Step-Size and Iterate Averaging Go? proceedings.mlr.press. Checked 20 October 2026.
  5. Neural Path Features and Neural Path Kernel : Understanding the role of gates in deep learning arxiv.org. Checked 20 October 2026.
  6. Learning to Price: Interpretable Attribute-Level Models for Dynamic Markets arxiv.org. Checked 20 October 2026.