Associate Editors

His research lies at the intersection of movement neuroscience, machine learning, robotics, and control, with a focus on developing solutions for individuals with motor impairments. His primary research interests include human movement neuromechanics, predictive modeling of gait, human-robot interaction, and assistive and rehabilitation robotics, particularly in developing controllers and intelligent systems for exoskeletons. Dr. Arami’s work aims to create personalized assistive robotic systems that optimize support for individuals with motor impairments, especially those with incomplete spinal cord injuries, stroke, or Parkinson’s disease.

Dr. Artemiadis’ primary research interests have been in robotics and autonomous systems that interact with humans. The goals of his research have been to improve the quality of life by developing and controlling robotic devices that physically and cognitively interact and collaborate with humans. This interaction can be with devices that assist and augment human capabilities, as well as provide motor rehabilitation therapy to impaired individuals. In order to accomplish this, Dr. Artemiadis’ research has been focusing on answering important questions regarding the symbiosis of humans and robots in environments that involve physical and cognitive interaction.

Dr Arvaneh’s research interest includes brain-computer interface, assistive technology, prosthetic control, cognitive processes and their clinical applications. She applies her expertise in adaptive signal processing and machine learning to accurately detect different biomarkers within brain and other physiological signals. She has incorporated these biomarkers in a range of robotic stroke rehabilitation, brain monitoring and cognitive performance enhancement experiments both in the laboratory and clinical settings. Dr Arvaneh is the head of Physiological Signals and Systems laboratory in the Automatic Control and Systems Engineering department at University of Sheffield, where analytical and experimental techniques are combined to develop improved therapeutic, assistive, adaptive and rehabilitative technologies for a variety of conditions.

Sivakumar Balasubramanian is a Professor of Bioengineering at the Christian Medical College in Vellore, India. He completed his basic training in Electrical Engineering and received his B.Tech. Degree in Electronics and Communication Engineering in 2003 from the Pondicherry Engineering College, Pondicherry, India. In 2005, he obtained his MTech in Biomedical Engineering from the Indian Institute of Technology Bombay, Mumbai, India. He completed his doctoral research in upper limb rehabilitation robotics from Arizona State University, Tempe, Arizona in 2009. From 2010 to 2012, he served as a post-doctoral research associate at the Imperial College London (London, UK), and from 2012 to 2014, and he was a researcher at Tecnalia Research and Innovation (San Sebastian, Spain). He has been with the Department of Bioengineering at the Christian Medical College Vellore since 2014. He also holds an honorary Associate Professor’s position with the School of Health and Rehabilitation Sciences at the University of Queensland, Brisbane, Australia. His research interests are in the development, validation and translation of neurorehabilitation technology and quantitative movement analysis.

Dr. Bolívar-Nieto leads the Wearable Robotics Laboratory — an interdisciplinary group at the intersection of human biomechanics and robotics that specializes in optimization-based algorithms for the mechanical design, control, and estimation of wearable robots. Applications of this approach include convex optimization algorithms to design the load response of springs in series or parallel with electric motors, task-agnostic predictive controllers, and real-time algorithms to predict and estimate whole-body center of mass. The work of the Wearable Robotics Laboratory has been recognized by multiple journal publications, a U.S. patent, a Best Student Robotics Paper Award at the ASME Dynamics Systems and Control Conference, the Trailblazer Award for New and Early Stage Investigators from the U.S. National Institutes of Health (NIH), Graduate Research Fellowships from the U.S. National Science Foundation (NSF), and an Outstanding Associate Editor Award from the IEEE International Conference on Robotics and Automation (ICRA).

Dr. Thomas C. Bulea is a Staff Scientist in the Functional & Applied Biomechanics Section of the Rehabilitation Medicine Department at the National Institutes of Health Clinical Center, Bethesda, MD. Dr. Bulea’s research focuses on integration of neural interfacing and functional neuroimaging with rehabilitation robotics for evaluation and treatment of movement disorders and paralysis. Specific focus areas include combining electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) with motion capture and electromyography (EMG) to study brain-body dynamics during movement, development and evaluation of assistive devices and technology to improve motor function, and evaluation of novel rehabilitation therapies, including human-machine interaction and integration of virtual reality, to enhance motor learning and functional recovery. A recent emphasis has been on the development of pediatric exoskeletons and their evaluation in children with cerebral palsy.

Dr. Castellini leads the Assistive Intelligent Robotics Group at the University of Erlangen-Nuremberg, Germany. He obtained a Ph.D. in Artificial Intelligence from the University of Edinburgh, Scotland, in 2005; he then spent 4.5 years as a post-doctoral fellow at the Advanced Robotics Laboratory of the University of Genoa, Italy. Since 2009 he is a researcher at the Institute of Robotics and Mechatronics of the DLR – German Aerospace Center, and since 2021 he is a full professor in assistive robotics, focussing on human-machine interaction and interfaces for prosthetics, rehabilitation devices, and extended reality.

Dr. Rosa H. M. Chan specializes in brain-machine interface, computational neuroscience, neural prosthesis, and wearable computing. She was the co-recipient of the Outstanding Paper Award of IEEE Transactions on Neural Systems and Rehabilitation Engineering in 2013, for research breakthroughs in mathematical modeling for cognitive prosthesis. Dr. Chan has been elected as the VP-Finance of IEEE Engineering in Medicine and Biology Society (EMBS) for 2024-25. She chaired the Hong Kong-Macau Joint Chapter of IEEE EMBS in 2014, and was elected to the IEEE EMBS Administrative Committee (AdCom) as Asia Pacific Representative (2018-2022) and VP-Elect (Finance) in 2023. Currently, she serves as an associate editor for IEEE Transactions on Neural Systems and Rehabilitation Engineering and IEEE Reviews in Biomedical Engineering, and is on the editorial boards of the Journal of Neural Engineering and IEEE Open Journal of Engineering in Medicine and Biology.

Wei Chen is Professor, Director of Center of Intelligent Medical Electronics at School of Information Science and Technology, and Director of the Physiological Signal and Sleep platform in the Human Phenome Institute, at Fudan University, Shanghai, China. She is also an Associate Editor of IEEE Journal on Biomedical Health Informatics (J-BHI).

Her research interests include patient health monitoring, sleep monitoring, brain activity monitoring, smart sensor systems, wearable sensor systems, health robotics, machine learning and data fusion for healthcare. Her research center mainly focuses on advanced sensor systems; monitoring physiological, psychological and behavioral signals; multi-modal signal processing and data fusion, as well as user-centered design. Her center aims at improving quality of life, empowering patients for personalized health management; and providing doctors more accurate and efficient clinical decision support. Her research in the areas of neonatal monitoring, sleep monitoring, and smart rehabilitation covers healthcare for people of different age groups, from neonates to elderly.

