I am currently a postdoctoral researcher in the Intelligent Robotics research group at the Aalto Univerity, Finland. My broad area of interests comes under the umbrella of machine learning, reinforcement learning and machine learning for robotics (i.e robot learning). At Aalto university, currently I am focusing my research on safe sim-2-real adapation in robotics. I also collaborate with other people in our research group working on data-efficient learning of variable impedence control profile, zero-shot damage recovery in robotics, user preference learning combined with reinforcement learning and so on. In addition, I also work at SiloAI (the largest private AI lab) as an AI scientist (ad-hoc) to work on various topics related machine learning, computer vision, simulation design and so on.
Prior to Aalto, I worked as a doctoral researcher at INRIA - Nancy, France and obtained my PhD on machine learning and robotics from University of Lorraine, France. During my PhD I worked on algorithms that enable robots (or any dynamical system, agent) to learn controllers/policies with as fewer interactions as possible with the robot/system.
Research keywords: reinforcement learning, robot learning, data-efficient learning, sim-to-real adaptation, evolutionary computation, quality-diversity algorithms.
- Postdoctoral researcher (August 2020 - Present)
- Aalto University, Finland
- AI Scientist (January 2021 - Present)
- SiloAI, Finland
- Doctoral Researcher (October 2016 - July 2020)
- INRIA Nancy, France
- Software Engineer (July 2012 - July 2013)
- Capgemini, India
- Year 2020
- Kaushik, R., Anne, T. & Mouret, J.-B. (2020), Fast Online Adaptation in Robotics through Meta-Learning Embeddings of Simulated Priors. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (Accepted).
- Year 2019
- Kaushik, R., Desreumaux, K., & Mouret, J.-B. (2019), Adaptive Prior Selection for Repertoire-based Online Learning in Robotics. Frontiers in Robotics & AI.
- Year 2018
- Kaushik, R., Chatzilygeroudis, K., & Mouret, J.-B. (2018), Multi-objective Model-based Policy Search for Data-efficient Learning with Sparse Rewards. Conference on Robot Learning (CoRL)
- Year 2017
- Chatzilygeroudis, K., Rama, R., Kaushik, R., Goepp, D., Vassiliades, V., & Mouret, J.-B. (2017). Black-Box Data-efficient Policy Search for Robotics. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
- PhD (October 2016 - July 2020):
- University de Lorraine, France.
- Supervisor: Dr. Jean-Baptiste Mouret
- Thesis: Data-Efficient Robot Learning using Priors from Simulators
- M.Tech (2016):
- Electronics Design and Technology
- Tezpur University, India
- Rank : 2nd in the batch
- B.Tech (2012):
- Electronics and Communication Engineering
- Tezpur University, India
- Rank: 1st rank in the batch