Michael A. Peshkin is a Professor of Mechanical Engineering at the Murphy Department of Mechanical and Industrial Engineering , Murphy Institute , and holds the Allen K. and Johnnie Cordell Breed Senior Professor in Design title. He is affiliated with the Master of Science in Robotics Program and the Segal Design Institute as their Engineering Education Lead (2021-). His work spans robotics, haptics, and voting accessibility research. Education: Ph.D. Physics, Carnegie Mellon University (1987) M.S. Experimental Solid State Physics, Cornell University (1982) B.A. Physics, University of Chicago (1979) Research interests focus on surface haptics (e.g., electroadhesion-based tactile feedback), collaborative robots (cobots) , and bioinspired electrosense . He also advocates for democracy through voting accessibility initiatives , studying how long polling lines disproportionately affect minority voters. His innovations include the TPaD haptic surface and spin-offs like Tanvas (2010) for tactile interfaces and Mako Surgical Corp (1995) for robotic surgery tools. Publications reflect a strong emphasis on haptic technologies and robotic safety. Notable trends include advancing electroadhesive surfaces, optimizing texture rendering, and exploring human-robot interaction dynamics. His work on cobots has addressed both industrial applications and healthcare rehabilitation. Scientific Awards: ASEE Ralph Coats Roe National Educator Award (2017) Fellow, National Academy of Inventors (2014) Charles Deering McCormick Professor of Teaching Excellence (2011–2014) Teaching contributions include pioneering Electronics Design and Engineering Analysis 3 , emphasizing hands-on learning via portable labs. He advises on mechatronics projects and co-founded companies like Cobotics and Kinea Design . His research teams collaborate across disciplines, integrating robotics with biosystems and educational outreach.
Carlo Ciliberto is an Associate Professor in Machine Learning at University College London. His research focuses on theoretical and applied machine learning, with particular emphasis on structured prediction, meta-learning, optimal transport, and quantum computing. He has contributed to advancements in kernel methods, reinforcement learning, and robotics perception systems, notably through work with humanoid robots like the iCub. Key research interests include: Developing algorithms for distribution regression and Wasserstein-based learning. Exploring meta-learning frameworks for few-shot and incremental learning tasks. Designing robust systems for robotics applications, such as object recognition and tactile sensing. Investigating statistical foundations of quantum machine learning. Notable contributions to the field include the Manifold Structured Prediction framework, Sliced Wasserstein Kernels for distribution regression, and methodologies for conditional meta-learning. His work bridges theory and practice, with applications ranging from civil infrastructure analysis to humanoid robot perception.
Ferdinando Mussa-Ivaldi is a Professor of Physiology, Physical Medicine & Rehabilitation, and Biomedical Engineering at Northwestern University's McCormick School of Engineering. He is affiliated with the Rehabilitation Institute of Chicago (RIC) and the Master of Science in Robotics Program. His research focuses on bi-directional brain-machine interfaces, assistive robotics, and sensory-motor learning mechanisms. Key projects include developing adaptive body-machine interfaces for spinal injury patients, studying neural plasticity in motor adaptation, and understanding temporal representation in the nervous system. Research interests span computational models of motor primitives, haptic perception under delays, and robotic rehabilitation tools. His work bridges neuroscience, robotics, and biomedical engineering to advance assistive technologies and neurorehabilitation. Notable contributions include studies on force control, internal models of limb dynamics, and the design of immersive virtual environments for training. Current affiliations include leadership roles in the Robotics Laboratory at RIC, where he investigates human-robot co-adaptation and clinical applications of body-machine interfaces. His interdisciplinary approach integrates clinical needs with advanced engineering solutions to enhance motor recovery and assistive device control.
Janet M. Weisenberger is a Professor in the Department of Speech and Hearing Science at The Ohio State University, within the College of Arts and Sciences. She joined Ohio State in 1991 after serving as a research scientist at the Central Institute for the Deaf at Washington University. After 23 years in university administration, including roles as Associate Dean for Research and Senior Associate Vice President for Research, she returned to teaching and research in 2022. Her work focuses on multimodal sensory integration, with applications in tactile aids for visual impairment, vibrotactile devices for speech perception, and cockpit haptics in aviation. Education: PhD in Psychology (Indiana University, 1981); BA in Psychology and Sociology (Edgecliff College, 1977) Her research explores how individuals integrate sensory inputs (vision, hearing, touch) to navigate environments. Current projects include leading the Ohio State University Driving Simulation Laboratory, studying driver-vehicle interactions, in-vehicle display design, and accessibility for special populations (e.g., older drivers, individuals with visual/hearing impairments). She teaches undergraduate courses in hearing anatomy, auditory perception, and research methods, and has supervised 50 undergraduate research theses. Dr. Weisenberger is a Fellow of the Acoustical Society of America and previously served as its Vice President. Her collaborations with automotive industry partners emphasize minimizing driver distraction and optimizing in-vehicle technologies for diverse user needs.