Zhe Sage Chen is a tenured associate professor and principal investigator at New York University (NYU), with joint appointment at the Department of Psychiatry and Department of Neuroscience and Physiology at NYU Grossman School of Medicine, Department of Biomedical Engineering at NYU Tandon School of Engineering. He is the Founding Director of the CN^3 (Computational Neuroscience, Neuroengineering and Neuropsychiatry) Laboratory at NYU, and Program Director of the Computational Psychiatry program at NYU. The research in his lab covers a wide range of areas in computational neuroscience, neural engineering, machine learning, and brain-machine interfaces, studying fundamental research questions related to sleep and memory, nociception and pain, and cognitive control, which has been published in high-impact journals. He is the lead author of the book Correlative Learning (Wiley, 2007) and the editor of books Advanced State Space Methods for Neural and Clinical Data (Cambridge University Press, 2015) and Dynamic Neuroscience: Statistics, Modeling, and Control (Springer, 2018). In addition to IEEE TNSRE, he has served in the editorial board for Neural Networks, Journal of Neural Engineering, and Frontiers in Computational Neuroscience.

Dr. Ashley Dalrymple is an Assistant Professor at the University of Utah, jointly appointed with the Departments of Biomedical Engineering and Physical Medicine & Rehabilitation and Director of the NERVES Lab. She completed her BSc in Electrical and Biomedical Engineering and her PhD in Neuroscience at the University of Alberta. She then went on to complete a postdoc at the Bionics Institute in Melbourne, Australia. Dr. Dalrymple moved to Pittsburgh to complete additional postdoc training, first at the University of Pittsburgh and then at Carnegie Mellon University. During that time, she obtained a pilot grant from the National Center of Neuromodulation for Rehabilitation and was awarded a prestigious fellowship from the Canadian Institutes of Health Research. The focus of Dr. Dalrymple’s work involves the use of implanted and non-invasive neural interfaces to restore function, particularly the rehabilitation of walking, restoring sensation, and reducing pain. Her research spans basic science, proof-of-concept, pre-clinical, and clinical studies.

Dr. Dean leads the Locomotion & Energetics Group at the Medical University of South Carolina. His research applies an engineering-based understanding of human movement to the development of rehabilitation techniques for clinical populations with limited functional mobility. This mechanistic work is focused on the influence of body biomechanics and sensory feedback on the control of human locomotion, and changes that occur following neurological injuries.

Dr. Fani Deligianni is a Senior Lecturer (Associate Professor) at the School of Computing Science at the University of Glasgow, UK. She is also the lead of the Computing Technologies for Healthcare theme. Dr Fani Deligianni’s holds a PhD in Medical Image Computing (Imperial College London), an MSc in Advanced Computing (Imperial College London), an MSc in Neuroscience (University College London) and a MEng (equivalent) in Electrical and Computer Engineering (Aristotle University, Greece).

Her research interests involve the development of machine learning approaches to process neurophysiological and human motion data to improve performance of human-AI systems and preserve human health and wellbeing. She has a strong track record on statistical machine learning with brain MRI data, human motion analysis as well as adaptive brain computer interfaces and wearable sensing technologies.

Strahinja Dosen is a Full Professor in Rehab Robotics at the Department of Health Science and Technology (HST), Aalborg University (AAU), Denmark, where he leads a research group on Neurorehabilitation Systems. He received the Diploma of Engineering in Electrical Engineering and the M.Sc. degree in Biomedical Engineering in 2000 and 2004, respectively, from the Faculty of Technical Sciences, University of Novi Sad, Serbia, and the Ph.D. degree in Biomedical Engineering from the Center for Sensory-Motor Interaction (SMI), Aalborg University, Aalborg, Denmark, in 2009. Until 2017, he was working as a Research Scientist at the Institute for Neurorehabilitation Systems, University Medical Center Gottingen, Germany, and then as an Associate Professor at the Department of Health Science and Technology (HST), Aalborg University (AAU), Denmark. Since 2017, he has been a Full Professor in the same Dept. and a principal investigator for AAU and HST in several EU (Tactility, Wearplex, Sixthsense, and SimBionics) and nationally (Robin, Remap and Climb) funded projects. He has published more than 100 manuscripts in peer-reviewed journals. His main research interests are the closed-loop control of movements and assistive systems, including the development of methods and technologies for human-machine interfacing, control of bionic limbs and rehabilitation robots, artificial sensory feedback, haptics, and functional electrical stimulation.

Yanggang Feng received his Ph.D. degree in Dynamics and Control from the College of Engineering, Peking University, Beijing, China, in 2019. Afterward, he joined the University of Tokyo, Tokyo, Japan, as a Postdoctoral Researcher. Currently, he is affiliated with the Institute of Robotics, School of Mechanical Engineering and Automation, Beihang University, Beijing, China. His research interests include wearable robots, human intelligence, and human-machine interaction. He has published numerous academic papers in reputable journals, e.g., IEEE TRO, TMECH, TNSRE, and TMRB.

Dr. Arielle Fischer is an Assistant Professor in the Department of Biomedical Engineering at the Technion – Israel Institute of Technology. She is head of the Technion BioMotion Lab, where her research is dedicated to the exploration of human biomechanics and wearable technology. In her current role, Dr. Fischer also serves as the Head of Collaborative Research between the Technion and the Israel Olympic Committee. Her research endeavors center around the intricate relationship between mechanics, biology, and structural factors in musculoskeletal joint pathologies, encompassing a wide spectrum from sports-related injuries to conditions like osteoarthritis and neuromuscular disorders. Dr. Fischer’s approach involves the use of non-invasive smart wearable personalized devices and sensor technologies to capture extensive bio-signal data, enabling a comprehensive examination of abnormal motion mechanics and joint health. To extract valuable insights from these intricate datasets, she leverages advanced machine learning algorithms, thus actively contributing to the advancement of inventive medical devices and interventions. Dr. Fischer’s academic path commenced with her pursuit of Mechanical Engineering at MIT. Subsequently, in 2011, she earned her BSc in Biomedical Engineering at the Technion. She furthered her education by completing an MSc (2013) and a PhD (2016) in Mechanical Engineering, both at the Technion. Following this, she held a postdoctoral research position at Stanford University from 2016 to 2020.

Dr. Fisher is an Assistant Professor in the Department of Physical Medicine and Rehabilitation at the University of Pittsburgh and Director of Education for the Rehab Neural Engineering Labs. His research interests focus on the development of neuroprosthetic systems to restore function after injury or disease to the nervous system, including limb amputation and spinal cord injury. His ongoing research efforts include the clinical testing of spinal cord stimulation to restore sensory function after the loss of a limb and pre-clinical development of devices to stimulate the spinal cord and vagus nerve to control sensory, bladder, and gastrointestinal function. In 2021, he was awarded the North American Neuromodulation Society’s Kumar New Investigator Award for his research on the use of cervical spinal cord stimulation to restore sensory function after upper-limb amputation.

