Speaker

Antonio Bicchi

Antonio Bicchi is Professor of Robotics at the University of Pisa, and Senior Scientist at the Italian Institute of Technology in Genoa. He graduated from the University of Bologna in 1988 and was a postdoc scholar at M.I.T.  Artificial Intelligence lab. He teaches  Robotics and Control Systems in the Department of Information Engineering  (DII) of the University of Pisa. He leads the Robotics Group at the  Research Center "E. Piaggio'' of the University of Pisa since 1990. He is the head of the SoftRobotics Lab for Human Cooperation and Rehabilitation at IIT in Genoa. Since 2013 he serves ad Adjunct Professor at the School of Biological and Health Systems Engineering of Arizona State University. 

From January, 2023, he is the Editor in Chief of the International Journal of Robotics Reserach (IJRR), the first scientific journal in Robotics. He has been the founding Editor-in-Chief of the IEEE Robotics and Automation Letters  (2015-2019), which rapidly became the top Robotics journal by number of submissions. He has organized the first WorldHaptics Conference (2005), today the premier conference in the field. He is a co-founder and President of the Italian Institute of Robotics and Intelligent Machines (I-RIM).

His main research interests are in Robotics, Haptics, and Control Systems. He has published more than 500 papers on international journals, books, and refereed conferences. His research on human and robot hands has been generoously supported by the European Research Council with an Advanced Grant in 2012, a Synergy Grant in 2019, and three Proof-of-Concept grants. He is the scientific coordinator of the JOiiNT Lab, an advanced tech transfer lab with leading-edge industries in Bergamo, Italy.

Speaker

Aude Billard

Aude Billard is full professor, head of the LASA laboratory and the Associate Dean for Education in School at the School of Engineering at the Swiss Institute of Technology Lausanne (EPFL). Prof Billard currently serves as the President of the IEEE Robotics and Automation Society, director of the ELLIS Robot Learning Program and co-director of the Robot Learning Foundation, a non-profit corporation that serves as the governing body behind the Conference on Robot Learning (CoRL), and leads the Innovation Booster Robotics, a program funding technology transfer in robotics and powered by the Swiss Innovation Agency, Innosuisse.

Prof Billard holds a BSc and MSc in Physics from EPFL and a PhD in Artificial Intelligence from the University of Edinburgh. Prof Billard is an IEEE Fellow and the recipient of numerous recognitions, among which the Intel Corporation Teaching award, the Swiss National Science Foundation career award, the Outstanding Young Person in Science and Innovation from the Swiss Chamber of Commerce, the IEEE RAS Distinguished Award, and the IEEE-RAS Best Reviewer Award. Dr. Billard was a plenary speaker at major robotics, AI and Control conferences (ICRA, AAAI, CoRL, HRI, CASE, ICDL, ECML, L4DC, IFAC Symposium, ROMAN, Humanoids and many others) and acted on various positions on the organization committee of numerous International Conferences in Robotics. Her research spans the fields of machine learning and robotics with a particular emphasis on fast and reactive control and on safe human-robot interaction. This research received numerous best conference paper awards, as well as the prestigious King-Sun Fu Memorial Award for the best IEEE Transaction in Robotics paper, and is regularly featured in premier venues (BBC, IEEE Spectrum, Wired).

Speaker

Oliver Brock

Oliver Brock is the Alexander-von-Humboldt Professor of Robotics in the School of Electrical Engineering and Computer Science at the Technische Universität Berlin, a German "University of Excellence". He received his Ph.D. from Stanford University in 2000 and held postdoctoral positions at Rice University and Stanford University.

He was an Assistant and Associate Professor in the Department of Computer Science at the University of Massachusetts Amherst before moving back to Berlin in 2009. The research of Brock's lab, the Robotics and Biology Laboratory, focuses on embodied intelligence, mobile manipulation, interactive perception, grasping, manipulation, soft material robotics, interactive machine learning, motion generation, and the application of algorithms and concepts from robotics to computational problems in structural molecular biology.

Oliver Brock directs the Research Center of Excellence "Science of Intelligence". He is an IEEE Fellow and was president of the Robotics: Science and Systems Foundation from 2012 until 2019. 

Speaker

Ankur Handa

Ankur Handa is currently a Principal Research Scientist at NVIDIA Robotics. Prior to that he was a Research Scientist at OpenAI and before that he was a Dyson Fellow at Imperial College London. He finished his PhD with Prof. Andrew Davison at Imperial College London and did a two year post-doc with Prof. Roberto Cipolla at the University of Cambridge. His papers have won Best Industry Paper Award at BMVC, 2014 and have been Best Manipulation Paper Award Finalist and Best Student Paper Award Finalist at ICRA 2019. 

