Abhinav Valada is an Assistant Professor and Director of the Robot Learning Lab at the University of Freiburg, Germany. He is a member of the Department of Computer Science, the BrainLinks-BrainTools center and a founding member of the ELLIS unit Freiburg. Abhinav is co-chair of the IEEE Robotics and Automation Society Technical Committee on Robot Learning and an elected Scholar of the ELLIS Society.

His research lies at the intersection of robotics, machine learning and computer vision with a focus on tackling fundamental robot perception, state estimation and control problems using learning approaches in order to enable robots to reliably operate in more complex domains and diverse environments. The overall goal of his research is to develop scalable lifelong robot learning systems that continuously learn multiple tasks from what they perceive and experience by interacting with the real-world. His approach is to design deep learning algorithms that facilitate transfer of information through self-supervised multimodal and multitask learning by exploiting complementary features and cross-modal interdependencies. These techniques in turn enable robots to perceive more robustly and reason about the environment more effectively.