Associate Editors

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.

Joseph Bamidele Awotunde is a Senior Lecturer in the Department of Computer Science at Faculty of Information and Communication Science, University of Ilorin, Ilorin, Nigeria. He received his Ph.D. and M.Sc. degrees in Computer Science from University of Ilorin, Ilorin, Nigeria, and his B.Tech. in Mathematics and Computer Science from Federal University of Technology, Minna, Nigeria. His research interests include Artificial Intelligence, Machine Learning, Deep Learning, Internet of Things, Internet of Medical of Things, Wireless Body Sensor Network, Cybersecurity, Information Security, Social Computing, Biomedical, and BioinformaticsInformation Security, Cybersecurity, Bioinformatics Artificial Intelligence, Internet of Medical Things, Wireless Body Sensor Networks, Wireless Networks, Telemedicine, m-Health/e-health, Medical Imaging, Software Engineering, and Biometrics. He has authored over 150 academic papers on reputable journals, edited books, or conferences, such as Elsevier, Springer, Taylor Francis, Hindawi etc.

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.

He obtained a degree in Electronic (Biomedical) Engineering from the University of Genoa, Italy, in 1998, then a Ph.D. in Artificial Intelligence (Mathematical Logic) from the School of Informatics of the University of Edinburgh, Scotland, in 2005. He then turned his attention to assistive robotics and 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. Since 2021 he is a full professor in assistive robotics at the Friedrich-Alexander University of Erlangen-Nuremberg, Germany. He has (co)authored some 150 scientific papers, is involved in a few national and international research projects, and regularly serves for international editorial boards and committees.

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. 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.

Professor Domingo’s goals are to elucidate the best methods for locomotor rehabilitation after neurological injury based on principles of biomechanics, motor learning and control. She seeks to understand how different types of error impact motor learning of walking balance in intact and disordered nervous systems. Related to this, she is interested in the role of proprioceptive sense in the recovery of balance and skilled walking function. She aims to use this knowledge to develop and optimize the use of physical guidance and rehabilitation robotics in restoring gait and balance in individuals with spinal cord injury and in older adults. She is also interested in improving the health and wellness of disabled populations using wearable sensors.

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.

Professor Deborah Falla’s research utilises state of the art electrophysiological measures to evaluate the control of human movement and how it is affected or adapted in response to various states (e.g. pain, injury, fatigue, and exercise). She has published over 230 papers in international, peer-reviewed journals and more than 300 conference papers/abstracts including over 30 keynote lectures. She has received several recognitions and awards for her work including the German Pain Research Prize in 2014, the George J. Davies – James A. Gould Excellence in Clinical Inquiry Award in 2009 and the Delsys Prize for Electromyography Innovation in 2004. She is an author of three textbooks including the latest entitled “Management of neck pain disorders: a research informed approach” (Elsevier, 2019). From 2016 to 2018, she was the President of the International Society of Electrophysiology and Kinesiology (ISEK).

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.

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. Gutierrez Farewik is a Professor of Biomechanics at the Department of Engineering Mechanics at KTH Royal Institute of Technology, and leads the KTH MoveAbility Lab.  She also has an affiliation to the Department of Women’s and Children’s Health at Karolinska Institutet. Her research interests span several biological scales, and include modelling, predictive simulation and device design for children and adults with motor disorders. She and her group combine experiments with numerical modelling to study the short- and long-term consequences of motor disorders, as well as the factors that influence a person’s movement strategy. They are developing biosignal-controlled assistive-as-needed devices for the lower extremities for applications in neurorehabilitation and habilitation, with a goal to increase movement efficiency, preserve available neural pathways and complement the user’s functional abilities.

Dr. Huang is a Professor of Biomedical Engineering in the Joint Department of Biomedical Engineering at the University of North Carolina at Chapel Hill (UNC) and North Carolina State University (NCSU) and the Director of the NCSU/UNC Closed-Loop Engineering for Advanced Rehabilitation (CLEAR) Core. Dr. Huang’s research interest lies in neural-machine interfaces for prostheses and exoskeletons, wearer-robot interaction, adaptive and optimal control of wearable robots, and human movement control. She pioneered EMG-based neural interface for robotic prosthetic legs. This work has won her the Delsys Prize in 2008. Her lab also invented novel control for multifunctional prosthetic arms based on EMG-driven musculoskeletal models. Her current research focuses on (1) optimal adaptive control of wearable robots with human-in-the-loop, (2) fault-tolerance in wearer-robot interaction, and (3) shared control of artificial limbs. She is a senior member of IEEE and member of the Society for Neuroscience and BMES.

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.

