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. 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? Research on this topic has to necessarily be at the intersection of Robotics, Machine Learning and Computer Vision. In my lab, we are specifically interested Robotic Grasping and Manipulation.
Prospective students and post-docs, please see this page.
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 incredibly 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 interested 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 Early Career and Best Paper awards, most notably the 2019 IEEE Robotics and Automation Society Early Career Award and the 2020 Robotics: Science and Systems Early Career Award.