Md Jahidul Islam is the Yangbin Wang Rising Star Professor at the Department of Electrical & Computer Engineering , part of the College of Engineering at the University of Florida. His research focuses on underwater robotics, autonomous systems, and machine vision with applications in marine environments. Education: PhD in Robotics, University of Minnesota (2021) MSc in Artificial Intelligence, BUET (2015) BSc in Computer Science & Engineering, BUET (2012) Research Interests: His work spans robot perception , underwater robotics , and machine vision . He develops autonomous systems for underwater cave exploration, acoustic communication, and environmental monitoring. His RoboPI Lab advances technologies like semantic guidance for marine robots and edge-centric real-time processing for underwater scenes. Key innovations include CavePI for autonomous cave navigation and LightViz for distributed light pollution monitoring. Publications: Recent work emphasizes underwater data center acoustics, natural language-driven mission programming, and robust communication systems. His research bridges robotics, computer vision, and environmental science, often with practical deployments in marine surveillance and resource management. Awards: Doctoral Dissertation Fellowship (University of Minnesota, 2019–20) RAS Travel Grant (ICRA 2019) IEEE/RSJ Travel Grant (IROS 2017) ADC Graduate Fellowship (Wireless Tech, 2015–16) Advising & Labs: Leads the RoboPI Lab , focusing on underwater robotics and autonomous systems. His research is supported by grants in robotics, environmental monitoring, and edge computing. Collaborations span academia and industry to advance marine technology and AI-driven environmental solutions.
Alexander Amini is a Postdoctoral Researcher at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) , working under the guidance of Prof. Daniela Rus. He earned his PhD (2022), Master of Science (2018), and Bachelor of Science (2017) in Computer Science from MIT, with a minor in Mathematics. Amini co-founded Liquid AI and Themis AI , and serves as a lead organizer and lecturer for MIT's deep learning course 6.S191 . His research focuses on the science and engineering of autonomy , particularly for safe decision-making in uncertain environments. Key contributions include Developing end-to-end control systems for autonomous agents Formulating confidence metrics in neural networks Creating mathematical models for human mobility analysis Innovating inertial refinement systems Amini's publications reveal trends across autonomous vehicle control , robust machine learning , and uncertainty quantification . His work spans continuous-time neural models, sensor optimization for soft robotics, and applications in molecular discovery and financial modeling. Notable collaborations include projects with NVIDIA and Harvard Medical School. Scientific recognition includes 2011 EU Contest for Young Scientists Grand Prize 2011 BT Young Scientist overall winner 2017 NSF Graduate Fellowship 2020 MIT Outstanding Mentor Award 2021 JP Morgan Fellowship As part of MIT's Distributed Robotics Laboratory , Amini works on systems that combine robotics with everyday life applications, supported by grants from FinTech@CSAIL and MachineLearningApplications@CSAIL for bias mitigation in financial and clinical domains.
