Ken Goldberg

About

Ken Goldberg is a pioneering roboticist and professor at UC Berkeley whose research spans robotic grasping, deep learning for manipulation, cloud robotics, surgical automation, and AI-driven perception. He is perhaps best known for the Dexterity Network (Dex-Net) project, which revolutionized robotic grasp planning by combining large-scale synthetic datasets, deep learning, and analytic grasp metrics. Dex-Net 2.0 alone has garnered over 1,400 citations across versions, establishing it as a landmark contribution to data-driven robotics. His work on Dex-Net 1.0 introduced cloud-based collaborative grasp planning using multi-armed bandit models, while his research on imitation learning via Virtual Reality teleoperation (590 citations) opened new pathways for intuitive robot skill acquisition. Goldberg has also pushed boundaries at the intersection of robotics and medicine, contributing to automated surgical suturing and AI-driven medical robotics. More recently, his involvement in Language Embedded Radiance Fields (LERF, 291 citations) reflects a forward-looking engagement with language-grounded 3D scene understanding. With foundational work in simulation-to-real transfer and object segmentation, Goldberg's cumulative impact makes him one of the most influential figures shaping the future of intelligent, dexterous robotic systems.

Research Focus

Key Achievements

Top Papers

1. 1
   Dex-Net 2.0: Deep Learning to Plan Robust Grasps with Synthetic Point Clouds and Analytic Grasp Metrics

   1,162 citations · 2017
2. 2
   Deep Imitation Learning for Complex Manipulation Tasks from Virtual Reality Teleoperation

   590 citations · 2018
3. 3
   Dex-Net 1.0: A cloud-based network of 3D objects for robust grasp planning using a Multi-Armed Bandit model with correlated rewards

   374 citations · 2016
4. 4
   LERF: Language Embedded Radiance Fields

   291 citations · 2023
5. 5
   Dex-Net 2.0: Deep Learning to Plan Robust Grasps with Synthetic Point Clouds and Analytic Grasp Metrics

   277 citations · 2017
6. 6
   Segmenting Unknown 3D Objects from Real Depth Images using Mask R-CNN Trained on Synthetic Data

   189 citations · 2019
7. 7
   Artificial intelligence meets medical robotics

   180 citations · 2023
8. 8
   Automating multi-throw multilateral surgical suturing with a mechanical needle guide and sequential convex optimization

   168 citations · 2016
9. 9
   Sim2Real in Robotics and Automation: Applications and Challenges

   151 citations · 2021
10. 10
    Algorithmic Foundations of Robotics V

    151 citations · 2004

Key Collaborators

Contact & Links