Uploaded November 2023 | Updated September 2026, 10 hours ago
Dr. Fei-Fei Li joins us for a fireside chat with Ali. She discusses her latest book, The Worlds I See: Curiosity, Exploration, and Discovery at the Dawn of AI.
Bio:
Dr. Fei-Fei Li is the inaugural Sequoia Professor in the Computer Science Department at Stanford University, and Co-Director of Stanford’s Human-Centered AI Institute. She served as the Director of Stanford’s AI Lab from 2013 to 2018. And during her sabbatical from Stanford from January 2017 to September 2018, Dr. Li was Vice President at Google and served as Chief Scientist of AI/ML at Google Cloud. Since then she has served as a Board member or advisor in various public or private companies. Dr. Fei-Fei Li obtained her B.A. degree in physics from Princeton in 1999 with High Honors, and her PhD degree in electrical engineering from California Institute of Technology (Caltech) in 2005. She also holds a Doctorate Degree (Honorary) from Harvey Mudd College.
Dr. Fei-Fei Li’s current research interests include cognitively inspired AI, machine learning, deep learning, computer vision, robotic learning, and AI+healthcare especially ambient intelligent systems for healthcare delivery. In the past she has also worked on cognitive and computational neuroscience. Dr. Li has published more than 300 scientific articles in top-tier journals and conferences in science, engineering and computer science. Dr. Li is the inventor of ImageNet and the ImageNet Challenge, a critical large-scale dataset and benchmarking effort that has contributed to the latest developments in deep learning and AI. In addition to her technical contributions, she is a national leading voice for advocating diversity in STEM and AI. She is co-founder and chairperson of the national non-profit AI4ALL aimed at increasing inclusion and diversity in AI education.
Dr. Li has been working with policymakers nationally and locally to ensure the responsible use of technologies, including a number of U.S. Senate and Congressional testimonies, her service as a special advisor to the Secretary General of the United Nations, a member of the California Future of Work Commission for the Governor of California in 2019 - 2020, and a member of the National Artificial Intelligence Research Resource Task Force (NAIRR) for the White House Office of Science and Technology Policy (OSTP) and the National Science Foundation (NSF) in 2021-2022.
Dr. Li is an elected Member of the National Academy of Engineering (NAE), the National Academy of Medicine (NAM) and American Academy of Arts and Sciences (AAAS). She is also a Fellow of ACM, a member of the Council on Foreign Relations (CFR), a recipient of the Intel Lifetime Achievements Award in 2023, a recipient of the 2022 IEEE PAMI Thomas Huang Memorial Prize, 2019 IEEE PAMI Longuet-Higgins Prize, 2019 National Geographic Society Further Award, IAPR 2016 J.K. Aggarwal Prize, the 2016 IEEE PAMI Mark Everingham Award, the 2016 nVidia Pioneer in AI Award, 2014 IBM Faculty Fellow Award, 2011 Alfred Sloan Faculty Award, 2009 NSF CAREER award, the 2006 Microsoft Research New Faculty Fellowship, among others. Dr. Li is a keynote speaker at many academic or influential conferences, including the World Economics Forum (Davos), the Grace Hopper Conference 2017, and the TED2015 main conference. Work from Dr. Li's lab has been featured in a variety of magazines and newspapers including New York Times, Wall Street Journal, Fortune Magazine, Science, Wired Magazine, MIT Technology Review, Financial Times, and more. She was selected as a 2017 Women in Tech by the ELLE Magazine, a 2017 Awesome Women Award by Good Housekeeping, a Global Thinker of 2015 by Foreign Policy, and one of the “Great Immigrants: The Pride of America” in 2016 by the Carnegie Foundation, past winners include Albert Einstein, Yoyo Ma, Sergey Brin, et al.
Dr. Fei-Fei Li is the author of the book "The Worlds I See: Curiosity, Exploration and Discovery at the Dawn of AI", published by Macmillan Publishers in 2023.
Dr. Fei-Fei Li joins us for a fireside chat with Ali. She discusses her latest book, The Worlds I See: Curiosity, Exploration, and Discovery at the Dawn of AI.
Bio:
Dr. Fei-Fei Li is the inaugural Sequoia Professor in the Computer Science Department at Stanford University, and Co-Director of Stanford’s Human-Centered AI Institute. She served as the Director of Stanford’s AI Lab from 2013 to 2018. And during her sabbatical from Stanford from January 2017 to September 2018, Dr. Li was Vice President at Google and served as Chief Scientist of AI/ML at Google Cloud. Since then she has served as a Board member or advisor in various public or private companies. Dr. Fei-Fei Li obtained her B.A. degree in physics from Princeton in 1999 with High Honors, and her PhD degree in electrical engineering from California Institute of Technology (Caltech) in 2005. She also holds a Doctorate Degree (Honorary) from Harvey Mudd College.
Dr. Fei-Fei Li’s current research interests include cognitively inspired AI, machine learning, deep learning, computer vision, robotic learning, and AI+healthcare especially ambient intelligent systems for healthcare delivery. In the past she has also worked on cognitive and computational neuroscience. Dr. Li has published more than 300 scientific articles in top-tier journals and conferences in science, engineering and computer science. Dr. Li is the inventor of ImageNet and the ImageNet Challenge, a critical large-scale dataset and benchmarking effort that has contributed to the latest developments in deep learning and AI. In addition to her technical contributions, she is a national leading voice for advocating diversity in STEM and AI. She is co-founder and chairperson of the national non-profit AI4ALL aimed at increasing inclusion and diversity in AI education.
