Jeannette Bohg

Assistant Professor for Robotics at Stanford

I'm a Professor for Robotics at Stanford University. I'm also directing the Interactive Perception and Robot Learning Lab. I enjoy research at the intersection of Robotics, Machine Learning and Computer Vision applied to problems in Robotic Grasping and Manipulation.
I'm a Professor for Robotics and part of the Stanford AI lab within the Computer Science Department of Stanford University. I'm also directing the Interactive Perception and Robot Learning Lab, and enjoy research at the intersection of Robotics, Machine Learning and Computer Vision. Previously, I was a group leader at the Autonomous Motion Department (AMD) of the MPI for Intelligent Systems. My favourite robot will always be Apollo. Before joining the MPI in 2012, I did my PhD at the Division of Robotics, Perception and Learning (RPL) at KTH in Stockholm. In my thesis, I proposed novel methods towards multi-modal scene understanding for robotic grasping. I did my undergrad in Computer Science at the Technical University in Dresden. Well, actually it was a Diploma. Maybe today it would be called a coterm. I also studied Art and Technology at Chalmers in Gothenburg, which was incredible fun. In general, my research explores two questions: What are the underlying principles of robust sensorimotor coordination in humans, and how we can implement them on robots? My generous guess is that we will need a few more years to find out. We will keep searching. And hopefully some day, these robots will finally step out of the lab and become truly useful to people in the real world.
Jeannette Bohg is an Assistant Professor of Computer Science at Stanford University. She was a group leader at the Autonomous Motion Department (AMD) of the MPI for Intelligent Systems until September 2017. Before joining AMD in January 2012, Jeannette Bohg was a PhD student at the Division of Robotics, Perception and Learning (RPL) at KTH in Stockholm. In her thesis, she proposed novel methods towards multi-modal scene understanding for robotic grasping. She also studied at Chalmers in Gothenburg and at the Technical University in Dresden where she received her Master in Art and Technology and her Diploma in Computer Science, respectively. Her research focuses on perception and learning for autonomous robotic manipulation and grasping. She is specifically interesting in developing methods that are goal-directed, real-time and multi-modal such that they can provide meaningful feedback for execution and learning. Jeannette Bohg has received several awards, most notably the 2019 IEEE International Conference on Robotics and Automation (ICRA) Best Paper Award, the 2019 IEEE Robotics and Automation Society Early Career Award and the 2017 IEEE Robotics and Automation Letters (RA-L) Best Paper Award.
Website adapted from Cassidy Williams with permission.