Dr. Gandolla is a Senior Researcher within the Department of Mechanical Engineering at Politecnico di Milano, whose research investigates neurological motor rehabilitation and motor assistance during daily life activities of fragile people or during exhausting activities of workers. She works within a multidisciplinary team, concentrating on the mechanical design of both rehabilitation and assistance devices toward exoskeletons, to allow movement to be perceived as more natural, and the control design toward patients’ initiated/controlled approaches to include users’ personal motor programming in the loop. As a further step, any device design naturally needs validation, both in terms of the effectiveness of the rehabilitation or assistance and the device’s usability and acceptability. The same user-centered approach is successful when investigating strategies to relieve a worker’s musculoskeletal system when performing exhausting activities. Biomechanical analysis, wearability, and ergonomics are key. Her research aims to enable solutions “from cure to care” and leverages multidisciplinary methodologies, including mechatronic design, human-machine interaction, and artificial intelligence. Dr. Gandolla focuses on the investigation of rehabilitation biomarkers and motion control strategies toward the development of human-centered and personalized technologies for effective usability and the democratic adoption of developed technologies.

Sabata Gervasio’s research focus is to understand how sensory feedback is processed in normal or pathological situations, and to identify and treat sensory-motor impairments and disorders. She has been investigating, for instance, the role of crossed spinal reflexes in interlimb coordination, the use of nociceptive withdrawal reflex in stroke rehabilitation and the effect of neurofeedback on musculoskeletal pain. Recently, she focused on methods to improve diagnosis and interventions for children with sensory motor impairments, including Sensory Processing Disorders, Autism Spectrum Disorder (ASD), Attention-Deficit/Hyperactivity Disorder (ADHD) and Cerebral Palsy. She is currently working on the development of a protocol to identify and assess the mechanism behind sensory processing anomalies in children with ASD and ADHD.

Dongyun Gu is Professor in the Department of Orthopaedic Surgery of Shanghai Ninth People’s Hospital affiliated to Shanghai Jiao Tong University School of Medicine and has a joint appointment with the School of Biomedical Engineering of Shanghai Jiao Tong University, China. She is the Deputy Director of Engineering Research Center of Digital Medicine & Clinical Translation of the Ministry of Education, China, which has been the first national center that focuses on innovative translational research and development of digital medicine. Dr. Gu’s research interests include gait analysis, musculoskeletal biomechanics, wearable devices and machine learning. Her research group investigates human gait disorder affected by physical disability, neurological disorders, musculoskeletal pathology and age-related diseases, with a goal of developing gait rehabilitation interventions and improving clinical decision-making. They also focus on the development of wearable gait analysis systems and deep-learning based human pathological gait recognition.

Dr. Guarin is an Assistant Professor for the Department of Applied Physiology and Kinesiology at the University of Florida. He was formerly an Assistant Professor in the Biomedical Engineering program at the Florida Institute of Technology, Melbourne, FL. USA. Dr. Guarin received his Master’s and Doctorate degrees in Biomedical Engineering from McGill Univerity and was a postdoctoral trainee at Harvard University and the University of Toronto/ Toronto Rehabilitation Institute. He is the director of The Movement Estimation and Analysis; his research areas include neuroscience, signals analysis and synthesis, machine learning, and computer vision. Dr. Guarin’s work is focused on translating engineering approaches to develop disease-modifying therapies for patients with neuromuscular diseases and novel methods for disease diagnosis that are sensitive for early diagnosis.

Xiaoli Guo is an Associate Professor at School of Biomedical Engineering, Shanghai Jiao Tong University, China. Her research interests focus on understanding brain diseases and neurorehabilitation using neuroimaging techniques from the aspect of neural plasticity. Her ongoing research efforts includes processing and integrating multimodal brain images (EEG, fMRI, DTI, etc.) for characterization of pathological conditions, such as stroke, amputation, Parkinson’s Disease and mental disorders, as well as for a better understanding of brain reorganization related to brain development and rehabilitation.

Dr Fei He is an Associate Professor and co-leads the ‘Digital Health’ Cross Cutting Theme at Coventry University. His research interests lie at the interface of control systems engineering, signal processing and neuroscience. Dr He has been developing nonlinear system identification, frequency-domain analysis, and graph deep learning techniques to study complex nonlinear interactions in human brain network; and use such nonlinear and network features to improve the diagnosis of neurological disorders, such as Alzheimer’s disease, from neurophysiological signals like electroencephalogram (EEG). Thus, his research expertise/areas include nonlinear systems, graph deep learning, EEG, brain connectivity, system identification, brain networks. He is a Senior Member of IEEE. Dr He previously held research positions at Imperial College London, University of Sheffield, and University of Manchester. He received a PhD and an MSc in control engineering from The University of Manchester.

Dr. Hu’s research focuses on neural control of biological and bionic hands. He develops neural-machine interface and neural stimulation techniques to help restore sensory and motor functions of the hand in individuals after stroke, traumatic brain injury, or limb loss. He is also interested in home-based health monitoring approaches that can continuously assess motor impairment and facilitate home-based neural rehabilitation.

Meghan Huber is an Assistant Professor in Mechanical and Industrial Engineering at University of Massachusetts Amherst. She is the director of the Human Robot System Laboratory, which conducts interdisciplinary research at the intersection of human neuromotor control and robotics. Specifically, her research investigates how humans learn internal models of robotic systems, such as wearable exoskeletons and robot manipulators, through physical interaction. She then leverages this fundamental work to develop novel robotic systems for assisting and (re)training human motor behavior.

Shahid Hussain is an Associate Professor at the University of Canberra where he directs the Rehabilitation Engineering Research Lab. Dr. Hussain’s primary research focuses on the development of rehabilitation and assistive robots. The development aspects of these robotic systems involve compliant actuation, robot mechanism design and optimization, non-linear dynamics and control of robotic systems, human-robot interaction, and biomechanical modelling. The unique feature of Dr. Hussain’s research is the control approach of these rehabilitation and assistive robots which is centred around the biomechanical models. Biomechanical models developed by Dr. Hussain are specifically suitable for the human-robot interaction control.

