Qingyuan Workshop丨No.24
Closed-door seminar on humanoid robots
As the world generally faces the problem of population aging, humanoid robots, as an emerging technology field, are gradually emerging in industry, services, medical and other fields, bringing new opportunities to manufacturing, agriculture and various service industries. with solutions. Compared with traditional industrial robots, humanoid robots have significant advantages in intelligence, flexibility and diversity. By integrating advanced AI perception technology and large language models, humanoid robots have autonomous learning, decision-making and reasoning capabilities, allowing them to proactively adapt to changes in various complex environments.
This exchange will focus on issues such as technological innovation, application prospects and technological ethics in the field of humanoid robots. Relevant researchers and corporate technical experts will share the latest research results, experiences and insights on humanoid robots, and jointly discuss the role of humanoid robots in promoting social progress . , play a positive role in improving the quality of life; at the same time, we will also discuss the many challenges faced by humanoid robots, such as security, privacy protection and human-machine collaboration, to promote the sustainable development of this field.
time and location
Time: September 13 (Wednesday) 19:00-21:00 (Beijing time)
Location: Zhiyuan Building (online + offline)
Participants (in no particular order)
Suiyanan丨Associate Professor at Tsinghua University
Yin Peng丨Assistant Professor at City University of Hong Kong and former project scientist at Carnegie Mellon University
Gao Yang丨Assistant Professor, Institute of Interdisciplinary Information, Tsinghua University
Wang Bin丨Vice President of Dachi Robot Co., Ltd.
Chen Jianyu丨Assistant Professor at the Institute of Cross-Information at Tsinghua University and founder of Star Dynamic Era
Zhao Xing丨Assistant Professor, Institute of Cross-Information, Tsinghua University
Activity process
1. Guidance report
Guided Report-1: Building a Humanoid Universal Intelligent Robot
Chen Jianyu丨Assistant Professor at the Institute of Cross-Information at Tsinghua University and founder of Star Dynamic Era
Guidance Report-2: Embodied Intelligent Humanoid Robot Integrated with Cloud and Network
Wang Bin丨Vice President of Dachi Robot Co., Ltd.
Guidance report-3: From autonomous driving to general robots, thoughts on the implementation of robots
Yin Peng丨Assistant Professor at City University of Hong Kong and former project scientist at Carnegie Mellon University
2. Problem discussion & cooperation initiatives
Participants (in no particular order)
/ Wang Bin /
Vice President of Dart Robot Co., Ltd.
Master of Computer Software, MBA. Research areas include: cloud robot operating system, key technologies for humanoid robots, deep reinforcement learning, Sim2real, robot application development and ecological construction. He has a number of patents and copyrights in cloud robot technology. He once served as deputy leader of the China CERNET IPv6 backbone network construction expert group, vice chairman of the Zhongguancun Software Outsourcing Association, researcher of the State Key Laboratory of Software Development Environment, vice chairman of the Zhongguancun Intelligent Transportation Industry Alliance, and executive director of the founding member of the Internet of Things and Smart City Alliance. , hosted and participated in the Beijing Olympics urban dynamic transportation project and won the second prize of the National Science and Technology Progress Award.
/ Suiyanan /
Associate Professor at Tsinghua University
Committed to machine learning, neural interaction, and robotics research. He received a bachelor's degree from Tsinghua University and a doctorate from the California Institute of Technology in the United States, and engaged in postdoctoral work at the California Institute of Technology and Stanford University. The research results were written into the textbook Algorithms for Optimization at Stanford University and other universities as an independent topic. They won the ICRA Best Paper Award at the 2020 International Conference on Robotics and Automation, and have been used in the clinical treatment of nerve damage diseases in China and the United States. He has served as chairperson of important international conferences on artificial intelligence (AAAI, AISTATS, ICLR, NeurIPS, etc.) for many times. Selected into MIT Technology Review's "Top 35 Technological Innovators Under 35" list in China for his contributions to the intersection of artificial intelligence and neural engineering.
/ Yin Peng /
Assistant Professor, City University of Hong Kong, former project scientist at Carnegie Mellon University
He graduated from Harbin Institute of Technology with a bachelor's degree, a PhD from the University of Chinese Academy of Sciences in Beijing, and was a former Project Scientist at Carnegie Mellon University. From 2019 to 2021, he participated in the Darpa SubT Challenge and provided solutions for NASA's Mars landing positioning. From 2020 to 2022, he participated in the design and development of the DARPA multi-aircraft collaboration system and designed and developed a long-range lifelong learning system for NVIDIA. The research directions mainly include scene recognition, large scene positioning and navigation, 3D perception and reinforcement learning. He has published many journal conference articles in the famous robotics journals IEEE Transacitons on Robotics, IEEE Transacitons on Industry and Electronics, IEEE Transacitons on Intelligent Transportation Systems and IEEE RAL, as well as the three top robotics conferences ICRA, IROS and RSS.
/ Gaoyang /
Assistant Professor, Institute of Interdisciplinary Information, Tsinghua University
Assistant professor and doctoral supervisor at the Institute of Interdisciplinary Information at Tsinghua University, focusing on computer vision and robotics. Previously, he received his PhD from the University of California, Berkeley, under the tutelage of Professor Trevor Darrell. He also completed postdoctoral work at the University of California, Berkeley, with Pieter Abbeel and others. Prior to this, Gao Yang graduated from the Computer Science Department of Tsinghua University and conducted research work on Bayesian inference with Professor Zhu Jun.
/ Chen Jianyu /
Assistant Professor, Institute of Cross-Information, Tsinghua University, Founder of Star Era
He received his bachelor's degree from Tsinghua University and his doctorate from the University of California, Berkeley, where he studied under Professor Masayoshi Tomizuka, an academician of the National Academy of Engineering and a pioneer in the field of electromechanical control. In recent years, he has been engaged in cutting-edge research at the intersection of robotics and artificial intelligence. His research goal is to build high-end robot software and hardware systems with high performance and high intelligence. He has published more than forty papers in top international conferences and journals in the fields of robotics, artificial intelligence, control, transportation, etc., and some papers have been shortlisted for the Outstanding Paper Awards of international conferences such as L4DC 2022, IEEE IV 2021, IFAC MECC 2021, etc. Personal Honor: Forbes China’s 30 Elites Under 30 (Science List, 2021)
/ Zhao Xing /
Assistant professor and doctoral supervisor, Tsinghua Institute of Interdisciplinary Information
Obtained a Ph.D. from MIT, where he studied under Professor Antonio Torralba, head of the MIT AI&D Department, and later served as a research scientist at Waymo, the Google self-driving car project. Zhao Xing proposed a series of framework work in the fields of multi-modal learning, autonomous driving BEV perception, and trajectory prediction, which have been widely used and referenced by the industry. His research has also been widely reported by mainstream technology media such as BBC, NBC, and MIT Technology Review. His paper won the 2015 ICCP Best Paper Award. He himself was selected into the 2020 Forbes China U30 Science List.
Qingyuan Club·Qingyuan Workshop
Fill out the form and participate in the event
This event is a closed-door discussion, with no live broadcast or video playback. The event is open to 20 participants (online or offline). If you are engaged in related technical research and industrial work, please fill in the application form truthfully, and the information will be used as a priority review basis . After passing the review, a confirmation notification will be sent by email 24 hours before the event.
