Haddadin was the founding and executive director of Europe’s largest center of robotics and machine intelligence, TUM’s Munich Institute of Robotics and Machine Intelligence (MIRMI). MIRMI became one of the world’s leading centers, ranked number one in robotics according to csrankings.org and number two by airankings.org.

Haddadin established himself as a foremost expert in robotics worldwide as professor and chair of robotics and systems intelligence at TUM. He is widely recognized for his pioneering work in tactile mechatronics, contact-aware robots, safety methodologies in human-robot interaction, and autonomous manipulation learning. His innovations range from manipulators and unmanned aerial vehicles to mobile systems, humanoids, intelligent prosthetics, and exoskeletons.

He holds degrees in electrical engineering, computer science, and technology management (TUM/LMU), earned his doctorate with high distinction from RWTH Aachen and became an IEEE fellow in 2024.

In-So Kweon received the BS and MS degrees in Mechanical Design and Production Engineering from Seoul National University, Seoul, Korea, in 1981 and 1983, respectively, and the PhD degree in Robotics from the Robotics Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania, in 1990. He worked for the Toshiba R&D Center, Japan, and joined the Department of Automation and Design Engineering, KAIST, Seoul, Korea, in 1992, where he is now a professor with the Department of Electrical Engineering. His research interests are sensor fusion, color modeling and analysis, visual tracking, and visual SLAM. He was the general chair for the Asian Conference on Computer Vision 2012 and he is on the editorial board of the International Journal of Computer Vision. He has been serving as a director for P3 DigiCar Center which is one of the National Core Research Center since 2010.

Michael Milford, FTSE, conducts interdisciplinary research at the intersection of robotics, neuroscience, and computer vision. He currently holds appointments as Australian Research Council Laureate Fellow, Director of the QUT Centre for Robotics, QUT Professor, Microsoft Research Faculty Fellow, and Fellow of the Australian Academy of Technology and Engineering. He has led or co-led projects totalling more than 56 million dollars in research and industry funding, receiving over 17,000 citations, and his work has culminated in numerous accolades, including six best paper awards (and ten finalists), the ATSE Batterham Medal, a joint outright Queensland Young Tall Poppy award, and was made a Microsoft Research Faculty Fellow, one of only three Australians ever to receive this recognition. From 2022 – 2027 he is leading a large research team combining bio-inspired and computer science-based approaches to provide a ubiquitous alternative to GPS that does not rely on satellites. Michael is also an educational entrepreneur: as founder of Math Thrills, he has produced engaging STEM education materials distributed to over 35 countries for more than 20 years. As a keen mentor, Michael works with individuals and groups, both locally at the individual, institute or university level across Australia, but also globally through his Hacking Academia initiative, and won the 2025 Outstanding Mentor of Researchers Eureka Prize.

Hae-Won Park is an Associate Professor in the Department of Mechanical Engineering at the Korea Advanced Institute of Science & Technology (KAIST) and serves as the director of its humanoid robot research center. He earned his Ph.D. from the University of Michigan in 2012, following master's and bachelor's degrees from Yonsei University. Prior to his tenure at KAIST, Park held roles as an Assistant Professor at the University of Illinois at Urbana-Champaign and as a research scientist and postdoctoral researcher at the Massachusetts Institute of Technology (MIT) Media Lab, where he contributed to social robotics projects aimed at children's language education. At KAIST, he leads the Dynamic Robot Control and Design Laboratory, concentrating his research on the control and design of dynamic robot systems, particularly legged locomotion, bio-inspired robots, model predictive control, reinforcement learning, and innovative robot mechanisms. His work has led to the development of agile climbing robots designed for navigating challenging environments. Professor Park's contributions to the field have been acknowledged with honors such as an Early Career Spotlight award at the 2021 Robotics Science & Systems conference, an editorial board membership for the IEEE/ASME Transactions on Mechatronics, and the ICRA DARwIn-OP Humanoids Application Challenge Winner award in 2013.

Aude Billard is full professor and the director of the LASA laboratory at the School of Engineering at the Swiss Institute of Technology Lausanne (EPFL). Prof Billard currently serves as the junior past 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), vice-president of the Swiss Robotics Association.
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).