Prof. Chang-Hwan Im received his B.S. degree from the School of Electrical Engineering, Seoul National University, South Korea in 1999, and M.S. and Ph.D. degrees from the same university in 2001 and 2005, respectively. He was a post-doctoral Associate in the Department of Biomedical Engineering, University of Minnesota, Minneapolis, USA, from 2005 to 2006. From 2006 to 2011, he was with the Department of Biomedical Engineering, Yonsei University, South Korea, as an assistant/associate professor. Since 2011, he has been with the Department of Biomedical Engineering, Hanyang University, South Korea, as a full professor. He has authored more than 200 articles in peer-reviewed international journals. He is currently serving as an Associate Editor for six international journals. His research interests cover various areas of computational neuroengineering, especially brain-computer interfaces, diagnosis of neuropsychiatric diseases, noninvasive brain stimulation, and biosignal-based human-computer interfaces. He is currently the director of the Computational intelligence and Neural Engineering (CoNE) Laboratory and Research Center for Neural Engineering, Hanyang University, South Korea.”

Delaram Jarchi is a Lecturer in Artificial Intelligence (AI) and machine learning at the School of Computer Science and Electronic Engineering, University of Essex, Essex, UK. Her research has been focused on the use of wearable sensors for healthcare applications including designing new algorithms and validation of commercial wearable sensors for robust estimation of physiological parameters such as heart rate, respiratory rate and blood oxygen saturation level in very unobtrusive ways. Her research interests include Body Sensor Network, Internet of things (IoT), bio-signal processing, adaptive signal processing and machine learning.

Dr Kameneva’s research interests include visual neuroscience and computational modelling; her research combines engineering tools and mathematical methods to solve open problems in biology and medicine. Dr Kameneva has expertise in control theory tools and their applications in life sciences and neuroprosthetic implants. Dr Kameneva contributes to the understanding of neural information processing in response to stimuli; she studies how electrical and optical stimulation affects neural activations and works on the development of new stimulation methods that can be used across a broad range of medical bionics applications.

Dr. Kamper’s research interests focus on the neuromechanics of the upper extremity and the restoration of upper extremity function following neurological injury. Studies of biomechanics and motor control are undertaken with the goal of identifying impairment mechanisms in individuals following neurological damage. Knowledge of these mechanisms guides the development of novel interventions, including virtual reality and soft exoskeletons.

Dr. Sang Hoon Kang is an Associate Professor in the Mechanical Engineering at UNIST and the Director of the Robotics and Rehabilitation Engineering Lab (R^2EL). Dr. Kang’s research interests include rehabilitation robotics/mechatronics and biomechanics of human movement, with an emphasis on rehabilitation medicine. He has been working on an upper-limb exoskeleton robot for neurorehabilitation, robust methods and robots for estimating upper limb mechanical impedance representing rigidity/spasticity, a real-time estimation method of knee 3D moments during stepping on a trainer for diagnosis/training of patients with knee osteoarthritis, a stepping device for the prevention and rehabilitation of the elderly with knee osteoarthritis or with sarcopenia at risk, and a device for evaluating joint proprioception under different external torques. He is a member of IEEE. He is the chair of the Technical Committee on Rehabilitation Robot, Korea Robotics Society, and Board Member of Korea Robotics Society, Korean Society of Medical Robotics, and the Bioengineering Division of The Korean Society of Mechanical Engineers.

Dr. Kaplanoglu leads the Biomechatronics & Assistive Technology Lab (BioAstLab®) at the University of Tennessee at Chattanooga. His research focuses on Biomechatronics systems; EMG and EEG controlled Prosthesis/Orthosis and Wearable Rehabilitation Robotics. Besides his biomechatronics research, he is also working on human-collaborative/industrial robot interaction with bio signals.

Dr. Hogene Kim seeks to develop practical technology and useful devices to people with special needs in rehabilitation engineering research. He is interested in understanding the human movement biomechanics in persons with neurological impairments and thus to find novel clinical interventions using diagnostic or therapeutic rehabilitation robotics and assistive technology in the community including rehabilitation exercise equipment. His research continues to extend real-world applications of the principles of design, instrumentations, and experimental methods in modern technology and product engineering for therapeutic advances in rehabilitation engineering.

Dr. Myunghee Kim is an assistant professor in Mechanical and Industrial Engineering at University of Illinois, Chicago. She directs Rehabilitation Robotics Lab. The lab aims to enhance human locomotion with assistive devices by coupling machine learning methods, a model-based approach, and hardware experimentation. Machine learning is used as a tool to learn human-robot interaction and human locomotion. This learning involves controlled human subject experiments with wearable robots. A simplified model is used to understand the underlying mechanism of such a learning process as the model is intellectually accessible. The outcome will inform effective wearable robot design and prescription to improve mobility and quality of life.

Dr. Klute’s research aims to enhance the mobility of individuals with lower limb amputation. His interests in biomechanics and robotics include: development of prosthetic lower limbs to facilitate the complex maneuvering gait that occurs in everyday life, terrain adapting prostheses that improve balance, and prostheses that remain secure despite vigorous activity in demanding environments.

Dr. Ko is a Professor in Institute of Bioinformatics and Systems Biology in National Chiao Tung University, Hsinchu, Taiwan. Dr. Ko is also affiliated with Institute of Biomedical Engineering, and Brain Research Center in NCTU, Taiwan. Dr, Ko is also the visiting scholar in Institute for Neural Computation (INC) in University of California, San Diego (UCSD). Dr. Ko leads Neural Engineering Laboratory in NCTU and primary research interests are focusing on neural engineering related research, especially in brain computer interface (BCI), real-world neuroimaging (RWN), EEG-fMRI simultaneous recording, functional near-infrared spectroscopy(fNIRS), and neural computation in the neurological diseases such as neural rehabilitation, migraine, and sleep disorders. In academic service, Dr. Ko was the Associate Editors of IEEE Transactions on Neural Networks and Learning Systems (Impact Factor: 6.108, Rank: 3/104, of computer science, theory and methods) in IEEE Computational Intelligence Society (CIS) from 2010-2015 and served as the committee members in neural networks and fuzzy systems technical committees.

Professor Krishnan directs the Neuromuscular and Rehabilitation Robotics Laboratory (NeuRRo Lab) at the University of Michigan. He is a physical therapist by background and has vast clinical experience both in inpatient and outpatient rehabilitation. He received his PhD in Physical Therapy & Rehabilitation Science from the University of Iowa in 2009 and completed a 3-year postdoctoral fellowship in Robotics and Noninvasive Brain Stimulation at the Rehabilitation Institute of Chicago and Northwestern University. His research involves both mechanistic and interventional studies to facilitate our current understanding of neuromuscular function and regulation in the context of movement control and neuromuscular plasticity. He has a special interest in developing and testing low-cost technologies for the assessment and treatment of neurological and orthopedic conditions.

Dr. Song Joo Lee is a Principal Research Scientist in the Bionics Research Center at the Korea Institute of Science and Technology, Seoul, South Korea. She is also an associate professor at the division of Bio-Medical Science & Technology, KIST School, University of Science and Technology (UST) and directs the Neuromechanics lab.