Lynette A Jones is a Senior Research Scientist in the Department of Mechanical Engineering at the Massachusetts Institute of Technology (MIT). She has been with MIT since 1994 and leads the Cutaneous Sensory Lab, which develops tactile, haptic, and thermal displays for diverse applications. Prior to MIT, she was a tenured Associate Professor in the Faculty of Medicine at McGill University. Education: B.A. in Psychology, University of Auckland, 1976 M.A. in Psychology, University of Auckland, 1978 Ph.D. in Psychology, McGill University, 1983 Research Interests: Dr. Jones specializes in haptic and tactile interface design, thermal display development, and skin mechanics. Her work bridges human-machine interaction, focusing on cutaneous communication systems and vibrotactile pattern recognition. She employs psychophysics, biomechanical modeling, and multisensory integration to advance wearable haptic technology. Key Article Trends: Her recent publications emphasize thermal and vibrotactile actuation methods, multisensory display integration, and MR fluid-based haptic devices. Themes include tactile perception, sensorimotor control, skin biomechanics, and applications in wearable technology and biomedical engineering. Scientific Awards: Meritorious Service Award, IEEE Transactions on Haptics, 2009 Fellow of the IEEE, 2018 IEEE Technical Committee on Haptics Distinguished Service Award, 2021 Professional Contributions: Dr. Jones has served as Editor-in-Chief of IEEE Transactions on Haptics (2014-2019), Chair of the IEEE Transactions on Haptics Management Committee (2023-present), and in multiple editorial and national committee roles. She is integral to MIT's Graduate Admissions and Postdoctoral Fellowship committees. Laboratory: The Cutaneous Sensory Lab at MIT employs a systems-level approach to haptic display development, including actuator characterization, skin mechanics analysis, and psychophysical user studies. The lab's work has been adopted in academic and industrial research on robotic swarms and soldier safety systems.
George A. Kantor is a Research Professor and Associate Director of Education at Carnegie Mellon University's Robotics Institute, based in the Collaborative Innovation Center (LL050). He leads the Kantor Lab and the AIIRA (AI Institute for Resilient Agriculture), focusing on controlling robotic systems with complex dynamics and state estimation through indirect measurements for applications in agriculture, underwater environments, and mining. His research spans agricultural robotics, field robotics, and control theory, emphasizing dynamics, kinematics, motion planning, and sensing/perception. Key areas include Robotics in Agriculture and Forestry, Underwater Robotics, Mining Robotics, and Sensing & Perception. He combines mathematical modeling with experimental validation to develop real-world solutions for balancing unstable robots and localizing autonomous vehicles in complex environments. Recent publications (2023-2025) reveal a dominant focus on agricultural robotics, featuring computer vision for crop monitoring, autonomous harvesting, and environmental sensing. Trends include transformer networks for fruit tracking, sim2real transfer techniques using Gaussian splatting, audio-visual contact classification, and LiDAR-based navigation in crop fields, demonstrating strong integration of deep learning with agricultural automation. No scientific awards were listed in the available information. Dr. Kantor actively mentors 4 current PhD students (Dominic Guri, John Kim, Mark Lee, Jenny Wang) and 2 master's students (Morgan Mayborne, Mohammad Nomaan Qureshi), with a track record of guiding 1 PhD graduate and over 20 master's graduates. His advising emphasizes agricultural robotics applications, reflected in student projects on robotic pruning, sensor calibration, and autonomous harvesting systems. He directs the Kantor Lab and contributes to AIIRA, developing systems like Bumblebee (autonomous vine pruning), Hefty (modular agricultural robot), and T-REX (vision-based leaf detection). Current work focuses on robotic manipulation in unstructured agricultural environments, sensor exchange for crop monitoring, and AI-driven solutions for resilient food systems.
Nicholas Roy is a Professor of Aeronautics and Astronautics at the Massachusetts Institute of Technology (MIT), serving as Undergraduate Committee Chair and Director of Engineering for the MIT Quest for Intelligence. He maintains primary affiliations with the Robust Robotics Group, Computer Science & Artificial Intelligence Lab (CSAIL), and MIT Schwarzman College of Computing. His academic credentials include: B.Sc., 1995, McGill University M.Sc., 1997, McGill University Ph.D., 2003, Carnegie Mellon University Professor Roy's research pioneers uncertainty-aware autonomy across robotics and AI domains. His work integrates machine learning with robust planning systems to enable operation in GPS-denied environments like forests and indoor spaces. Key innovations include evidential learning for traversability estimation, physics-informed trajectory optimization, and language-grounded multi-robot coordination. His group develops systems for micro air vehicles, contact-rich manipulation, and scientific expeditions requiring autonomous decision-making under partial observability. Analysis of his 2024-2025 publications reveals three dominant trends: (1) diffusion models for anomaly detection and traversability synthesis, (2) evidential deep learning for risk-aware off-road navigation, and (3) large language model integration for task and motion planning. These works consistently address real-world deployment challenges through uncertainty quantification and physics-based constraints. As an educator, Roy champions principles of autonomy and decision-making through courses on robotics science and real-time systems. His advising philosophy emphasizes student independence while maintaining active mentorship within the Robust Robotics Group. The Robust Robotics Group (RRG) focuses on practical autonomy for aerial and ground robots in unstructured environments. Current projects include multi-UAV forest canopy navigation, methane detection for scientific expeditions, and contact-rich manipulation systems leveraging force-guided exploration. RRG maintains strong ties with CSAIL's autonomous systems initiatives and the MIT Quest for Intelligence.
