Professor Sangbae Kim is the Jerry McAfee (1940) Professor in Engineering at the Massachusetts Institute of Technology (MIT), School of Engineering, Department of Mechanical Engineering. His research focuses on bio-inspired robotics, extracting principles from animal biomechanics to develop high-performance robotic systems. Education: B.S. from Yonsei University (2001), M.S. (2004) and Ph.D. (2008) from Stanford University. Research Interests: Bio-inspired Robotics, Robotic Actuators, Locomotion Dynamics, Composite Sensor Fabrication, and Minimally Invasive Surgical Robotics. His notable achievements include the MIT Cheetah robot capable of 13mph outdoor running and autonomous obstacle jumping, and Stickybot, a climbing robot featured in TIME's Best Inventions (2006). Recent publications emphasize soft robotics, energy-efficient legged locomotion, and bio-inspired actuator design. Kim has received prestigious awards including the NSF CAREER Award (2014), DARPA Young Faculty Award (2013), and Ruth and Joel Spira Award for Distinguished Teaching (2015). Scientific Awards: NSF CAREER (2014), DARPA YFA (2013), TIME Best Invention (2006), multiple best paper awards. Professional Service: Associate Editor roles, NSF review panels, and leadership in IEEE and ASME organizations.
Oya Celiktutan is a Reader (Associate Professor) at King’s College London in the Department of Engineering, leading the Social AI & Robotics (SAIR) Lab within the Centre for Robotics Research. She holds a BSc in Electronics Engineering from Uludag University, and an MSc and PhD in Electrical and Electronics Engineering from Bogazici University, Turkey. Her doctoral work included a visiting research period at the National Institute of Applied Sciences in Lyon, France. She has held postdoctoral positions at Queen Mary University London, the University of Cambridge, and Imperial College London before joining King’s College in 2018. Her research focuses on multimodal machine learning for autonomous agents, addressing challenges in human-robot interaction, social awareness, and navigation. Key areas include human behavior analysis, generative models, and continual learning. Her work is supported by EPSRC, The Royal Society, EU Horizon, and industry partners like Toyota and NVIDIA. Notable awards include the EPSRC New Investigator Award (2021) and a Best Paper Award at IEEE Ro-Man 2022. Dr. Celiktutan’s lab explores socially assistive robotics, extended reality systems, and ethical AI. Recent projects include the LISI initiative to enable robots to learn social interactions from human-human data and the CL-HRI project advancing continual learning in human-centric robotics. Her research has led to datasets like MHHRI and RICA, and collaborations with companies like SoftBank Robotics. She teaches modules on Sensing and Perception, and Sensors and Actuators, emphasizing practical applications in robotics and mechatronics. Current research interests span socially-aware navigation, algorithmic fairness, and multimodal data fusion for robotics in healthcare and urban environments.
Aaron M. Dollar is the Frederick W. Beinecke Professor of Mechanical Engineering at Yale University, affiliated with the Yale Grab Lab. His research focuses on robotics, mechatronics, robotic grasping, and prosthetics, emphasizing adaptive mechanisms and human-robot interaction. He holds a PhD from Harvard University (2008) and degrees from UMass Amherst. Key research areas include dexterous manipulation, underactuated mechanisms, and assistive devices. His work bridges theory and practical applications, with contributions to prosthetic hands, robotic hands, and modular robotics systems. Recipient of prestigious awards: TR35 Innovator (2010), NSF CAREER Award (2010), DARPA Young Faculty Award (2013), and Air Force Young Investigator Award (2011). Developed the Yale MyoAdapt Hand, a single-actuator prosthetic with high functionality. Pioneered methods in real-to-sim transfer, modular lattice printing, and energy-aware robotic exploration. His lab, the Yale Grab Lab, explores robotics, prosthetics, and human motion analysis. Recent projects include autonomous calibration systems (ARC-Calib) and low-cost robotic hardware (RB5 Explorer).