Dr. Lee’s research interests stem from evidence-based translational research that aims to make biomechanical and (patho)physiological finding useful and improve human neuromuscular performance for patients with movement disorders. Her lab focuses on 1) understanding human neuromechanics by applying engineering principles and 2) applying the knowledge to develop rehabilitation strategies and assessment tools. Her research fields include neuromechanics, brain-computer interface, prosthetics and orthotics, and rehabilitation engineering.

Mike Lewek is a faculty member in the Division of Physical Therapy, Department of Health Sciences at the University of North Carolina at Chapel Hill. He currently serves as the associate Director of the Closed Loop Engineering for Advanced Rehabilitation core in the joint Department of Biomedical Engineering at UNC-Chapel Hill and NC State University. He is also the associate director of the Human Movement Science PhD Curriculum at UNC – Chapel Hill. Dr. Lewek’s uses tools in biomechanics, motor learning, and clinical rehabilitation to understand and improve walking function for people with neurologic injuries. Most of his work has been with people recovering from stroke, or with Parkinson disease.

Jing Li is a Professor with the School of Computer Science and Engineering at Tianjin University of Technology, Tianjin, China. She holds a Ph.D. in Electronic and Electrical Engineering (University of Sheffield, U.K.) and has worked as an Associate Professor with the School of Information Engineering at Nanchang University and a Research Associate with the Department of Computer Science at University of Sheffield.

Her research interests involve the development of machine learning methods for the assistive diagnosis and intervention of brain diseases, including Autism Spectrum Disorder (ASD) and Major Depressive Disorder (MDD), based on multimodal data, e.g., video, texts, EEG and fMRI. She has a strong track record in computer vision and pattern recognition, and proposed some representative approaches of gaze estimation, facial expression recognition, abnormal behavior detection, etc.

Le Li currently is a professor with the Institute of Medical Research, Northwestern Polytechnical University, Xi’an, China. Prof. Li’ primary research interests have been in rehabilitation engineering and biomechanics, particularly in neuromusculoskeletal modeling of normal and spastic subjects, bio-signal processing and evaluation (ie. Electromyography, Electrical impedance myography, etc), neuromodulation technique, and musculoskeletal ultrasound application. He has published over 100 papers in these areas. He is also in Editorial board of BMC Musculoskeletal Disorders and guest associate editor of Frontiers in Bioengineering and Biotechnology, Frontiers in Aging Neuroscience.

Max began his career writing software, signal processing algorithms and music for video games, then moved on by way of a degree in mathematics to the University of Oxford. After postdoc positions in Oxford and co-founding a web-based image search business, he won a Wellcome Trust fellowship at MIT to follow up on his doctoral research work in biomedical signal processing. He is currently an Associate Professor in Computer Science at the University of Birmingham in the UK, where his research focuses on the theory of machine learning with applications to wearable devices.

Dr. Lobaton’s research focuses on the integration of AI, and physical and probabilistic modeling applied to cyber-physical systems in areas such as wearable health monitoring, rehabilitation robotics, and biological imaging. He has worked on applications including gait analysis using kinematic and inertial measurements, and predictive models that make use of computer vision to provide context awareness to robotic prosthesis for adaptive operation. The emphasis of his probabilistic approaches is on robust AI models that incorporate techniques such as accurate uncertainty quantification and out-of-distribution detection. Dr. Lobaton leads the Active Robotic Sensing (ARoS) laboratory at NC State.

Pauline Maurice is a CNRS researcher within the LORIA laboratory, University of Lorraine, France. She holds an MS and a PhD in Robotics from Sorbonne University (France), and an MEng from Ecole Polytechnique (France). Her research interests are in computational and experimental human motion analysis in the context of physical human-robot interaction, in order to develop human-centered designs and controllers for collaborative robots and exoskeletons, with a focus on ergonomics.

Dr. Juan Moreno is Principal Investigator and Director of the BioRobotics Group in Center for Automation and Robotics at CSIC (Spain). He is the Responsible of the Associated Unit to CSIC from the National Spinal Cord Injury Hospital promoting translational research to generate knowledge and deliver solutions for disabled people. His main research fields are wearable robotics, neuroprosthetics and neural rehabilitation technologies. In each one of them, he has made contributions which have greatly impacted the robotics and neural engineering communities. He has led development of several human-machine interaction schemes applied for neural rehabilitation of patients with brain or spinal lesions. One of his main lines of research investigates the benefits of cooperative control in the fusion of neuro-prosthetic and robotic exoskeletons in improving locomotion in stroke and spinal cord injured patients. He is currently leading research projects on modeling and characterization of longitudinal robot-aided treatments towards optimization of robotic therapy and FES-based therapy with intelligent controllers. He has supervised 6 completed doctoral theses and currently is supervising 7 doctoral projects. Dr. Moreno has coordinated several international European projects in the last 10 years. He is founder & Co-Chair of the IEEE/RAS Technical Committee (TC) on Wearable Robotics. He is co-founder of Technaid S.L., “spin-off” company of CSIC. His contributions have been licensed for exploitation and his concepts to establish robot-based therapies have won 4 outstanding awards and 4 personal prizes including the Young Investigator Medal by Royal Academy of Engineering (2015), Princess Infanta Cristina Award (2011), MIT’s Technology Review 35 Spain 2012 Award, and the Royal Academy of Engineering of Spain Young Scientists Medal 2015.

Dr. Nakanishi is an Assistant Research Scientist at Swartz Center for Computational Neuroscience, Institute for Neural Computation, University of California San Diego. His research interest spans brain-computer interface, ERPology, neurobiology of language, multi-modal bio-sensing (e.g., EEG, ECG, EMG, PPG, and GSR), and their real-world and clinical applications, aiming at enhancing human physical, mental and social well-being.

Imran Khan Niazi received his B.Sc. degree in Electrical engineering (specialization: Biomedical Engineering) from the Riphah International University, Islamabad, Pakistan, in 2005 and his Master’s in biomedical engineering from University & FH Luebeck, Luebeck, Germany, in 2009 and later he got his PhD from Center of sensory-motor interaction, Health Science Technology Department, University of Aalborg, Aalborg, Denmark in 2012. After working as a research assistant professor for a year, he moved to New Zealand in 2013, where he is currently working as Dean of innovation and technology and Research director at the New Zealand College of Chiropractic. His research interests focus on rehabilitation engineering, neural engineering, and brain-machine interface for rehab with a patient-centred approach. He is interested in studying and understanding the altered mechanism of motor control and learning in neurological disorders to develop various technologies that can enhance the QOL of these patients. His publication can be found here.