Dr. Suncica Hadzidedic is an Assistant Professor in the Department of Computer Science at Durham University and a Fellow of the Wolfson Research Institute for Health and Wellbeing. She holds a PhD from the University of Warwick, MSc from Binary University (Malaysia), and BSc from SSST (Bosnia and Herzegovina) and Buckingham University (UK). Her research bridges computer science with healthcare, psychology, and design, focusing on recommender systems, affective computing, and responsible AI applications in health and wellbeing. She leads projects like MoreLife UK KTP (Innovate UK-funded) and is part of research networks such as the EU COST Action VascAgeNet and the Alan Turing Institute’s Knowledge Graphs Interest Group. Her research interests include digital health interventions, mental health support systems, and ethical AI frameworks. Notable projects include developing PORT.org.ba, a cancer website with affect-aware recommendations, and studying authentication methods in youth populations. She teaches courses on recommender systems and business analytics. Dr. Hadzidedic’s work spans interdisciplinary collaborations, including the Erasmus+ e-VIVA project enhancing educational competencies in Balkan universities. She supervises postgraduate students in AI-driven health technologies and actively contributes to the AIHS (Artificial Intelligence and Human Systems) research group at Durham.
Jonathan Shemmell is a Senior Lecturer at the School of Medical, Indigenous and Health Sciences, University of Wollongong, since 2021. His research focuses on understanding and enhancing sensorimotor nervous system plasticity to improve movement and balance, particularly through the study of cortical and subcortical contributions. He leads the Neuromotor Adaptation Laboratory, equipped with advanced systems for 3D motion capture, neurophysiological recording, and nervous system stimulation. Additionally, he co-directs the Neuromechanics Hub, emphasizing interdisciplinary collaboration with clinicians and engineers. His teaching interests include human neuromechanics, sensorimotor control, and healthy aging. He coordinates the course MEDI258 and has taught MEDI330 and MEDI151. He currently supervises PhD students exploring neurophysiological correlates of balance control and supraspinal contributions to postural adjustments during movement. Dr. Shemmell has secured funding for projects such as the AI-assisted Obstacle Detection and Guidance System for Blind and Vision-Impaired People (2023-2024) and equipment grants for neurophysiological studies. His work bridges basic neuroscience with clinical applications, aiming to develop neuromodulation techniques for stroke rehabilitation and musculoskeletal disorders.
Dr. Mania Aikaterini is a Professor at the School of Electrical and Computer Engineering (ECE) of the Technical University of Crete. She specializes in Perception-based Computer Graphics, Virtual Reality, and Human-Computer Interaction. Her research focuses on 3D graphics, simulation engineering, and human factors in virtual environments. Education: B.Sc. in Mathematics, University of Crete (1994) M.Sc. in Advanced Computing (Global Computing and Multimedia), University of Bristol (1996) Ph.D. in Computer Science, University of Bristol (2001) Her career includes tenure as an Assistant Professor at the University of Sussex (UK) and research roles at Hewlett Packard Laboratories and NASA Ames Research Centre. She leads the SURREAL research team (http://surreal.tuc.gr) and contributes to the Distributed Multimedia Information Systems and Applications Laboratory. She has served as an Associate Editor for ACM Transactions on Applied Perception and Presence: Teleoperators and Virtual Environments. Teaching responsibilities include courses on Introduction to Computer Programming and Computer Graphics.
Peter Lennox is a Senior Lecturer in Performance at the University of Derby's School of Arts. His research explores spatial audio, multimodal perception, and embodied cognition through innovative sound technologies. Research focuses on tissue-conducted sound fields, perceptual augmentation, and spatial music composition. His work bridges auditory display, cognitive mapping, and sensory substitution for immersive experiences. Publications demonstrate strong emphasis on auditory-tactile integration, spatial sound perception, and creative pedagogy. Recent projects investigate sensory augmentation techniques for artistic expression and educational innovation. Achievements include Higher Education Academy Fellowship. His research has received international recognition in audio engineering and perceptual studies communities.