Zhenhong Li is a Lecturer in Robotics and Control at the University of Manchester, holding an EPSRC Fellowship in physical human-robot interaction. He earned his B.Eng. from Huazhong University of Science and Technology (2013), and M.Sc. and Ph.D. in Control Engineering from the University of Manchester (2014 and 2019). Before joining Manchester in 2023, he was a Research Fellow in Rehabilitation Robotics at the University of Leeds (2019–2023). His research focuses on control technologies for human-robot systems, with applications in healthcare and industry. Key areas include physical human-robot interaction for rehabilitation, brain-computer interfaces, and neuromusculoskeletal modeling. He leads the Neurorobotics Lab (NRL) at Manchester and collaborates with healthcare professionals, industries, and designers via EPSRC/STFC/Wellcome Trust funding. Notable achievements include the 2019 Best Paper Award for Unmanned Systems and the 2020 EPS International Academic Pump-priming Award. In 2025, he was elected as a Senior Member of the IEEE. He actively organizes conferences and special issues, including the 2025 IEEE UK Robotics Conference and a Frontiers special issue on intelligent rehabilitation technology. Dr. Li supervises PhD candidates in robotics and control, emphasizing interdisciplinary approaches to human-robot interaction. His lab develops cutting-edge technologies like assistive exoskeletons and adaptive control systems for healthcare and industrial applications.
James Tung is an Associate Professor at the University of Waterloo’s Faculty of Engineering, Department of Mechanical and Mechatronics Engineering. His research focuses on assistive technology, rehabilitation engineering, and mobility solutions for individuals with disabilities. He leads the Neural and Rehabilitation Engineering (NRE) Lab, which develops wearable sensors, robotics, and machine learning tools to enhance mobility and monitor motor rehabilitation. He teaches courses including BME 355 (Physiological Systems Modelling), BME 540 (Neural and Rehabilitation Engineering), and ME/MTE engineering modules. The lab collaborates with clinical and industry partners to translate research into practical solutions, addressing real-world mobility challenges and aging demographics. His research spans real-world gait analysis, fall risk assessment, and prosthetic design, with a focus on pediatric neurodevelopmental disorders and elderly mobility. The NRE Lab emphasizes interdisciplinary work, combining biomechanics, robotics, and data science to improve healthcare outcomes. Lab Alumni: Includes researchers like Robin Murdock (Myant Inc.), Andrew Hart, and Raj Senthilkumar, contributing to prosthetics and gait analysis. Partnerships: Engages clinical and industry stakeholders for knowledge translation and commercialization. Current projects include developing smart rollators, biofeedback prosthetics, and sensor-based assessment tools to address mobility limitations in aging populations and individuals with disabilities.
Giulia Giordano is a Full Professor in the Department of Industrial Engineering at the University of Trento, Italy, where she leads the Dynamical Networks and Systems Biology research group. She also holds a dual appointment as Visiting Professor and Delft Technology Fellow at the Delft Center for Systems and Control, Delft University of Technology, The Netherlands. Her career includes previous positions as Assistant Professor at Delft University of Technology (2017-2019), Postdoctoral Research Fellow at Lund University, Sweden (2016-2017), and Research Fellow at the University of Udine, Italy (2016). Giulia earned her Ph.D. in Industrial and Information Engineering: Automation (Excellent) from the University of Udine with a thesis titled "Structural Analysis and Control of Dynamical Networks." She completed her M.Sc. and B.Sc. in Electrical Engineering (both Summa cum laude) at the same institution. She also undertook research visits at Caltech (2012) as a SURF Fellow and at the University of Stuttgart (2015) as a DAAD Research Scholar. Her primary research focuses on the analysis and control of dynamical networks with applications in systems biology, mathematical ecology, and mathematical epidemiology. She develops mathematical frameworks that bridge control theory, network theory, and dynamical systems to address complex problems in biological systems. Her recent work spans epidemic modeling, opinion dynamics, biochemical networks, and neurological