Shuran Song is an Assistant Professor at Stanford University, leading the Robotics and Embodied AI Lab at Stanford University (REAL@Stanford). Before joining Stanford University, she was a faculty at Columbia University. Shuran received her Ph.D. in Computer Science at Princeton University, BEng. at HKUST.  Song’s research has been recognized through several awards, including the Best Paper Awards at RSS’22 and T-RO’20, Best System Paper Awards at CoRL’21, RSS’19, and finalists at RSS, ICRA, CVPR, and IROS.  She is also a recipient of the IEEE RAS Early Career Award, NSF Career Award, Sloan fellowship, MIT TR35, as well as research awards from Samsung, Microsoft, Toyota Research, Google, Amazon, and JP Morgan.

Steve Collins is an Associate Professor of Mechanical Engineering at Stanford University, where he teaches courses on design and robotics and directs the Stanford Biomechatronics Laboratory. His primary focus is to speed and systematize the design and prescription of prostheses and exoskeletons using versatile device emulator hardware and human-in-the-loop optimization algorithms (Zhang et al. 2017, Science). Another interest is efficient autonomous devices, such as highly energy-efficient walking robots (Collins et al. 2005, Science) and exoskeletons that use no energy yet reduce the metabolic energy cost of human walking (Collins et al. 2015, Nature).
Prof. Collins received his B.S. in Mechanical Engineering in 2002 from Cornell University, where he performed undergraduate research on passive dynamic walking robots. He received his Ph.D. in Mechanical Engineering in 2008 from the University of Michigan, where he performed research on the dynamics and control of human walking. He performed postdoctoral research on humanoid robots at T. U. Delft in the Netherlands. He was a professor of Mechanical Engineering and Robotics at Carnegie Mellon University for seven years. In 2017, he joined the faculty of Mechanical Engineering at Stanford University.
Prof. Collins is a member of the Scientific Board of Dynamic Walking and the Editorial Board of Science Robotics. He has received the Young Scientist Award from the American Society of Biomechanics, the Best Medical Devices Paper from the International Conference on Robotics and Automation, and the student-voted Professor of the Year in his department.

Prof. Dr. Lorenzo Masia (born 1977 in Rome) earned a Mechanical Engineering degree from Sapienza University of Rome (2003) and a PhD from the University of Padua (2007), then began his robotics career as a researcher at MIT’s Newman Lab for Biomechanics and Human Rehabilitation. He later served as Team Leader at the Italian Institute of Technology (Robotics, Brain and Cognitive Sciences), became Assistant Professor at Nanyang Technological University Singapore (2013–2018), and subsequently Associate Professor in Biodesign at the University of Twente. From 2019 to 2024, he was Full Professor of Biorobotics & Medical Technology at Heidelberg University, where he founded the ARIES Lab (Assistive Robotics and Interactive ExoSuits) at ZITI. Since 1 October 2024, he has been Professor of Intelligent BioRobotic Systems and Executive Director of the Munich Institute for Robotics and Machine Intelligence (MIRMI) at TUM; his internationally recognized work includes multiple major conference awards (including two IEEE Best Paper and three IEEE Best Student Paper Awards) and extensive editorial and leadership roles across top robotics and rehabilitation journals and IEEE RAS conferences, including serving as General Chair of IEEE RAS EMBS BIOROB 2024 in Heidelberg.

Hang Su is a Professor at the IBISC Laboratory, Université Paris-Saclay, Évry, France. His research advances robotics and embodied intelligence, with a focus on human–robot interaction and wearable/assistive systems that adapt to human intent and context. He develops learning- and optimization-based methods for multimodal sensing, activity understanding, and adaptive control to enable robust and intuitive human–robot interaction in wearable and assistive systems. He has authored 150+ peer-reviewed publications and received recognitions including the Andrew P. Sage Best Transactions Paper Award (IEEE THMS, 2021) and the Outstanding Interaction Paper Award (ICRA, 2022), and he has been listed among Stanford’s Top 2% Scientists (2021–2025). He contributes to the community through editorial and leadership roles, currently serving as co-Chair of the IEEE RAS Technical Committee on Neuro-Robotics Systems and an Advisory Board Member of the IEEE Telepresence Community.