Sabarish V. Babu is a tenured full Professor in the Division of Human-Centered Computing within the School of Computing at Clemson University. He co-directs the virtual environments group where his research focuses on innovative design, implementation, and evaluation of immersive and interactive eXtended Reality (XR) systems. As a Senior Member of IEEE, Dr. Babu ranks number 1 in the US in VR research according to CSRankings.org, significantly contributing to placing Clemson University among top institutions in VR research. Dr. Babu's educational background includes: PhD in Computer Science from University of North Carolina at Charlotte (2007) MS in Information Technology from UNC-Charlotte (2002) BS in Biology with concentration in Microbiology from UNC-Charlotte (2000) Dr. Babu's research interests span the areas of XR (VR/AR/MR), Applied Perception-Action and Cognition in XR, Virtual Humans and Avatars, and 3D Human Computer Interaction. His work bridges theoretical foundations with practical applications across healthcare, education, and industrial domains. He has published over 140 peer-reviewed papers examining how humans interact with and perceive virtual environments, how virtual humans influence user behavior, and how XR technologies can solve real-world problems. His research methodology emphasizes rigorous empirical evaluation through user studies, often employing eye-tracking, behavioral analysis, and psychophysical measurements. Analysis of Dr. Babu's publication trends reveals a strong focus on perception-action coordination in virtual environments, with particular attention to how visual, auditory, and haptic cues affect user experience. His recent work has expanded into mental health applications of virtual agents, cybersickness mitigation, and the transfer of perceptual learning between virtual and real environments. The interdisciplinary nature of his research spans computer science, psychology, human factors, and healthcare applications. Dr. Babu's scientific achievements include: 8 Best Paper Awards at premier IEEE and ACM conferences (ACM Symposium on Applied Perception 2022, 2020, 2016; IEEE Virtual Reality Conference 2023, 2018; IEEE Symposium on 3D User Interfaces 2016, 2007; IEEE International Conference on Healthcare Informatics 2013) Best Presentation Awards at IEEE Virtual Reality Conference (2024) and ACM Symposium on Applied Perception (2021) Honorable Mentions for Best Paper at IEEE VR 2023 and ACM SAP 2020 Senior Member status in IEEE Ranking as #1 in VR research field in the US per CSRankings.org Dr. Babu has graduated 9 PhD students, 8 MS CS students, and several undergraduate honors students. His PhD graduates now serve as faculty members at Clemson University, University of Central Florida, UNC Wilmington, and Morehouse College, as well as in industry research positions at Meta Reality Labs, Microsoft Research, and other XR/CG/Visualization firms. His research has been supported by significant funding from the National Science Foundation, Department of Labor, and corporate foundations including Medline Inc., Prisma Health Inc., Bon Secours Inc., Adobe Inc., and BMW Inc. Dr. Babu has served in leadership roles including General Chair of the IEEE Virtual Reality Conference 2016, Program Chair of IEEE Virtual Reality Conference 2017, and upcoming ACM Symposium on Applied Perception 2025, and serves on the editorial boards of IEEE Transactions on Visualization and Computer Graphics and MDPI Virtual Worlds journals. Dr. Babu co-directs the virtual environments group at Clemson University, which maintains strong collaborations with healthcare institutions, educational organizations, and industry partners to develop practical applications of virtual reality technologies. Current research directions include healthcare education simulations, computational thinking education through VR, and advanced interaction techniques for near-field and distant object manipulation in virtual environments.
Prof. Johnell Brooks is a Professor in Automotive Engineering at Clemson University, with a clinical appointment in Prisma Health University Medical Center's Department of Medicine. Her research develops simulator-based rehabilitation tools and instrumented vehicle systems to extend safe driving independence for aging populations. As an IAHC Scholar, she directs labs at the Roger C. Peace Rehabilitation Hospital studying driver performance through simulated and on-road assessments. Research includes: Driving simulator applications for clinical assessment Instrumented vehicle technologies Rehabilitation protocols for aging drivers Objective performance metrics for mobility Her team utilizes driving simulators, instrumented vehicles (Toyota Avalon, Chevrolet Malibu), and a 'home lab' assessing daily living activities. Volunteer studies: (864) 283-7272.