disorders, with a particular emphasis on structural analysis of networked systems. She employs both theoretical and computational approaches to understand system behavior under uncertainty. Giulia's publications reveal a strong interdisciplinary focus, spanning from theoretical control systems to practical applications in epidemiology and biology. Her recent work shows increasing emphasis on epidemic modeling (particularly related to mpox and SARS-CoV-2), network synchronization, and the application of control theory to biological phenomena like fibromyalgia pathogenesis and opinion formation. Many of her papers appear in top-tier control journals including Automatica and IEEE Transactions on Automatic Control. 2024: Outstanding Service as Associate Editor of IEEE Control Systems Letters 2021: SIAM Activity Group on Control and Systems Theory Prize 2020: Outstanding Reviewer, Annals of Internal Medicine 2017: NAHS Best Paper Prize and EECI PhD Award 2016: Outstanding TAC Reviewer, IEEE Transactions on Automatic Control Giulia actively mentors students and postdoctoral researchers, currently supervising five postdoctoral researchers and two Ph.D. students at the University of Trento. She has advised numerous M.Sc. and B.Sc. students on topics ranging from bio-inspired modeling to optimal control of epidemic systems. Her research is supported by competitive grants including the ERC Starting Grant INSPIRE (Integrated Structural and Probabilistic Approaches for Biological and Epidemiological Systems). She serves as Associate Editor for IEEE Control Systems Letters and Automatica, and is a Senior Member of IEEE and the Control Systems Society. Giulia leads the Dynamical Networks and Systems Biology research group at the University of Trento, which maintains strong international collaborations across Europe and North America. The group's work combines theoretical advances in control theory with practical applications to pressing problems in public health and biological systems, demonstrating the power of mathematical approaches to understanding complex phenomena in the life sciences.
Daniel E. Koditschek is the Alfred Fitler Moore Professor in the Department of Computer and Information Science at the University of Pennsylvania’s School of Engineering and Applied Science. He also holds primary appointments in the Department of Electrical and Systems Engineering and a research affiliation with the Department of Mechanical Engineering and Applied Mechanics. He is a leading figure in the GRASP Lab, where he leads the Kod*lab, a specialized group focused on physical interaction and locomotion in autonomous robots. His research lies at the intersection of dynamical systems theory and robotics, emphasizing legged locomotion, hybrid control systems, and bio-inspired design. Koditschek's work integrates formal mathematical modeling with empirical testing of physical robots that run, jump, climb, and manipulate objects. He actively explores how biological insights into animal mobility can inform robotic autonomy and control. His group maintains strong collaborations with biologists and emphasizes embodied intelligence in machine behavior. The recent publications reflect a strong trend in applying theoretical control frameworks—such as hybrid dynamical systems, averaging methods, and navigation functions—to practical robotic challenges in unstructured environments. Topics include terrain adaptation, energy-efficient locomotion, reactive planning, and affordance-based interaction. There is a clear focus on bridging abstract mathematical models with real-world robotic performance, particularly in legged and mobile manipulation systems. IEEE RAS Pioneer Award Heilmeier Research Award AFOSR MURI Award (2010) Daniel Koditschek has advised numerous PhD students and postdoctoral researchers, many of whom now hold faculty positions or leadership roles in robotics companies like Ghost Robotics and Boston Dynamics. His research is supported by major grants from the NSF and AFOSR, including the MURI award and REU/RET programs that engage K-12 and undergraduate educators. He has also been involved in international outreach, including activities at the Penn Wharton China Center. Koditschek leads the Kod*lab within the GRASP Lab’s PERCH facility, which houses advanced legged robots such as the Ghost Minitaur, XRHhex, Inu, Delta Hopper, and Jerboa platforms. The lab emphasizes experimental validation of control theories using custom hardware and real-world terrain challenges.