Dr. Li has been working with policymakers nationally and locally to ensure the responsible use of technologies, including a number of U.S. Senate and Congressional testimonies, her service as a special advisor to the Secretary General of the United Nations, a member of the California Future of Work Commission for the Governor of California in 2019 - 2020, and a member of the National Artificial Intelligence Research Resource Task Force (NAIRR) for the White House Office of Science and Technology Policy (OSTP) and the National Science Foundation (NSF) in 2021-2022.
Dr. Li is an elected Member of the National Academy of Engineering (NAE), the National Academy of Medicine (NAM) and American Academy of Arts and Sciences (AAAS). She is also a Fellow of ACM, a member of the Council on Foreign Relations (CFR), a recipient of the Intel Lifetime Achievements Award in 2023, a recipient of the 2022 IEEE PAMI Thomas Huang Memorial Prize, 2019 IEEE PAMI Longuet-Higgins Prize, 2019 National Geographic Society Further Award, IAPR 2016 J.K. Aggarwal Prize, the 2016 IEEE PAMI Mark Everingham Award, the 2016 nVidia Pioneer in AI Award, 2014 IBM Faculty Fellow Award, 2011 Alfred Sloan Faculty Award, 2009 NSF CAREER award, the 2006 Microsoft Research New Faculty Fellowship, among others. Dr. Li is a keynote speaker at many academic or influential conferences, including the World Economics Forum (Davos), the Grace Hopper Conference 2017, and the TED2015 main conference. Work from Dr. Li's lab has been featured in a variety of magazines and newspapers including New York Times, Wall Street Journal, Fortune Magazine, Science, Wired Magazine, MIT Technology Review, Financial Times, and more. She was selected as a 2017 Women in Tech by the ELLE Magazine, a 2017 Awesome Women Award by Good Housekeeping, a Global Thinker of 2015 by Foreign Policy, and one of the “Great Immigrants: The Pride of America” in 2016 by the Carnegie Foundation, past winners include Albert Einstein, Yoyo Ma, Sergey Brin, et al.
Dr. Fei-Fei Li is the author of the book "The Worlds I See: Curiosity, Exploration and Discovery at the Dawn of AI", published by Macmillan Publishers in 2023.






![Learning Language-Guided Visuomotor Policies for Robotic Manipulation
Abstract: In this presentation, we will focus on the problem of learning language-guided visuomotor policies for robotic manipulation. We will explore different approaches to enabling robots to interpret natural language
instructions, perceive the current environment state, and act accordingly to solve a given task. We will begin this presentation by discussing the visual gap between simulation and the real world for policy transfer. Simulation training is safer and faster, but visual and physical mismatches often cause policies to fail once transferred to the real robot. To address this, we introduce a data-driven method for optimizing domain randomization parameters, enabling more effective sim-to-real transfer while minimizing the need for manual tuning and real-world trials. We then focus on language-guided policy learning, starting with Hiveformer, a 2D model that integrates
images and natural language instructions to perform manipulation tasks. To overcome the limitations of 2D inputs, such as lack of depth and occlusions, we introduce PolarNet and 3D-LOTUS, 3D point cloud-based models, to obtain more precise policies with better performance. In the final part of the talk, we will talk about the challenge of generalization in robotic manipulation. Many current approaches perform well on the same tasks they were trained for but fail to transfer to novel tasks. To address this problem, we propose a comprehensive benchmark with four levels of increasing difficulty, covering novel object placements, rigid and articulated objects, and long-horizon tasks. We then present 3D-LOTUS++, a generalist model that integrates three components: 3D-LOTUS as a trajectory prediction module, a large language model for task planning, and a vision-language model for object grounding.
Bio: Ricardo Garcia-Pinel is a last-year (graduating in Spring2025) PhD student at Inria Paris | ENS (Willow team) working on language-guided visuomotor policies for robotic manipulation. He is supervised by Cordelia
Schmid and Shizhe Chen. Ricardo received his BS degree in Telecommunication Technologies and Services and his MS degree in
Telecommunication Engineering in 2015 and 2018, respectively, from the Technical University of Madrid (UPM), Spain. Since then, he has worked on multiple computer vision and robotics projects, such as multi-
agent reinforcement learning for quadcopters, semantic segmentation, neural motion planning, or visual sim-to-real policy transfer. Currently, he is working on language-guided visuomotor policy learning for robotic
manipulation, focusing on policy generalization. His contributions in this field include works such as Hiveformer [1], Polarnet [2], 3D-LOTUS [3], and GEMBench [3]. For more information about his projects, check his webpage: https://rjgpinel.github.io/ or CV:
https://rjgpinel.github.io/files/resume_RicardoGarciaPinel_2025-30Jan.pdf
[1] Instruction-driven history-aware policies for robotic manipulations, CoRL 2022
[2] PolarNet: 3D Point Clouds for Language-Guided Robotic Manipulation, CoLR 2023
[3] Towards Generalizable Vision-Language Robotic Manipulation: A Benchmark and LLM-guided 3D Policy,
ICRA 2025 Learning Language-Guided Visuomotor Policies for Robotic Manipulation](https://i.ytimg.com/vi/qapMZKr-lHc/mqdefault.jpg)



