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Shoudong HuangView profile

Professor

• Mobile robot navigation
• Simultaneous localization and mapping (SLAM)
• Underwater robotics
• +4 more

Shoudong Huang is a Professor at the School of Mechanical and Mechatronic Engineering , University of Technology Sydney, and Deputy Director of the UTS Robotics Institute. His research focuses on mobile robot navigation , SLAM , nonlinear state estimation , and surgical robotics . He has published over 200 papers and is recognized as one of the 100 Most Influential Scholars in Robotics (Aminer, 2018). PhD in Automatic Control, Northeastern University (China) Postdoctoral Research Fellow, University of Hong Kong (1998-2000) Research Fellow, Australian National University (2001-2003) Full-time academic roles at UTS since 2004 His work addresses challenges in robot localization across extreme environments (underwater, underground mining, surgical settings) and develops globally optimal SLAM algorithms with guaranteed performance. He has secured over $4 million AUD in external funding, including ARC Discovery grants and industry partnerships. Recent publications emphasize cross-modal calibration (camera-LiDAR), interval analysis for bounded noise , and template-based deformable surface reconstruction . These span applications in autonomous driving, surgical navigation, and UAV guidance. Chancellor’s Medal for Research Excellence (2020) Supervisor of the Year (2023) Best Paper Award (2016 ICARCV) Huang serves as Associate Editor for IEEE Transactions on Robotics and International Journal of Robotics Research , and has held leadership roles in top robotics conferences like IROS and RSS. His collaborations span MIT, USC, Zhejiang University, and industry partners including PMSW Research Pty Ltd and Multiplex Constructions Pty Ltd.

Ajmal MianView profile

Professor

• Artificial Intelligence
• Computer Vision
• Machine Learning
• +8 more

Ajmal Mian is a Professor of Computer Science at the University of Western Australia (UWA), affiliated with the School of Physics, Maths and Computing. He holds an Australian Research Council Future Fellowship (2022) and leads research in Artificial Intelligence, Computer Vision, and Machine Learning. His work focuses on 3D computer vision, adversarial AI defense, and explainable AI. His research interests include 3D point cloud analysis, face recognition, human action recognition, and remote sensing. He has published over 300 papers and secured major grants from ARC, NHMRC, and DARPA, totaling millions in funding. He has supervised 29 PhD students and mentored 12 postdoctoral researchers. Key projects include 3D diffusion models for scene generation, robust 3D vision systems, and defense against AI deception attacks. He serves as a fellow of IAPR, an ACM Distinguished Speaker, and has editorial roles at IEEE Transactions on Neural Networks and Pattern Recognition. Research Awards: HBF Mid-Career Scientist of the Year, West Australian Early Career Scientist of the Year, IAPR Best Scientific Paper Award. Grants: ARC Discovery Projects, National Intelligence & Security Discovery grants, DARPA grants for AI security. His teaching spans computer vision, machine learning, and programming courses. Collaborations include defense, medical, and agricultural applications.

• Neural Interfaces
• Micro/Nano Electro Mechanical Systems (MEMS)
• Biosystems & Computational Biology
• +3 more

Michel M. Maharbiz is a Professor in the Department of Electrical Engineering and Computer Science at the University of California, Berkeley. He leads research on miniaturized bioelectronic interfaces, including neural dust implants and cyborg insects. He holds affiliations with the Berkeley Sensor & Actuator Center (BSAC), Center for Neural Engineering & Prostheses (CNEP), and SWARM Lab. His education includes a Ph.D. in EECS from UC Berkeley (2003) and a B.S. in EE from Cornell University (1997). Maharbiz's research integrates MEMS, ultrasonic systems, and synthetic biology to develop wireless neural interfaces, implantable sensors, and biohybrid devices. Key focus areas are neural dust technology for peripheral nerve recording, magnetoelastic strain sensors for medical applications, and electrochemical biosensing using bacterial flagellar motors. His publications emphasize neural interfaces, ultrasonic implants, and biomedical monitoring. Recent articles explore ultrasonic power delivery (2025), radiation detectors for oncology (2025), and fracture-healing smart plates (2019). Trends include miniaturization of wireless implants, closed-loop therapeutic systems, and novel biomaterials. Scientific Awards: McKnight Technological Innovations in Neuroscience Award (2017) Chan-Zuckerberg Biohub Investigator (2017) NSF CAREER Award (2009) MIT TR10 Top Emerging Technology (2009) Bakar Fellows Spark Award (2012) He directs the Maharbiz Lab, advancing neural dust and bioelectronic interfaces. Projects include impedance-based fracture monitoring, carbon fiber neural arrays, and hernia repair sensors. Funding includes NSF and industry partnerships for implantable device development.