Jeff Shamma is the Department Head and Professor of Industrial and Enterprise Systems Engineering (ISE) at the University of Illinois at Urbana-Champaign, holding the Jerry S. Dobrovolny Chair. He is also courtesy Professor in Aerospace Engineering and Mechanical Science and Engineering. Formerly, he held the Julian T. Hightower Chair at Georgia Institute of Technology and faculty positions at KAUST. Dr. Shamma earned his PhD in Systems Science and Engineering from MIT (1988) and a BS in Mechanical Engineering from Georgia Tech (1983). He is a Fellow of IEEE and IFAC, recipient of the IFAC High Impact Paper Award, AACC Donald P. Eckman Award, and NSF Young Investigator Award. His research spans Decision and Control , Game Theory , and Multi-Agent Systems , focusing on human-machine networks, distributed autonomy, and adaptive robotic systems. Recent work examines crowd dynamics, risk-sensitive control, and feedback linearization for constrained optimization. Jeff has served as Editor-in-Chief of IEEE Transactions on Control of Network Systems (2020–2024) and held editorial roles in journals like Annual Reviews in Control and IEEE Transactions on Robotics . His 15 most recent publications (2024–2025) analyze learning dynamics, multi-agent optimization, and UAV-crawler systems, reflecting trends in autonomous systems, game-theoretic modeling, and industrial inspection technologies. Scientific distinctions include: Fellow of IEEE and IFAC IFAC High Impact Paper Award (2020) AACC Donald P. Eckman Award (1996) NSF Young Investigator Award (1992) Mohammed Dahleh Distinguished Lecture Award (2013) Dr. Shamma advises current PhD students Hassan Abdelraouf, Aya Hamed, and Nawaf Otaibi, with former advisees including Sarah Toonsi (2025) and Fat-hy Rajab (2025). His lab integrates theoretical research with applied projects like FalconScan, a UAV-crawler system for industrial inspection, and develops magnetic legs for curved surface UAV landing.
Quan Zhou is a Professor leading the Robotic Instruments Group at the Department of Electrical Engineering and Automation, School of Electrical Engineering, Aalto University, Finland. He holds an M.Sc. in Control Engineering and a Dr.Tech. in Automation Technology from Tampere University of Technology. His research focuses on miniaturized robotics, robotic manipulation using contact, acoustic, magnetic, interfacial, and fluidic methods, integrating physics, mechatronics, and machine learning to address challenges in dexterous manipulation with applications in biomedicine, materials science, and industrial technologies. He directs the Master’s Programme in Automation and Electrical Engineering (AEE) at Aalto and coordinates the European Robotics Association’s Topic Group on Miniaturized Robotics. He has led the EU FP7 project FAB2ASM and chaired international conferences like MARSS 2019. Notably, he received the 2018 Anton Paar Research Award for Instrumental Analytics and Characterization. His research spans fundamental methodologies and practical applications, emphasizing interdisciplinary innovation. Recent work includes advancements in fluid-driven manipulation, biomimetic robotics, and acoustic particle control. His contributions bridge theoretical frameworks and real-world automation solutions, with publications in journals like Advanced Intelligent Systems , Nature , and Physical Review E . Prof. Zhou’s leadership roles include coordinating the EIT Digital Master's Programme in Autonomous Systems and chairing IEEE Finland robotics chapters. His work has been recognized through grants and awards, reflecting his impact on robotics and automation research and education.
