About me

Hi there! I am a PhD Candidate at the Institute for Information-Oriented Control (ITR), Technical University of Munich. I am being supervised by Prof. Sandra Hirche.

BackGround

I completed my Master’s degree at the Technical University of Munich. During this time, I was also an Intern at the AI Research team under Prof. Dr. Patrick Van der Smagt at Volkswagen AG. During this period, I completed my master’s thesis, focusing on the development of state-space models for learning dynamics in control at the lab. I was an AI Resident from 2019 to 2020 at Facebook AI Research (FAIR) in Menlo Park, California. I was a part of the Robotics LAB at FAIR and collaborated with Dr. Franziska Meier. During my time there, I worked on a variety of projects aimed at improving robotic manipulation and control, including representation learning for control and manipulation of robotic arms from visual data, learning loss functions for inverse dynamics training, and model-based inverse reinforcement learning from visual demonstrations.

Interests

My research interests mostly lie in inferring more about the physical world (and creating a model of the same for control/manipulation) using machine learning architectures. Such a model has several applications - it can help answer pertinent questions regarding the causes of any phenomena that occur in their scope, help learn a policy that can output controls to drive the physical environment to a goal state that satisfies desired properties, or, given a chain of previous observations, help predict what would happen next.

I am particularly interested in learning about models and representations of dynamical systems that facilitate easier control and manipulation. I am also interested in learning better task representations that can automatically translate a higher-level task into interpretable and easily optimizable costs.

Apart from the above, I enjoy singing, doodling, reading mystery novels, and have recently found a fondness for writing!