Pieter AbbeelView profile

Professor

• Artificial Intelligence (AI)
• Robotics
• Machine Learning
• +5 more

Pieter Abbeel is a Professor in the Department of Electrical Engineering and Computer Sciences (EECS) at the University of California, Berkeley. He leads the Berkeley Robot Learning Lab and co-directs the Berkeley Artificial Intelligence Research (BAIR) Lab. His work focuses on advancing AI and robotics through deep reinforcement learning, imitation learning, and unsupervised learning, with applications in automation, healthcare, and education. Abbeel's research also explores the societal implications of AI and its potential to revolutionize other scientific and engineering fields. Education: Ph.D. in Computer Science, Stanford University (2008) M.S. in Electrical Engineering, KU Leuven, Belgium (2000) Research Interests: Robotics, AI, Machine Learning, Reinforcement Learning, Autonomous Systems, and Applications in Surgery, Manufacturing, and Education. Recent Article Trends: Focus on multimodal learning, robot manipulation, protein structure prediction, and scalable AI systems. Key areas include sim-to-real transfer, embodied AI, and foundation models for decision-making. Awards & Honors: IEEE Kiyo Tomiyasu Award (2022) ACM Prize in Computing (2021) IEEE Fellow (2018) MIT Tech Review TR35 (2011) Advising & Grants: Advises startups and has received grants from NSF, DARPA, and industry partnerships. Notable students include those advancing robotics, reinforcement learning, and bioAI. Labs & Initiatives: Berkeley Robot Learning Lab, BAIR Lab, and collaborations with the Center for Human-Compatible AI (CHAI). Founded companies include Gradescope, Covariant, and Berkeley Open Arms.

Animesh GargView profile

Assistant Professor

• Robotics
• Reinforcement Learning
• Artificial Intelligence
• +3 more

Animesh Garg is an Assistant Professor at the School of Interactive Computing at Georgia Tech, where he leads the People, AI, and Robotics (PAIR) research group . He holds a Senior Researcher position at Nvidia Research and has courtesy appointments at the University of Toronto and Vector Institute. Previously, he served as Chief Scientific Officer at Apptronik (2024-2025) and Senior Staff Research Scientist at Nvidia Research (2018-2024). Education : Ph.D. in Operations Research from UC Berkeley (2011-2016), MS in Computer Science and Industrial Engineering from Georgia Tech and University of Delhi. Research Focus : Building Generalizable Autonomy through Reinforcement Learning , Control Theory , and 3D Vision , with applications in Surgical Robotics , Self-Driving Labs , and Manufacturing . Key Article Themes : His recent work emphasizes Foundation Models for robotics, Differentiable Simulation , Language-Guided Autonomy , and Structured Inductive Biases in sequential decision-making. Scientific Awards : Stephen Fleming Early Career Professorship at Georgia Tech. Teaching : Courses on AI, Deep Reinforcement Learning, and Algorithmic Intelligence in Robotics at Georgia Tech. Labs & Collaborations : Affiliated with Institute for Robotics and Intelligent Machines (IRIM) and ML@GT at Georgia Tech; collaborates intensively with Nvidia Robotics.