Dr. Novak’s primary research areas are wearable robotics, rehabilitation robotics, serious games, and affective computing. Her overall goal is to improve human health and wellbeing through development and evaluation of novel intelligent and user-friendly technologies. For example, she has used signal processing and pattern recognition techniques to infer human workload levels, and has used this information to guide adaptive rehabilitation games. Additionally, she has used diverse signals to infer human motor intentions in wearable devices such as exoskeletons and prostheses. She is currently an Associate Professor of Electrical Engineering and Computer Science at the University of Cincinnati. She is a senior member of the IEEE and an active volunteer for several LGBTQ+ organizations.

Denny Oetomo’s research interest is in robotics and the physical interaction between human and robots. Specifically, it includes the topics of rehabilitation robotics, physical assistive robots and the information content in perception as well as dexterous manipulation through advanced prostheses. He co-leads the Human-Robotics Laboratory at The University of Melbourne. Aside from the TNSRE, he has been an associate editor for ASME Journal of Mechanisms and Robotics, IEEE Robotics and Automation Letters, IEEE/ASME Transactions on Mechatronics, and (Elsevier IFAC) Mechatronics.

Professor Ono leads the Health Science and Medical Engineering Lab of the Department of Electronics and Bioinformatics, School of Science and Technology at Meiji University, Japan. Her team focuses on combining human functional measurement and bio-signal processing techniques to develop novel applications in medical diagnosis and neurorehabilitation. Professor Ono’s personal expertise and research interest lie in the human cognitive neuroscience and neural engineering of cognitive/motor enhancement, utilizing the electrical and optical functional imaging/stimulation techniques (EEG, MEG, fNIRS, fMRI. PET, tDCS, and diffuse correlation spectroscopy).

Dr. Lizhi Pan received the Bachelor degree in Mechanical Engineering from Wuhan University, Wuhan, China, in 2010 and the PhD degree in Mechanical Engineering from Shanghai Jiao Tong University, Shanghai, China, in 2016. From 2016 to 2019, he was a Postdoctoral Research Associate in the Joint Department of Biomedical Engineering at the University of North Carolina at Chapel Hill and North Carolina State University. He is currently a professor at School of Mechanical Engineering, Tianjin University, Tianjin, China. His research interests include bio-mechatronics and surgical robots. The goal of his research is to use myoelectric signals to achieve the closed-loop control of surgical robots. He is a member of the Chinese Committee of the International Federation for the Promotion of Mechanism and Machine Science (IFToMM).

Dr. Danilo Pani leads the Medical Devices and Signal Processing (MeDSP) Lab at the University of Cagliari, Italy. The MeDSP Lab is a biomedical engineering lab specialized in advanced biomedical signal processing, applied machine learning, and the development of medical devices and systems.

His research interests include cardiac electrophysiology, fetal electrocardiography, wearable sensors and systems for health monitoring and advanced human-computer interfaces, neurorehabilitation, and telemedicine. In the field of neural system and rehabilitation engineering, his main achievements are in the development and validation of novel polymer-based textile electrodes for EMG, telerehabilitation systems, and real-time systems for neural signal decoding in neuroprosthetics application.

Dr. Pani is a senior member of the IEEE, and co-founder officer of the Italian Chapter of the IEEE Sensors Council. He is organizer and chair of the International Summer School on Technologies and Signal Processing in Perinatal Medicine (TSPPM). He is an Italian expert in the Technical Committee 251 of CEN, Working Group 2.

Dr. Hyung-Soon Park is a Professor in the Department of Mechanical Engineering at KAIST (Korea Advanced Institute of Science and Technology). He serves as the director of KIHST (KAIST Institute for Health Science Technology), the KAIST-CERAGEM healthcare research center, and the RENEW (Rehabilitation Engineering for Neurological disorders worldwide) center. Dr. Park’s overarching research objective is to advance robotics and sensor technology for the purpose of reconnecting neural pathways related to human movement.

His ongoing research is centered around several key areas, including the development of soft wearable hand rehabilitation robots, brain-machine interfaces, and machine learning algorithms for recognizing intentions in upper limb movement. Furthermore, his work explores neuromuscular coordination in human movement and the design of robotic devices for monitoring and assisting human motion. Dr. Park is widely acknowledged as a pioneering researcher, notably recognized for his enduring contributions to the field of rehabilitation robotics in South Korea.

Dr. Emily Rogers-Bradley is an Assistant Professor at the University of Calgary in the departments of Mechanical and Manufacturing Engineering and Biomedical Engineering. Dr. Rogers-Bradley is the director of the Adaptive Bionics Lab, researching the design of quasi-passive prostheses and exoskeletons that adapt to speed, terrain, and ground surface for walking and running optimization. Her research merges precision machine design, biomechanics, and robotics for the development of new types of prostheses and exoskeletons. Prior to joining the University of Calgary she obtained her PhD in Mechanical Engineering from Massachusetts Institute of Technology in February 2023. She received a SM in Mechanical Engineering from MIT in 2019 and a SB in Biomedical Engineering from Harvard University in 2015. She has also spent several years in industry as a Mechatronics Engineer at Ekso Bionics, where she designed robotic exoskeletons for stroke and spinal cord injury rehabilitation. Her work has been featured in the PBS NOVA documentary ‘Augmented’, a permanent exhibit in the Boston Museum of Science, and she is a named inventor on 3 patents.

Dr. Sahin’s research career has focused on pre-clinical testing of Neuromodulation ideas in general, starting out with Hypoglossal Nerve stimulation, and then moving to the Spinal Cord with the floating light-activated micro-stimulators (FLAMES) and the Spinal Cord-Computer Interface projects. His recent research interests have been in Neuromodulation of the Cerebellum using transcranial AC stimulation (tACS) and Low Intensity Focused Ultrasound (LIFUS). Specifically, he is working on modulatory effects of cerebellar cell entrainment on motor functions. He has been on the faculty of Biomedical Engineering at New Jersey Institute of Technology since 2005, and currently he is a Full Professor. He has authored more than 100 peer-reviewed publications, including a textbook on Bioinstrumentation as the lead-author and three patents. Dr. Sahin is an Editorial Board Member on Academia Engineering, an Associate Editor for Frontiers in Neuroscience-Neuroprosthetics, and a Senior Member of IEEE/EMBS.

