Sumedh A Sontakke
I am a PhD Student at the Computer Science Department, at the University of Southern California where I work on reinforcement learning, machine learning, and artificial general intelligence. I was a Student Researcher at Google Brain (now Google Deepmind) in 2022 and a Research Intern at the Robot Learning Group at Microsoft Research in 2023. I'm interested in autonomous decision-making, causality, and robot learning. My current research is about teaching robots to discover physical processes (friction, gravity, etc) through interaction. I also work on learning from demonstrations.
At USC, I'm fortunate to be advised by Prof Laurent Itti and Prof Erdem Bıyık. I was also fortunate to collaborate with Prof Bernhard Schölkopf at the Max Planck Institute for Intelligent Systems. In an old life, I helped build the Facebook-start funded Skyline Labs. I have also spent time at the Adolphs Lab at Caltech, in addition to University of Oxford as a SENS Scholar. In the industry, I've done internships at Bell Labs and Adobe Research. I received my bachelor's in electrical engineering at the College of Engineering, Pune in 2019.
Service: I review for ICLR, AISTATS, ICML and NeurIPS.
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Preprints
I'm interested in autonomous decision making, causality and machine learning.
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RoboCLIP:One Demonstration is Enough to Learn Robot Policies
Sumedh A. Sontakke, Jesse Zhang, Sébastien M. R. Arnold, Karl Pertsch, Erdem Bıyık, Dorsa Sadigh, Chelsea Finn, Laurent Itti
Thirty-seventh Conference on Neural Information Processing Systems, NeurIPS 2023
Website
We teach a robot how to perform a task using a single visual demonstration or a textual description of the task.
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RT-1: Robotics Transformer for Real-World Control at Scale.
Google Deepmind (Internship Project)
Robotics Science and Systems, 2023. Best Demo Paper Finalist
Website
We build a Foundation Model for Manipulation solving more than 700 tasks.
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SHERLock: Self-Supervised Hierarchical Event Representation Learning
Sumegh Roychowdhury*, Sumedh A. Sontakke*, Nikaash Puri, Mausoom Sarkar, Milan Aggarwal, Pinkesh Badjatiya, Balaji Krishnamurthy, Laurent Itti
International Conference on Pattern Recognition 2022
Code
We generate hierarchical concepts from long horizon video demonstrations without supervision.
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GalilAI: Out-of-Task Distribution Detection using Causal Active Experimentation for Safe Transfer RL
Sumedh A. Sontakke*, Stephen Iota*, Zizhao Hu*, Arash Mehrjou, Laurent Itti, Bernhard Schölkopf
The 25th International Conference on Artificial Intelligence and Statistics, 2022.
Website
We teach RL agents to detect Out-of-Distribution Tasks. Our agents differentiates between the effects of Mass and Gravity, like Galileo!
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Causal Curiosity: RL Agents Discovering Self-supervised Experiments for Causal Representation Learning
Sumedh A. Sontakke, Arash Mehrjou, Laurent Itti, Bernhard Schölkopf
Thirty-eighth International Conference on Machine Learning (ICML) Spotlight, 2021.
Website and Code
We teach RL agents to perform self-supervised experiments to discover the causal processes like gravity and friction that affect their environment. Check out our Ant pirouetting to discover how heavy it is!
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Unsupervised Hierarchical Concept Learning
Sumegh Roychowdhury*, Sumedh A. Sontakke*, Nikaash Puri, Mausoom Sarkar, Milan Aggarwal, Pinkesh Badjatiya, Balaji Krishnamurthy, Laurent Itti
BabyMind Workshop at Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS) 2020.
Code
We generate hierarchical concepts from long horizon video demonstrations without supervision.
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Classification of Cardiotocography Signals Using Machine Learning
Sumedh A. Sontakke, Jay Lohokare, Reshul Dani, Pranav Shivagaje
IntelliSys 2018. Advances in Intelligent Systems and Computing. Springer, 869, 2019
We use deep-learning techniques to improve CTG based diagnosis.
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Acquiring Domain Knowledge for Cardiotocography: A Deep Learning Approach
Priyamvada Huddar, Sumedh A. Sontakke
IEEE International Conference on Informatics and Computational Sciences 2019
We use multi-task learning techniques to improve CTG representation learning.
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Emergency services platform for smart cities
Jay Lohokare, Reshul Dani, Sumedh A. Sontakke , Ameya Apte and Rishab Sahni
2017 IEEE Region 10 Symposium (TENSYMP)
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Diagnosis of liver diseases using machine learning
Sumedh A. Sontakke, Jay Lohokare, Reshul Dani
2017 IEEE International Conference on Emerging Trends & Innovation in ICT (ICEI) (pp. 129-133)
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Scalable tracking system for public buses using IoT technologies
Jay Lohokare, Reshul Dani, Sumedh A. Sontakke
2017 IEEE International Conference on Emerging Trends & Innovation in ICT (ICEI) (pp. 104-109)
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Automated data collection for credit score calculation based on financial transactions and social media
Jay Lohokare, Reshul Dani, Sumedh A. Sontakke
2017 IEEE International Conference on Emerging Trends & Innovation in ICT (ICEI) (pp. 134-138)
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