Jindong TanView profile

Professor

• Medical Robotics
• Surgical Robotics
• Human-Robot Interactions
• +3 more

Jindong Tan is a Professor in the Department of Mechanical, Aerospace, and Biomedical Engineering at the University of Tennessee, Knoxville (since 2015). Previously, he held roles at Michigan Technological University (2002–2015) and Northeastern University, China (1995–1998). He specializes in medical/surgical robotics, human-robot interactions, wearable sensors, control systems, and mechatronics. His research integrates robotics, biomedical engineering, and computer science to advance minimally invasive surgical tools, wearable technology, and autonomous systems. Education: Ph.D. in Mechanical Engineering from Michigan State University (2002), M.S. from Northeastern University (1995), and B.S. from Lanzhou University of Technology (1992). Research interests focus on developing innovative medical robotic systems, including laparoscopic camera robots, magnetic actuation mechanisms, and human-robot collaboration frameworks. He has contributed to advancements in wearable sensors for healthcare, sensor networks for dynamic environments, and calibration techniques for bio-inspired robots. Key projects include the design of an untethered laparoscopic camera robot (s-CAM), magnetic localization for surgical tools, and frameworks for controlled robot language in human-robot collaboration. His work emphasizes practical applications in surgical environments and wearable health monitoring. Professional service includes roles with the IEEE Robotics & Automation Society, Engineering in Medicine and Biology Society, and the Association for Computing Machinery. Contact: tan@utk.edu, Perkins Hall 315.

• Supply Chain Management
• Transportation Systems
• Logistics
• +4 more

Dr. Jérôme Verny is an Associate Professor specializing in transport, logistics, and supply chain management. He is the founder and director of the research institute in innovative transport and logistics, as well as the co-founder of the DISC Master's program (Digital & Innovative Supply Chain) in Paris and the Mobility Accelerator. His expertise spans digitalization in logistics, blockchain applications, and sustainable development. Educated at the University of Lille Nord de France (PhD in Economics and Management) and engineering schools like École Nationale des Ponts et Chaussées, he advises both public institutions (OECD, EU) and private enterprises on transportation strategies. Research Interests: Dr. Verny focuses on supply chain innovation, digital transformation, and strategic logistics. His work integrates blockchain technology for supply chain transparency, optimizes last-mile delivery in urban environments, and analyzes the impact of geopolitical actors like China on global trade networks. He also explores sustainable practices in transportation, including CO2 reduction strategies and pandemic response logistics. Awards: Recipient of the 2009 OECD-FIT Young Researcher Prize in Transport. His contributions bridge academic research with practical applications in industry, policy, and international trade. Key Activities: Co-founded the DISC Master’s program and leads research initiatives on blockchain adoption, Arctic shipping routes, and Mediterranean trade dynamics. He actively contributes to conferences such as the International Association of Maritime Economists (IAME) and publishes in journals like Structural Change and Economic Dynamics and International Journal of Shipping and Transport Logistics . Labs/Teams: Directs the Institut de Recherche en Transport et Logistique Innovante and collaborates with institutions like the OECD and European Commission on transport policy. His interdisciplinary approach involves engineering, economics, and data science to address global supply chain challenges.