Andrej Savić is affiliated with the Science and Research Centre of the University of Belgrade – School of Electrical Engineering in the role of Senior Science Associate. He received Dipl. Ing degree, master’s degree and the PhD in Electrical Engineering and Computer Science from University of Belgrade – School of Electrical Engineering, Belgrade, Serbia in 2008, 2010 and 2014 at study modules for Physical Electronics, Biomedical Engineering and System Control and Signal Processing, respectively. His main research interests include biomedical engineering, neural engineering, and neuroscience, with specific expertise in brain-computer interfaces (BCI) and closed-loop neurotechnology. He has actively contributed to a total of 15 publicly (EU) and privately funded research projects covering topics such as BCIs for stroke rehabilitation, assistive BCIs for ALS, hybrid BCIs, neuroergonomics, implantable neurotechnology, neuromodulation, and neural biomarkers of neurological disorders. He was the principal investigator for the HYBIS project funded by the Fund for Science of the Republic of Serbia, dedicated to excellent ideas of young researchers, and led a team of five researchers from three Science and Research institutions. He has more than 8 years of experience in collaboration with industry partners. Since 2016, he has held a lecturer position at the University of Belgrade, contributing to multidisciplinary PhD studies in Biomedical Engineering and Technologies, Intelligent Systems, and Biophysics. He actively participates in supervising multiple PhD theses. He has coauthored more than 90 scientific publications in peer-reviewed journals, books, and conferences. Additionally, he serves as a reviewer and editor for multiple international scientific journals.

Marianna Semprini got a BS in Biomedical Engineering and a MS in Bioengineering (Neuroengineering curriculum) both at the University of Genoa (Italy) in 2004 and 2007 respectively. In 2007 she was research fellow at Northwestern University (Chicago, IL, USA). In 2011 she received a PhD in Robotics, Neurosciences and Nanotechnologies from the Istituto Italiano di Tecnologia (IIT). 

She is currently Clinical Research Team Manager at IIT-INAIL Rehab Technologies Lab of the Italian Institute of Technologies. Her current interests are  neurorehabilitation, neuroprostheses and neural control of movement

Dr. Jon Sensinger is the director of the Institute of Biomedical Engineering and a professor of Electrical Engineering at the University of New Brunswick. Trained as a biomedical engineer and licensed as a professional engineer in the province of New Brunswick, he has worked in Chicago and Thailand and cofounded Coapt LLC, the first company to successfully market pattern recognition in prostheses. His past research has developed new mechatronic devices including motor designs and cycloid gears, along with complete prosthetic systems. His current research focuses on curiosity-driven algorithms with applications in human-machine interfaces, prostheses, exoskeletons, and the newly constructed Centre for Adaptive Rehabilitation Engineering, which houses massive infrastructure that can be controlled in real-time to provide immersive virtual reality environments. He leads a team of faculty, scientist, engineers, clinicians, and students who all share a common goal of making an impact in the lives of others that extends from our neighborhoods to the international community.

Dr. Sharma leads Neuromuscular Control and Robotics lab in the Joint Department of Biomedical Engineering at NC State University and UNC-Chapel Hill. His research lab focuses on the modeling, optimization, and control of functional electrical stimulation (FES) and hybrid exoskeletons that combine FES and a powered exoskeleton. The lab also researches ultrasound imaging-derived and surface electromyography signals that quantify muscle contractility changes during FES-evoked and voluntary limb movements. The research uses a variety of control design tools ranging from Lyapunov-based nonlinear control design, model predictive control, dynamic optimization, neural networks(NN)-based adaptive control, NN-based optimal control, and data-driven modeling and control.

Lab Website: http://www.sharmalabncsu.org/

Dr. Junfeng Sun is a full professor of biomedical engineering at School of Biomedical Engineering and Med-X Research Institute, Shanghai Jiao Tong University. He is IEEE Senior Member, Associate Editor of IEEE Transactions on Neural Systems & Rehabilitation Engineering (2022-) and Medical and Biological Engineering and Computing (2018-). His research interests include transcranial ultrasound stimulation techniques, neuroimaging techniques and analysis methods, and applications of these techniques to cognitive function and therapeutic intervention for brain diseases including depression, schizophrenia, and stroke.  He has published more than 70 papers in SCI journals.

Dr. Yu Sun is a Research Professor in the Department of Biomedical Engineering at Zhejiang University and is also affiliated with the Department of Radiology, the Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, China.  Dr. Sun’s research emphasis has been placed on the integration of the neural engineering, cognitive sciences, and virtual reality in service of insights into functions of the brain, cognition, and behavior. In particular, his research work of brain connectome studies of neuroergonomics and brain state monitoring has provided nascent insights into the neural mechanisms of mental workload/fatigue. Another area of interest is brain-computer interface and its clinical applications such as neural rehabilitation. In academic service, Dr. Sun is also an associate editor of the journal Medical & Biological Engineering & Computing (MBEC), and a youth corresponding expert of the journal Engineering.

Dr. Carmen Vidaurre is Ramon y Cajal fellow at the public University of Navarre, Dp of Statistics, Informatics and Mathematics, in Spain. From 2008 to 2016, she was a member of the Machine Learning Group at TU-Berlin, Berlin, Germany, where she was in charge of several national and international research projects. Between 2006 and 2008, she was Marie Curie fellow at the IDA group of the Fraunhofer Institute in Berlin, Germany. In 2006 she was post-doc researcher at CIMA in Pamplona, Spain. From 2002 to 2005 she was guest researcher at the TU-Graz, Institute of Biomedical Engineering, in Austria, where she pursued her PhD in the field of Brain-Computer Interfacing.

Her research interests are about the development of optimized multimodal methods for the understanding of motor control and their application to functional motor rehabilitation. She is also interested in the development of principled optimized procedures to ease the processing of neuroscientific data and to increase our understanding of the nervous systems.

Yiwen Wang received B.S. and M.S. degrees from University of Science and Technology of China (USTC), Hefei, Anhui, China respectively. She received a Ph.D. degree from University of Florida, Gainesville, FL, USA. Shee joined as an associate professor at Zhejiang University, Hangzhou, China.  She is now an associate professor with substantiation at the Department of Electronic and Computer Engineering, Department of Chemical and Biological Engineering, the Hong Kong University of Science and Technology.

Her research interests are in neural decoding of brain-machine interfaces, adaptive signal processing, computational neuroscience, and neuromorphic engineering. She serves as the Chair of the IEEE EMBS Neural Engineering Tech Committee, the chair of the IEEE BRAIN publication subcommittee, and the board member of Brain Computer Interfaces Society. She is the Editor-in-Chief of the IEEE Brain Newsletter. She also serves on the editorial board of the Journal of Neural Engineering, and is the associate editor of Frontiers in Human Neuroscience (Brain-Computer Interfaces), an associate editor of the IEEE Transactions on Neural Systems and Rehabilitation Engineering, and an associate editor of the IEEE Transactions on Cognitive and Developmental Engineering. She was recognized as IEEE EMBS distinguished lecturer in 2022, and received IEEE EMBS distinguished service award in 2023. She holds two US patents and has authored more than 100 peer-reviewed publications.