His talk will focus on deep reinforcement learning (RL)  algorithms to learn complex robotic behaviours in simulation, including in the domain of multi-fingered manipulation. However, such models can be challenging to transfer to the real world due to the gap between simulation and reality. He will cover his past 5 years of efforts in dexterous manipulation from building teleop hand-arm systems to training large scale RL and tricks to transfer policies to the real world. 

Speaker

Josie Hughes

Josie Hughes is an Assistant Professor at EPFL where she established the CREATE Lab in the Institute of Mechanical Engineering in 2021. She undertook her undergraduate, masters and PhD studies at the University of Cambridge, joining the Bio-inspired Robotics Lab (BIRL).  Her PhD focused on examining the role of passivity in bio-inspired manipulators, and methodologies for exploiting morphology soft large area soft sensing.  Following this, she worked as a postdoctoral associate at the Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology in USA in the Distributed Robotics Lab.  Her research focuses on developing novel design paradigms for designing robot structures that exploit their physicality and interactions with the environment.  This includes the development of robotic hands, soft manipulators and automation systems for applications focused on sustainability and science.   She has a number of best paper awards and was awarded the IEEE RAS Early Career Award in 2024.

Speaker

Tengyu Liu

Tengyu Liu is a research scientist at the General Vision Lab of the Beijing Institute of General Artificial Intelligence (BIGAI). He obtained his PhD in computer science from UCLA in 2021 under the supervision of Prof. Song-Chun Zhu, following a master's degree in computer science from UCLA and a bachelor's degree in computer science from UIUC. His research interests lie at the intersection of 3D computer vision, computer graphics, and robotics, focusing on creating intelligent agents that can interact with virtual or physical environments in human-like ways. 

Dr. Liu's recent works include dexterous grasping, dexterous manipulation, humanoid robot control, and complex human-scene interactions. His research has been recognized with multiple highlights and oral presentations at top-tier conferences such as CVPR, ICCV, ICRA, and IROS. His work on DexGraspNet was selected as an Outstanding Paper Finalist (Manipulation) at ICRA 2023.

Speaker

Lerrel Pinto

Lerrel Pinto is an Assistant Professor of Computer Science at NYU Courant and part of the CILVR group. Before that, he was at UC Berkeley for a postdoc, at CMU Robotics Institute for a PhD, and at IIT Guwahati for undergrad. He run the General-purpose Robotics and AI Lab (GRAIL) with the goal of getting robots to generalize and adapt in the messy world we live in. His research focuses broadly on robot learning and decision making, with an emphasis on large-scale learning (both data and models), representation learning for sensory data, developing algorithms to model actions and behavior, reinforcement learning for adapting to new scenarios, and building open-sourced affordable robots. He has won the NSF CAREER award and the RAL Early Career award, and received the Packard Fellowship, and was named on the TR35 list.

Speaker

Shuran Song

Shuran Song is an Assistant Professor of Electrical Engineering, by courtesy of Computer Science at Stanford University. She leads the Robotics and Embodied AI Lab at Stanford University ( REAL@Stanford ). She is interested in developing algorithms that enable intelligent systems to learn from their interactions with the physical world, and autonomously acquire the perception and manipulation skills necessary to execute complex tasks and assist people.

She received the PhD in Computer Science from Princeton University and the Bachelor of Engineering from the Hong Kong University of Science and Technology (HKUST). Her research has been recognized by Best Paper Awards at RSS’22 and T-RO’20, Best System Paper Awards at CoRL’21 and RSS’19, and finalist awards at RSS, ICRA, CVPR, and IROS.  She is also a recipient of the NSF Career Award and the Sloan Foundation fellowship as well as research awards from Microsoft, Toyota Research, Google, Amazon, and JP Morgan.

Speaker

Xiaolong Wang

Xiaolong Wang is an Assistant Professor in the ECE department at the University of California, San Diego. He received his Ph.D. in Robotics at Carnegie Mellon University. His postdoctoral training was at the University of California, Berkeley. His research focuses on the intersection between computer vision and robotics. His specific interest lies in learning 3D and dynamics representations from videos and physical robotic interaction data. These comprehensive representations are utilized to facilitate the learning of human-like robot skills, with the goal of generalizing the robot to interact effectively with a wide range of objects and environments in the real physical world. He is the recipient of the NSF CAREER Award, Intel Rising Star Faculty Award, and Research Awards from Sony, Amazon, Adobe, and Cisco.