Frank L. Hammond IIIView profile

Assistant Professor

• Adaptive Robotic Manipulation
• Soft Robotics
• Wearable Robotics
• +5 more

Frank L. Hammond III serves as Assistant Professor at Georgia Tech's Woodruff School of Mechanical Engineering since April 2015, directing the Adaptation Robotic Manipulation (ARM) Laboratory. A Carnegie Mellon PhD graduate, he previously held postdoctoral positions at MIT and Harvard as a Ford Fellow. His interdisciplinary work bridges mechanical engineering, biomedical applications, and computational design. Education Ph.D. in Mechanical Engineering, Carnegie Mellon University M.S. in Mechanical Engineering, University of Pennsylvania M.S. in Electrical Engineering, University of Pennsylvania B.S. in Electrical Engineering & Biomedical Engineering, Drexel University Hammond's research pioneers adaptive robotic manipulation (ARM) systems that operate in unstructured human environments through bioinspired computational design. His lab develops xenomorphic (non-biomorphic) robots using soft pneumatic actuation, flexible electronics, and machine learning to achieve biological-level versatility. Key application domains include wearable human augmentation devices , haptic-enabled surgical teleoperation , and autonomous soft platforms for medical and industrial use. The ARM methodology integrates empirical biomechanics characterization with simulation-driven optimization and rapid prototyping. Analysis of his 15 most recent publications (2023-2025) reveals three dominant trends: (1) Medical rehabilitation breakthroughs through intention-driven exoskeletons with soft bioelectronics, (2) Novel locomotion strategies for soft robots in complex environments (sand, water, cluttered spaces), and (3) Advanced haptic feedback systems leveraging multimodal sensory substitution for proprioceptive restoration. These works consistently bridge biomechanics, control theory, and human factors. Awards Ford Postdoctoral Research Fellowship at Harvard School of Engineering Hammond actively mentors graduate researchers including PhD candidates Lucas Tiziani (soft actuators) and Bangyuan Liu (earthworm robotics), and Master's student Alex Hart (pediatric haptics). His lab secures research funding for projects like tunable mechanical interfaces for neuropathy treatment and cognition-focused wearable devices, with strong industry and clinical partnerships evident in co-authored medical device publications. The ARM Lab maintains robust collaborations across Georgia Tech's robotics, neuroscience, and biomedical engineering communities. The Adaptation Robotic Manipulation Laboratory operates from Whitaker Building Room 4102, housing specialized facilities for soft robot fabrication (3D printing, shape deposition manufacturing) and biomechanics testing. Current projects include pediatric haptic feedback displays, biomimetic swimming robots, and kirigami-skinned earthworm robots for subsurface locomotion. The lab emphasizes translational research with multiple pending medical device patents and active participation in K-12 STEM outreach programs.

• Robotics
• Mechatronics
• Human-Robot Interaction
• +3 more

Mr. Richardo Khonasty is a Senior Research Engineer at the School of Mechanical and Mechatronic Engineering, part of the Faculty of Engineering and Information Technology at the University of Technology Sydney (UTS). He has held appointments at UTS since 2019, including roles at the Centre for Autonomous Systems and Robotics Institute. He also serves as a Tutor since 2016. PhD in Robotics (2020), UTS B.Eng. in Mechanical and Mechatronic Engineering (2014), UTS Khonasty's research focuses on robotics and human-robot collaboration, with applications in surgical robotics (total hip replacement), industrial automation (abrasive blasting), and green wall inspection systems. His work emphasizes kinematic accuracy, adaptive control schemes, and cost-effective robotic solutions. His recent publications explore robotic-assisted burring for orthopedic surgery, damping strategies for singularity management, and exoskeleton design frameworks. Khonasty is currently involved in funded research related to hydraulic tooling safety under the BTP - Stage 2 - IntelliForce Tooling grant.

Yayun DuView profile

Assistant Professor

• Bioelectronics
• Intelligent Systems
• Wearable and Implantable Sensors
• +7 more

Dr. Yayun Du is an Assistant Professor in the Department of Electrical and Computer Engineering at Vanderbilt University School of Engineering. She holds a Ph.D. in Robotics and System Control (Minor: Solid Mechanics) from UCLA (2022) and was a postdoctoral scholar at Northwestern University's Rogers Group through 2024. Current faculty at Vanderbilt University Ph.D. from University of California, Los Angeles Postdoctoral experience at Northwestern University Her research integrates bioelectronics and robotics through three core directions: 1) Developing multimodal wearable/implantable sensors for health monitoring, 2) Creating human-in-the-loop interaction systems using brain-computer interfaces, and 3) Applying machine learning to medical environment robotics. She has deployed four sensor types across seven hospitals globally, serving users from neonates to elderly patients. Dr. Du's recent publications focus on wireless bioelectronic devices ( PNAS ), sustainable sensor materials ( ACS Sustainable Chemistry & Engineering ), and agricultural robotics ( ICRA , IROS ). She serves as Associate Editor for ICRA 2025 and has received two Best Paper Award final nominations at IROS 2021. Finalist - Best Paper Award in Agri-Robotics (IROS 2021) Finalist - Best Paper Award in Robot Mechanisms and Design (IROS 2021) As head of the Du Group, she leads interdisciplinary research with applications in both healthcare and agricultural contexts, collaborating with Vanderbilt Institute for Surgery and Engineering (VISE) and clinical partners. Her work emphasizes deployable systems that transition from academic research to real-world implementation in medical and industrial environments.