Dr. Leila Notash is a Professor in the Department of Mechanical and Materials Engineering at Queen's University, where she has been a faculty member since 1997. She is a Fellow of Engineers Canada (FEC) and a licensed Professional Engineer with Professional Engineers Ontario (PEO), with significant contributions to engineering education and professional service. Her educational background includes: Bachelor of Science in Mechanical Engineering, Middle East Technical University (Ankara, Turkey) - High Honor Student (2nd out of 166) Master of Applied Science in Mechanical Engineering, University of Toronto PhD in Mechanical Engineering, University of Victoria Dr. Notash's research centers on robotics and mechatronics, with specialized expertise in cable-driven parallel manipulators. Her work integrates kinematics, fault-tolerant design, and neural network applications to address challenges in robot calibration, workspace analysis, and motion control under real-world constraints like cable mass and elasticity. She investigates both theoretical frameworks and practical implementations for industrial and specialized robotic systems. Analysis of her recent publications (2020-2024) reveals a clear trajectory toward intelligent control systems, where machine learning techniques—particularly neural networks and reinforcement learning—are increasingly applied to solve complex problems in cable-driven robotics. This includes motion control optimization, path generation, and kineto-static analysis while accounting for physical limitations such as cable elasticity and mass effects, demonstrating a shift from traditional mechanical analysis to data-driven adaptive control methodologies. Her scientific recognition includes: Fellow of Engineers Canada (FEC) University of Toronto Open Fellowship University of Toronto International Differential Fee Waiver Charles S. Humphrey Graduate Student Award NSERC Doctoral Prize Nominee (1996) Dr. Notash has mentored 161 undergraduate students as Faculty Advisor for the Mechanical '06 cohort and pioneered international educational initiatives like the International Undergraduate Student Design project (IVDS), connecting Queen's University with Middle East Technical University and Union College. Her service extends to editorial leadership for Mechanism and Machine Theory and ASME journals, and governance roles including Faculty Senator at Queen's University (2009-2025) and PEO Council Councillor-at-Large (2019-2025). She has established collaborative research networks through initiatives like the Reading Week shop course 'Design Basics 1.0' and sustained leadership in the Canadian Committee for the Promotion of Mechanism and Machine Science (CCToMM) and the International Federation for the Promotion of Mechanism and Machine Science (IFToMM), where she chaired the Permanent Commission on Communications (2006-2011).
George T. C. Chiu is a Professor in the School of Mechanical Engineering at Purdue University, with courtesy appointments in Electrical and Computer Engineering and Psychological Sciences. He holds a 50% appointment as Assistant Dean for Global Engineering Programs and Partnerships. His research focuses on mechatronics, dynamic systems and control, functional printing, and human-machine interaction, with applications in biomedical engineering, robotics, and advanced manufacturing. Education: PhD (1994), MS (1990) University of California, Berkeley; BS (1985) National Taiwan University. Research interests emphasize application-driven solutions for printing technologies, motion control, and embedded systems. Notable projects include developing inkjet printing for biomedical materials and sensor systems. Awards include ASME Fellowship (2013) and the 2024 ASME Rabins Leadership Award. Publications span topics like inkjet drop dynamics, control systems, and biofabrication. He has led initiatives such as the Purdue FIRST Programs, fostering K-12 STEM education through robotics mentorship. Editorial roles include Editor-in-Chief of IEEE/ASME Transactions on Mechatronics (2017-2019).
Professor Khac Duc Do is a faculty member at Curtin University, holding a position in the School of Civil and Mechanical Engineering within the Faculty of Science and Engineering. He serves in the Office of the Provost and is based at Curtin Perth campus. His research focuses on advanced control systems, nonlinear dynamics, and robotics applications in marine, aerospace, and mechanical systems. He earned a PhD with distinction in 2003 and has held prestigious fellowships including ARC Postdoctoral Fellow (2004) and ARC Australian Research Fellow (2009). His teaching includes courses like Advanced Control and Mechatronics, Navigation and Marine Control Systems, and Advanced Control Engineering. Key research interests encompass control of nonlinear systems, stochastic systems, formation control of mobile agents, fluid-structure interaction, and boundary control of PDE-governed systems. His funded projects include wave-energy converter development (2023-2026), inerter-based damper research (2019-2021), and ocean vehicle control systems. Scientific awards include ARC grants totaling over AUD 2 million. Current opportunities include scholarships in control systems/fluid-structure interaction and a postdoc position in wave-energy conversion.
