Jeannette Bohg

Jeannette Bohg is a Professor of Robotics and Computer Science at Stanford University, directing the Interactive Perception and Robot Learning Lab. Her work focuses on perception, learning, and real-time methods for autonomous robotic manipulation and grasping, emphasizing cross-embodiment learning. She previously led the Autonomous Motion Department at MPI for Intelligent Systems (2012–2017) and completed her PhD at KTH in Stockholm, with earlier studies at Chalmers and TU Dresden. Notable awards include the 2019 IEEE Early Career Award and the 2020 Robotics: Science and Systems Early Career Award.

• Education:
• PhD in Robotics, Perception and Learning (RPL), KTH Royal Institute of Technology, Stockholm (2012)
• Masters in Art and Technology, Chalmers University, Gothenburg
• Diploma in Computer Science, TU Dresden

Research interests span robotic grasping, equivariant policies, and scalable data-driven approaches. Key projects include the DROID dataset for cross-embodiment learning and development of the Tidybot mobile manipulator platform. Her lab explores principles of human sensorimotor coordination to enhance robotic autonomy, integrating machine learning and computer vision.

Recent work emphasizes leveraging human demonstrations and vision-language models for generalizable manipulation skills, alongside tactile sensing and sim-to-real transfer techniques.