Howie ChosetView profile

Professor

• Robotics
• Medical Robotics
• Snake Robots
• +11 more

Howie Choset is a Professor of Robotics at the Robotics Institute, Carnegie Mellon University. He directs the Undergraduate Robotics Minor and leads the Biorobotics Laboratory, where his research focuses on snake robots, motion planning, and medical robotics. He is also affiliated with the Manufacturing Futures Institute. Ph.D., Mechanical Engineering, California Institute of Technology (1996) M.S., Mechanical Engineering, California Institute of Technology (1995) B.S.E., Computer Science and Engineering, University of Pennsylvania (1990) B.S., Economics, The Wharton School of Business (1990) Choset's research centers on robotics for confined and complex environments, particularly through the development of snake robots. His work integrates mechanism design, path and motion planning, and estimation to enable applications in surgery, manufacturing, infrastructure inspection, and search and rescue. He is a pioneer in medical robotics and has co-founded Medrobotics to commercialize minimally invasive surgical robots. His recent publications highlight a strong focus on ergodic exploration, multi-agent systems, motion planning under uncertainty, and medical robotics. Themes include optimizing robot trajectories for information gathering, solving complex path planning problems with dynamic obstacles, and advancing autonomous systems for disaster response and space exploration (e.g., the EELS robot for Enceladus). MIT Technology Review Top 100 Innovators under 35 (2002) Best Paper Award, RIA (1999) Best Paper Award, ICRA (2003) Best Paper, IEEE Bio Rob (2006) Best Video, ICRA (2011) Nominations for best papers at ICRA, IROS, and CLAWAR Choset has advised numerous students, many of whom have won top awards. His lab has received significant funding for robotics research, including projects in surgical robotics, additive manufacturing, and autonomous exploration. He is the lead author of the textbook Principles of Robot Motion and is actively involved in educational innovation through custom robotics labs. He leads the Biorobotics Laboratory at CMU, which develops advanced robotic systems like snake robots and the EELS (Exobiology Extant Life Surveyor) robot for NASA missions. The lab collaborates with industry and government agencies on applications ranging from surgery to space exploration.

• Biomaterials
• Tissue Engineering
• Regenerative Medicine
• +12 more

Professor Hala Zreiqat AM is a leading biomedical engineer at The University of Sydney , serving as the Director of the ARC Training Centre for Innovative BioEngineering . A Fellow of all major Australian academies (AAS, ATSE, FAHMS, FRSN), she develops 3D printed bioceramics for bone regeneration while championing diversity through initiatives like the IDEAL Society and BIOTech Futures mentorship program. Her work bridges academia, clinical practice, and industry in musculoskeletal research . Research Focus: Her lab creates synthetic bone scaffolds that mimic natural bone architecture, strength, and porosity, enabling non-rejected bone regeneration via patient-matched implants. Key applications include orthopaedic, dental, and maxillofacial repair , with over $18M in competitive funding and multiple patents. Current projects explore AI-driven scaffold performance prediction and anti-senescence strategies for aging-related bone loss. Scientific Trends: Recent publications highlight 3D printed nanovoxelated ceramics , antisenescence biomaterials , and multifunctional theranostic platforms . Her team integrates machine learning for scaffold design, atom probe tomography for interface analysis, and two-photon imaging for cellular monitoring in 3D environments. 2021-2022 Fulbright Senior Scholar 2018 NSW Premier's Woman of the Year 2019 Eureka Prize for Innovative Use of Technology Fellow of Australian Academy of Science (2021) Over $18M in research funding Teaching & Leadership: She designed core courses like Tissue Engineering and Nanomaterials in Medicine , mentoring 158 students in 2020 alone. As Chair of CAAR (2020-2023), she strengthens Australia-Arab collaborations. Her lab trains early-career researchers , with alumni now in academia and industry.