Dr. Prabhakar Pagilla is the Associate Department Head and a Professor in the Department of Mechanical Engineering at Texas A&M University. He holds the James J. Cain Professor II title and leads the Robotics and Control Engineering Group. His research focuses on advanced control systems for robotics and roll-to-roll manufacturing, with emphasis on nonlinear dynamics, autonomous systems, and mechatronics. Education: Ph.D., Mechanical Engineering, University of California, Berkeley (1996) M.S., Mechanical Engineering, University of California, Berkeley (1994) B.E., Mechanical Engineering, Osmania University (1990) Research Interests: Modeling and control of roll-to-roll manufacturing systems Autonomous vehicles and cooperative adaptive cruise control Robotics/mechatronics, including workpiece localization and human-robot collaboration Control of large-scale nonlinear dynamic systems Recent Trends in Publications: Dr. Pagilla’s recent work emphasizes safety and efficiency in autonomous systems, including platooning strategies, V2V communication impacts, and exoskeleton ergonomics. His robotics research explores real-time path planning, shared control mechanisms, and anomaly detection in manufacturing processes. Awards: Fellow of ASME (2011) John J. Shelton Best Paper Award (2017, 2019) Regents Distinguished Research Award (2012) Lab/Teams: The Robotics and Control Engineering Group at Texas A&M focuses on interdisciplinary projects combining advanced control theory with practical applications in robotics and manufacturing. Current initiatives include surface finishing of curved geometries and predictive intent modeling for human-robot collaboration.
Christoforos Mavrogiannis is an Assistant Professor of Robotics at the University of Michigan, leading the Fluent Robotics Lab within the Department of Robotics. He holds a Ph.D. and M.S. from Cornell University and a Diploma in Mechanical Engineering from the National Technical University of Athens. His research focuses on enabling robots to seamlessly integrate into dynamic, unstructured environments through advancements in human-robot interaction, shared autonomy, multiagent systems, and navigation algorithms. Education: Ph.D. and M.S., Cornell University Diploma in Mechanical Engineering, National Technical University of Athens Research Interests: His work spans human-robot interaction , shared autonomy , and multiagent systems . He develops algorithms for navigating dynamic environments , decentralized control , and behavior prediction , with applications in robotic manipulation and collaborative transport . Recent projects include the HOUND off-road robot and pixel-art generation with mobile robots. Awards: Best paper award at the RSS Social Navigation Workshop (2024) Grants & Advising: He advises the Fluent Robotics Lab and contributes to organizing conferences like ICRA and HRI. His lab focuses on human-centered robotics and socially competent navigation . Labs & Teams: Fluent Robotics Lab at the University of Michigan, collaborating on projects like the HOUND platform and electrostatic brake systems for manipulation.
Akio Kodaira is affiliated with the Institute of Science Tokyo as a researcher. His work focuses on soft robotics, mechatronics, and advanced actuator design using materials like IPMC (Ionic Polymer-Metal Composites) and flexible fuel cells. Primary institution: Institute of Science Tokyo Research Interests Kodaira's research spans the development of soft robots, thin-film actuators, and bio-inspired mechanical systems. Key areas include IPMC fabrication techniques, energy-efficient actuators using Au/Pt electrodes, and 3D crafts using paper/fabric materials. Publication Trends Recent publications emphasize soft robotics, material hybridization (e.g., paper/fabric-assisted IPMC), and flexible fuel cell applications. His collaborations with researchers like Koichi Suzumori and Hiroyuki Nabae highlight interdisciplinary efforts in mechatronics and mechanical engineering. Collaborations Frequent co-authors include Koichi Suzumori (Professor, Institute of Science Tokyo), Kinji Asaka , and Hiroyuki Nabae . Projects involve thin-film robotics, McKibben muscles, and simulator-based navigation software.