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. 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. Uttama Lahiri is a faculty at Electrical Engineering with research interests in Virtual Reality based Human Computer Interaction used in Neuro-rehabilitation and Affective computing. In her research, she uses Eye Tracking, Physiology-based modeling, Signal Processing and Artificial Intelligence to develop Adaptive Physiology-sensitive Rehabilitation and Intervention techniques. She loves to work on application-oriented projects and solutions for children with Autism and Stroke-rehabilitation platforms for the elderly. She is leading the Intelligent Rehabilitation and Affective Computing Systems (IRACS) Laboratory at IIT Gandhinagar. She enjoys teaching both fundamental and advanced technical concepts of engineering to the undergraduate and the post-graduate students.

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.

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.

Ting Li is a full professor and director of lab for intelligent diagnosis and treatment technology in Institute of Biomedical Engineering, Chinese Academy of Medical Sciences & Peking Union Medical College. She is also the director of the provincial/ministerial level center for Tianjin Medical Electronic Diagnosis & Treatment Technology Engineering. She has engaged in brain-inspired intelligence and non-invasive photoelectric monitoring & modulation in deep tissue. Her main achievements included the computing model and software of 4D photon migration in voxelized complex-structure tissue, multimodal neural information acquisition and modulation technology for BCI robot, and instrumentation of monitoring deep tissue hemodynamics for neural ICU & rehabilitation. She has presided ~20 projects, such as founded by NSFC and Beijing Major Instrumentation grants. She has won the Melvin H. Knisely Award (1/global per year, Only Chinese winner in the past 41 years), global Nirfast Award, Top10 Outstanding Sci.&Tech. scholars of CIE (the youngest winner in recent 6 years), National Youth Talents, ISO/IEC/IEEE standardization experts, the first batch of National Health Science Popularization experts, National Innovative Medical Device Review Expert, Tianjin outstanding youth, the director of Tianjin innovation team, and Tianjin young & middle-aged Sci.&Tech. leaders, etc.

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.

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.

Prof. Dr. Natalie Mrachacz-Kersting member of IEEE, received her Ph.D. degree in biomedical engineering from Aalborg University, in 2005, and currently holds the Chair for Neuroscience and Neuroscience in Sport at the Albert-Ludwigs University of Freiburg. She is the Practitioner Representative for the IEEE Engineering Medicine and Biology Society, Chair of the IEEE WI(BM)E and on the Initiative Steering Committee of the IEEE Brain. She has previously held positions at Aalborg University, Denmark, FH Dortmund and at the University of Auckland, New Zealand. Natalie does research in Medical Technology, Biomedical Engineering and Neuroscience. She has authored over 80 articles in peer-reviewed journals, over 130 conference articles/abstracts, ten book chapters and one book. She is working on several projects specifically within the area of Brain-Computer-Interfaces (BCIs) involving patient populations such as those suffering from stroke or ALS. Dr. Mrachacz-Kersting received several awards including the international BCI award in 2017.

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.

Ilana Nisky is an associate professor in the Department of Biomedical Engineering, Ben-Gurion University of the Negev, where she is the head of the Biomedical Robotics Lab. She is also the head of the Israel-Italy Virtual Lab on Artificial Somatosensation for Humans and Humanoids. She is the recepient of the 2019 IEEE RAS Early Academic Career Award, the prestigious Alon Fellowship for young faculty from the Israeli Council for High Education, and the Marie Curie International Outgoing Fellowship from the European Commission. Her research interests include human motor control, haptics, robotics, human and machine learning, teleoperation, and robot-assisted surgery and rehabilitation, and her lab is supported by competitive grants from the Israeli Science Foundation, the Israel-US Binational Science Foundation, and the Ministry of Science and Technology. Nisky has authored more than 70 scientific publications in peer-reviewed journals and conference proceedings, and numerous abstracts in international conferences. She hopes that her group’s research will improve the quality of treatment for patients, will facilitate better training of surgeons, advance the technology of teleoperation and haptics, and advance our understanding of the brain.

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. Ram Bilas Pachori is currently a Professor in the Department of Electrical Engineering at Indian Institute of Technology Indore, Indore, India. He has authored 233 publications which include journal papers (143), conference papers (66), books (06), and book chapters (18). His publications have around 9000 citations with h index of 50 (Google Scholar, September 2021).
He works on the development of new methodologies based on the signal processing and machine learning for analysis and classification of biomedical signals and images (EEG, ECG, PCG, CT, X-ray, MRI, MEG, EMG, fundus images, lung sounds, etc.) with applications to diagnosis of various diseases like epilepsy, glaucoma, coronary artery disease, diabetes, congestive heart failure, septal defects, myocardial infarction, atrial fibrillation, amyotrophic lateral sclerosis, sleep disorders, alcoholism, human emotions, etc.
His broad research interests are in the areas of Signal and Image Processing, Biomedical Signal Processing, Non-stationary Signal Processing, Speech Signal Processing, Brain-Computer Interfacing, Machine Learning, and Artificial Intelligence in Healthcare.