Wenping WangView profile

Professor

• Computer Graphics
• Computer Vision
• Geometric Modeling
• +3 more

Wenping Wang is a Professor in the Department of Computer Science & Engineering at Texas A&M University, part of the College of Engineering. His research focuses on computer graphics, computer vision, geometric modeling, and visualization. He holds Fellowships from ACM and IEEE, and has received notable awards including the 2021 AsiaGraphics Outstanding Technical Contributions Award and the 2017 John Gregory Memorial Award. Wang's educational background includes a Ph.D. from the University of Alberta and M.Eng. and B.Sc. degrees from Shandong University. His work spans advancements in neural implicit surfaces, 3D reconstruction, and medical imaging applications such as orthodontic treatment prediction. He has authored numerous influential papers in top-tier conferences like SIGGRAPH and journals like ACM Transactions on Graphics. His research interests emphasize bridging geometric modeling with machine learning, particularly in neural rendering, surface parameterization, and medical visualization. Recent projects include developing frameworks for automatic tooth alignment and high-fidelity 3D geometry generation. Wang's contributions have significantly impacted both theoretical foundations and practical applications in computer graphics.

Stéphanie P. LacourView profile

Professor

• Bioelectronics
• Neuroprosthetics
• Soft Electronics
• +9 more

Stéphanie P. Lacour is a Full Professor at the School of Engineering, École Polytechnique Fédérale de Lausanne (EPFL), where she holds the Foundation Bertarelli Chair in Neuroprosthetic Technology. She leads the Laboratory of Soft Bioelectronic Interfaces (LSBI) and is affiliated with multiple departments including INX-STI, STI-SMT, SV-SSV, and AVP-DLE-EDOC. Since 2025, she has served as EPFL’s Vice-President for Support to Strategic Initiatives, overseeing institutional research strategy. Her research is centered at Campus Biotech in Geneva, where she was the founding director of the Neuro-X Institute. PhD in Electrical Engineering, INSA Lyon, France (1998–2001) Postdoctoral Research, Princeton University and University of Cambridge Joined EPFL in 2011 Her research focuses on soft bioelectronic interfaces that seamlessly integrate with biological tissues. She pioneers the development of stretchable, compliant electronics for implantable and wearable applications, using techniques from MEMS and microelectronics adapted to elastomeric substrates. Her work enables long-term, minimally invasive neural interfacing for applications in neuroprosthetics, rehabilitation, and health monitoring. Key innovations include soft electrocorticography arrays, liquid metal sensors, and encapsulation methods for chronic implants. Her recent publications span high-impact journals such as Nature , Science Robotics , Advanced Materials , and Nature Nanotechnology , covering topics like neural stimulation, soft robotics, wireless implants, and hydrogel-based interfaces . The work demonstrates a strong trend toward multimodal, closed-loop, and translational neurotechnologies with real-world clinical potential. Scientific Awards: No scientific awards explicitly mentioned in the provided text. She advises a large cohort of PhD students and postdoctoral researchers, many of whom have completed their theses under her supervision. Her team has received funding for projects in neural interfacing, bioelectronics, and soft robotics. She is actively involved in teaching courses such as Soft Microsystems Processing and Devices and Neural Interfaces . Lacour leads the Laboratory of Soft Bioelectronic Interfaces (LSBI) , a multidisciplinary research team focused on the fabrication, characterization, and in vivo evaluation of soft bioelectronic systems. The lab collaborates extensively across EPFL and with clinical partners to translate technologies from bench to bedside.

Sangbae KimView profile

Professor

• Bio-inspired Robotics
• Bipedal Locomotion
• Manipulation
• +7 more

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.