Ken Goldberg

Ken Goldberg is a Professor in the Department of Computer Science at the University of California, Berkeley. His research focuses on Artificial Intelligence (AI), Control, Intelligent Systems, and Robotics (CIR), as well as Human-Computer Interaction (HCI). Goldberg supervises research in Robotics and Automation and holds dual degrees in Electrical Engineering and Economics from the University of Pennsylvania (1984) and a PhD from Carnegie Mellon University (1990). He joined the UC Berkeley faculty in 1995 and is also affiliated with the School of Information, Art Practice, and the UCSF Dept of Radiation Oncology. His work includes over 300 peer-reviewed papers and ten U.S. patents, with contributions to robotics, automation, and social information filtering.

Ken Goldberg is a professor at UC Berkeley and UCSF, known for his work in robotics, automation, and collaborative filtering. His research spans robotic learning, manipulation, and automation, with a focus on developing algorithms for efficient and robust robotic systems. He has contributed to the fields of deep learning for grasping, motion planning, and cloud robotics. His work includes the development of datasets and models for robotic learning, such as Dex-net and Open X-Embodiment. Goldberg's research also addresses real-world applications, such as using robotics in public health and infectious disease management. His publications highlight the integration of machine learning and robotics to enhance automation and human-robot collaboration.