James Weiland received his B.S. in Electrical Engineering from the University of Michigan in 1988. After 4 years in industry with Pratt & Whitney Aircraft Engines, he returned to Michigan for graduate school, earning degrees in Biomedical Engineering (M.S. 1993, Ph.D. 1997) and Electrical Engineering (M.S. 1995). He joined the Wilmer Ophthalmological Institute at Johns Hopkins University in 1997 as a postdoctoral fellow and, in 1999, was appointed an assistant professor of ophthalmology at Johns Hopkins. Dr. Weiland was appointed assistant professor at the Doheny Eye Institute-University of Southern California in 2001, and was promoted to Professor of Ophthalmology and Biomedical Engineering in 2013. In 2017, Dr. Weiland was appointed as Professor of Biomedical Engineering (Medical School) and Ophthalmology & Visual Sciences at the University of Michigan. Dr. Weiland has over 100 peer-reviewed articles. Dr. Weiland’s research interests include retinal prostheses, neural prostheses, electrode technology, visual evoked responses, implantable electrical systems, and wearable visual aids for the blind. He is a Fellow of the American Institute of Medical and Biological Engineering and a Fellow of the IEEE.

Dr. Wang received his PhD in Computer Science and Engineering from Zhejiang University, China in 2007. From 2007 to 2010, he worked as a postdoctoral fellow at the Department of Information Engineering, The Chinese University of Hong Kong. Currently, he holds the position of Professor at the College of Computer Science and the Qiushi Academy for Advanced Studies, Zhejiang University. His research interests lie in the areas of brain-computer interface, artificial intelligence, and machine learning. Dr. Wang’s research aims to improve the quality of life for people with tetraplegia by enabling direct cortical control of robotic devices, and to enhance the quality of life for patients with treatment-resistant epilepsy or depression through the development of closed-loop brain stimulation methods.

Dr. Wong’s research interests are broadly separated into neural prostheses and systems neuroscience. In the field of neural prostheses, Dr Wong is interested in brain machine interfaces for upper limb movement control, cortical and retinal stimulation studies (Bionic vision), improved cochlear implant fitting techniques, new electrode technologies and the general use of local field potentials to improve neural prostheses. On the basic neuroscience side, Dr Wong studies the role of the local field potentials in communication across brain areas and in multi-effector decision making, reward learning and movement planning. This is done with a mix of recording techniques from in vivo electrophysiology, to EEG, MEG and fMRI.

Dr. Wu received his PhD in Electrical Engineering from the University of Southern California. He is now Professor in the School of Automation, Huazhong University of Science and Technology, Wuhan, China, and directs its Brain-Computer Interface and Machine Learning Lab. His research interests include affective computing, brain-computer interfaces, computational intelligence, and machine learning. He has published over 100 papers in these areas. He is also an Associate Editor of the IEEE Computational Intelligence Magazine, and the IEEE Transactions on Human-Machine Systems.

Dingguo Zhang is with Department of Electronic & Electrical Engineering, University of Bath, UK. His research interests include rehabilitation and assistive robotics, brain-computer interfaces and human-machine interfaces, biomechatronics and neuroprostheses. He serves as an Associate Editor for some high-profile journals including IEEE Transactions on Neural Systems & Rehabilitation Engineering, IEEE Transactions on Medical Robotics and Bionics, IEEE Trans. Human-Machine Systems, etc. He is a senior member of IEEE (EMBS, RAS, SMC), and serves in three technical committees (BioRob, TST, BMI) of EMBS and SMC. He was a Board Member of International Society of Functional Electrical Stimulation (IFESS) and a Youth Commission Member of International Society of Bionic Engineering (ISBE). He has authored over 180 papers, and some were published in top biomedical and robotic journals.

Mingming Zhang (Senior Member, IEEE) received the Ph.D. degree in mechanical engineering from the University of Auckland, New Zealand, in 2015. Since August of 2018, Dr Zhang has joined and directed the Brain-Robot Rehabilitation Technology Lab at Southern University of Science and Technology. His research interests are to develop task-oriented rehabilitation robots with haptic force feedback and explore neural intention decoding from biomedical information, aiming to improve the accuracy and clinical effect of robot-assisted rehabilitation He has authored over 90 academic papers on reputable journals or conferences, such as IEEE TFS, TII, TIE, TASE, TIM, TNSRE, RAL, JBHI, TBME, JNE, J NEUROENG REHABIL, J BIOMECH, ICRA/IROS. Prof. Zhang has been currently serving as the associate editor for IEEE RAL and IEEE TMRB.

Dr. Yingchun Zhang is a Professor in the Department of Biomedical Engineering, the Desai Sethi Urology Institute and the Miami Project to Cure Paralysis at the University of Miami. Dr. Zhang is a recipient of a NIH Pathway to Independence (K99/R00) award and a recipient of the 12th Annual Delsys Prize for Innovation in Electromyography. He serves as an academic editor/reviewer for a number of peer-review scientific journals, and a grant reviewer for NIH, NSF, AHA and UK Cancer Research. The long-term goal of Zhang’s research is to advance precision diagnosis/phenotyping and mechanism-driven interventions of pain and movement disorders associated with neurological and neuromuscular diseases, via multimodality assessment of the dynamics of brain and muscle activation as well as brain-muscle interaction. This goal will be achieved through the fusion of multimodal neuroimaging, neuroengineering and neuromodulation techniques. His current work involves high-impact research for quantitative and precision diagnosis, phenotyping and personalized treatment of a variety of neurological/neuromuscular diseases including the Depression, Alzheimer’s disease, Pain including Chronic Pelvic Pain and Movement Disorders.

Dr. Zheng’s research focuses on human-machine interaction (HMI). Specifically, her work explores the fundamental mechanisms and applications of HMI in the contexts of developmental disabilities, aging, and substance use. Her research is collaborative, involving partnerships with researchers in psychology, medicine, and social sciences. Dr. Zheng leads the Intelligent Interaction Research lab. She has served on the organizing and technical program committees for multiple IEEE and other conferences. She has also served as a reviewer for numerous IEEE Transactions and medical research journals.

Ping Zhou is a Professor in University of Health and Rehabilitation Sciences (tentative name), Qingdao, China. As the first professor joining this university still in preparation, he helps plan and found its biomedical/rehabilitation engineering programs. Before current position he was a professor in Physical Medicine and Rehabilitation at University of Texas Health Science Center at Houston (UTHealth). Before joining UTHealth, he spent most time in Rehabilitation Institute of Chicago and Northwestern University, progressively as PhD student, postdoctoral fellow, research assistant professor, and research associate professor. His research interests include biomedical signal processing (particularly EMG), motor unit analysis, electrodiagnosis of neuromuscular diseases, myoelectric prosthesis control, and neurorehabilitation robotics. He has published over 140 peer-reviewed journal articles. He serves as Associate Editor for IEEE-TBME, IEEE-TNSRE, Journal of NeuroEngineering and Rehabilitation, Frontiers in Neurology, BioMed Research International, and Journal of Healthcare Engineering.