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. Philip Requejo is the Director of the Rehabilitation Engineering Department and Associate Director of the Pathokinesiology Laboratory at Rancho Los Amigos National Rehabilitation Center. He serves as a faculty member at the University of Southern California in the Departments of Biomedical Engineering, Human and Evolutionary Biology, and Biokinesiology and Physical Therapy. He also is the Director of Rehabilitation Engineering Department and Co-Director of the RERC on Technologies for Successful Aging with Disability at the Model Systems Knowledge Translation Center (MSKTC). The MSKTC is a national center that helps facilitate the knowledge translation process to make research meaningful to those with Spinal Cord Injury (SCI), Traumatic Brain Injury (TBI) and Burn Injury (Burn). He received his undergraduate degree in Electrical Engineering and PhD degree in Kinesiology from the University of Southern California. He is a faculty in the Department of Biomedical Engineering and Department of Kinesiology, and Department of Biokinesiology and Physical Therapy at USC. His research primarily falls into several broad areas of rehabilitation engineering and biomechanics research; focusing on the design, analysis, and implementation of technologies to preserve and enhance mobility in those with spinal cord injury- particularly focusing on the biomechanics of the weight-bearing shoulder to prevent and treat shoulder pain.

Dr. Robinson is a Senior Research Fellow and Program Manager at the Centre for Brain Computing Research, School of Computer Science and Engineering, Nanyang Technological University, Singapore. Her research interests include Brain-Computer Interfaces (BCI), neural signal processing and machine learning for BCI, and applications of BCI in neurorehabilitation. Dr. Robinson’s research focuses on developing clinically feasible neurotechnology solutions for motor rehabilitation, cognition enhancement, and emotion regulation. Her research in motor BCI aims to reconstruct fine movement parameters from non-invasive neural signals, understand underlying neuromotor control mechanisms, and leverage this to enhance motor learning.

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. Mridu Sahu completed her graduation in Computer Science and Engineering from Maulana Azad National Institute of Technology, Bhopal in 2004. She completed her postgraduation Master of Technology in Computer Science and Engineering from RIT, Raipur in 2011 and completed her Ph.D. in Computer Science and Engineering from the National Institute of Technology Raipur, India in 2018. She has over 15 years of experience in teaching, currently working as an Assistant Professor in the Department of Information Technology at NIT Raipur. She has published 15 research articles in various reputed journals including SCI/SCIE and more than 22 papers in conferences. She is the author of the book Brain and Behavior Computing published by CRC Press and has more than 10 book chapters published by renowned publishers in the fields of Data Mining, Brain-Computer Interfaces, Sensor Devices, Visual Mining Techniques, and Earth Science etc. Five of her research papers received “Best Paper Awards” at conferences and she was awarded the Best Researcher Award by the VDGOOD Professional Association in 2022.

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. 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. Shull’s research interests include human performance measurement and analysis, wearable sensors, biomechanics of locomotion, and machine learning. His laboratory develops wearable systems to explore principles of human movement and movement modification. His group combines robotic, haptic, and biomechanics principles to create unique sensors, real-time models, sensor fusion algorithms, and novel feedback devices. They focus on human movement in laboratories, in clinics, and in natural environments such as a home or office. Target applications are in medicine such as osteoarthritis and stroke, and in athletics such as basketball and running.

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.

Karen L. Troy directs the Musculoskeletal Biomechanics Laboratory, where she investigates questions related to musculoskeletal health and structure, physical activity, and biomechanics, in healthy and clinical populations. She has expertise in computational biomechanics and finite element modeling, aging and fall avoidance, and medical imaging. She has worked on clinical trials targeting bone health in both healthy women and people with spinal cord injury. She collaborates with physicians in the areas of orthopaedic trauma, radiology, rheumatology, and physical medicine and rehabilitation.

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.

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.

Dr. Yao’s research interests include EEG inverse and forward, quantitative EEG (qEEG), simultaneous EEG and fMRI, and Brain-Apparatus Conversation (Bacomics). He got his first PhD in Applied Geophysics (1991) at Chengdu University of Technology, and second PhD in Biomedical Science (2005) at Aalborg University. He is a full professor since 1995, a Changjiang Scholar Professor (2006), and the Director of Key Laboratory for NeuroInformation of Ministry of Education of China, and the Director of International Joint Research center for Neuroinformation of Ministry of Science and Technology of China. He is an AIMBE Fellow (2017) and “Roy John Award” winner (2018).

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 TNSRE.

Dr. Yingchun Zhang is a Professor in the Department of Biomedical Engineering at the University of Houston. 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.

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.