1037 talks, interviews and lectures on humanoid robots, each summarised with its key moments, so you can read the gist and jump to the part you need.
Hanxiao Jiang of Columbia University presents GRASP Lab’s Fall 2026 SFI talk on how physics models can help robots predict and respond to interactions with the physical world.
Andrea Bajcsy, a robotics researcher at Carnegie Mellon University, discusses how to make increasingly capable generalist robots safer, with examples from her lab’s work at the GRASP seminar at Penn.
Jesse Zhang, a PhD student at the University of Washington, presents at the GRASP Lab’s Fall 2026 GRASP SFI about extracting more useful training signal from robot data to help robots keep learning after deployment.
Glen Berseth, assistant professor at Université de Montréal and Mila, discusses using pretrained models, reinforcement learning, and search to improve embodied control at the Spring 2026 GRASP Seminar, hosted by GRASP Lab.
Tom Zhang of Daxo Robotics discusses robotic hand design, the company’s technology and its path from student research and agricultural products to a dexterous hand at a GRASP Lab talk at Penn.
Chuning Zhu, a robotics researcher at the University of Washington, presents research on scaling robot learning with world models at the Spring 2026 GRASP SFI seminar hosted by GRASP Lab.
Stone Tao, a PhD student at the University of California, San Diego, presents simulation-integrated robot learning at the GRASP Lab, covering sim-to-real cable routing and simulation software design.
David Held, associate professor at Carnegie Mellon University and head of the RPAD Lab, presents research on precise, generalizable robot manipulation at a GRASP on Robotics seminar hosted by a Penn faculty member.
Jiafei Duan, a robotics researcher whose university affiliation is given as the University of Washington, presents at GRASP Lab on building robotics foundation models that reason before acting.
Jie Tan, a robotics director at Google DeepMind, reviews a decade of robot learning and discusses progress, obstacles, and the path toward general-purpose robots at Penn’s GRASP on Robotics series.
Huy Ha, a researcher affiliated with Columbia University and Stanford University, presents GRASP Lab work on collecting manipulation data with UMI and using it to control quadruped robots.
Roberto Martín Martín, a robotics researcher at the University of Texas at Austin, presents GRASP Lab research on learning mobile manipulation with limited real-world demonstrations, at the Fall 2025 GRASP SFI.
Suraj Nair of Physical Intelligence discusses building general-purpose robot models at a GRASP Lab seminar hosted by Zach.
Tairan He, affiliated with Carnegie Mellon University and NVIDIA, presents at GRASP Lab on scalable simulation learning for general-purpose humanoid skills.
Baxi Chong, a researcher at Georgia Institute of Technology, discusses how mechanical intelligence and redundant robot designs can improve locomotion in noisy, complex terrain, and how to balance that with sensing and control.
Dian Wang, a PhD candidate at Northeastern University, presents research on symmetry-aware robot learning at the Fall 2024 GRASP SFI.
Eric Jang, AI team lead at 1X Technologies, describes the company’s humanoid robots and data engine at the Spring 2024 GRASP SFI event hosted by GRASP Lab.
Xiaolong Wang, robotics and vision researcher at the University of California San Diego, presents his group’s work on generalization for robotics at the Fall 2023 GRASP SFI.
Andy Zeng of Google DeepMind presents “From Words to Actions” to GRASP Lab at the Fall 2023 GRASP SFI, outlining how language and vision-language models can help robots plan and act.
Michael Chang, a PhD researcher at the University of California, Berkeley, presents his work at the GRASP Lab Spring 2023 SFI on neural abstractions for modeling and controlling systems, and discusses future human-computer interfaces at DeepMind.
A GRASP Lab seminar host and panelists Nadia Figueroa, Dinesh Jayaraman, and Mark Yim discuss robotics research, deployment challenges, and future opportunities at the University of Pennsylvania.
Harold Soh of the National University of Singapore discusses robot learning and human-robot interaction at the Fall 2022 GRASP SFI, hosted by GRASP Lab.
Roberto Calandra, a researcher at Meta AI, presents his work on tactile sensing at the GRASP Lab’s Fall 2022 SFI seminar in Philadelphia.
Srinath Sridhar, professor at Brown University, discusses methods for generating and editing 3D shapes and aligning objects for robotic perception at a GRASP SFI seminar.
Sonia Chernova, a robotics researcher at Georgia Institute of Technology, presents work on semantically guided robot assistance and interaction for the GRASP Lab’s Fall 2022 SFI.
Zhongyu Li, a PhD student at Tsinghua University working with UC Berkeley’s Koushil Sreenath, presents research on combining model-based safety methods with model-free reinforcement learning for legged robots.
Dr. Dinesh Jayaraman, a faculty member in computer and information science at the University of Pennsylvania and GRASP Lab, discusses visual robot learning and ways to make robots more capable in uncertain settings.
Dr. Nadia Figueroa, a new GRASP faculty member at the University of Pennsylvania, presents her research on collaborative, human-aware robotics and the challenges of making robots learn, adapt, and work safely with people.
Stefanie Tellex, a Brown University robotics researcher, presents her work on language-guided robot collaboration at a GRASP Lab seminar.
Vincent Sitzmann, an MIT researcher, presents GRASP Lab’s spring 2022 robotics seminar on learning 3D scene representations from images and applying them to robot control and manipulation.
Jason Ma, researcher at the University of Pennsylvania, presents research on safer and reward-free offline reinforcement learning at a GRASP Lab seminar.
Robert J. Wood, a robotics researcher at Harvard University, discusses designing soft manipulators for delicate and dexterous tasks, including deep-sea sampling, in a GRASP Lab seminar.
Shuran Song, a robotics researcher at Columbia University, presents her work on dynamic manipulation of deformable objects at the GRASP Lab Spring 2022 SFI.
Ted Xiao, a robotics researcher at Google, presents his views on end-to-end robot learning at the GRASP Lab Spring 2022 seminar.
Dieter Fox, a University of Washington professor who also leads robotics research at NVIDIA, presents joint work from those teams at GRASP Lab on robot manipulation, with host Dan.
Dorsa Sadigh, a Stanford University professor working across robotics, learning, and control, presents research on how robots can learn and shape interactions, with examples from air hockey, household coordination, and human feedback.
Briefs summarise talks and interviews; timestamps open the video at that moment. Claims in a talk are the speaker's own.
