Varun is currently a research scientist at Sony AI. He earned his master’s of science degree in informatics with a specialization in graphics, vision and robotics from Institut Nationale Polytechnique de Grenoble (INRIA Grenoble), and a Ph.D degree from Università della Svizzera Italiana (IDSIA Lugano), Switzerland, working with Prof. Juergen Schmidhuber. In his thesis work he developed algorithms that use the slowness principle for driving exploration in reinforcement learning agents. After completing his Ph.D., he worked as a postdoctoral researcher at the Institute for Neural Computation (INI), Germany. His research contributions led to several patents, publications in peer-reviewed journals and conference proceedings.


“My current focus at Sony AI is to develop algorithms to speed up learning multiple off-policy reinforcement learning tasks.”


Outracing Champion Gran Turismo Drivers with Deep Reinforcement Learning

Nature, 2022
Pete Wurman, Samuel Barrett, Kenta Kawamoto, James MacGlashan, Kaushik Subramanian, Thomas J. Walsh, Roberto Capobianco, Alisa Devlic, Franziska Eckert, Florian Fuchs, Leilani Gilpin, Piyush Khandelwal, Varun Kompella, Hao Chih Lin, Patrick MacAlpine, Declan Oller, Takuma Seno, Craig Sherstan, Michael D. Thomure, Houmehr Aghabozorgi, Leon Barrett, Rory Douglas, Dion Whitehead Amago, Peter Dürr, Peter Stone, Michael Spranger, Hiroaki Kitano

Many potential applications of artificial intelligence involve making real-time decisions in physical systems while interacting with humans. Automobile racing represents an extreme example of these conditions; drivers must execute complex tactical manoeuvres to pass or block…

Agent-Based Markov Modeling for Improved COVID-19 Mitigation Policies

JAIR, 2021
Roberto Capobianco, Varun Kompella, James Ault*, Guni Sharon*, Stacy Jong*, Spencer Fox*, Lauren Meyers*, Pete Wurman, Peter Stone

The year 2020 saw the covid-19 virus lead to one of the worst global pandemics in history. As a result, governments around the world have been faced with the challenge of protecting public health while keeping the economy running to the greatest extent possible. Epidemiologi…

Multiagent Epidemiologic Inference through Realtime Contact Tracing

AAMAS, 2021
Guni Sharon*, James Ault*, Peter Stone, Varun Kompella, Roberto Capobianco

This paper addresses an epidemiologic inference problem where, given realtime observation of test results, presence of symptoms,and physical contacts, the most likely infected individuals need to be inferred. The inference problem is modeled as a hidden Markovmodel where inf…


March 3, 2021 | Sony AI

The Challenge to Create a Pandemic Simulator

The thing I like most about working at Sony AI is the quality of the projects we're working on, both for their scientific challenges and for their potential for improving the world. What could be more exciting than magnifying hu…

The thing I like most about working at Sony AI is the quality of the projects we're working on, both for their scientific challen…


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