Dr. Mo Rastgaar is a Professor at Purdue Polytechnic Institute, Purdue University. He holds a PhD in Mechanical Engineering from Virginia Tech (2008) and completed a postdoctoral fellowship at MIT's Newman Laboratory for Biomechanics and Human Rehabilitation. He leads the Human-Interactive Robotics Lab (HIRoLab), focused on assistive and rehabilitation robots for enhanced mobility, particularly lower-extremity devices. His research emphasizes understanding agile gait dynamics through human experiments and modeling. Research interests include assistive robotics, cyber-physical systems, dynamics, and control systems. Notable awards include the 2014 NSF CAREER Award. He has secured grants such as the 2019 NRI Collaborative Grant on robotic ankle prosthetics and 2020 grants for undersea infrastructure. Dr. Rastgaar's work bridges biomechanics, robotics, and clinical applications, advancing prosthetic designs and human-robot interaction. Key contributions include developing steerable powered ankle-foot prostheses and exploring multi-robot systems for underwater exploration. His labs integrate interdisciplinary approaches to solve complex mobility challenges, emphasizing both technical innovation and real-world clinical impact.
Silvestro Micera is a Full Professor at the Swiss Federal Institute of Technology Lausanne (EPFL) and holds the Bertarelli Foundation Chair in Translational Neuroengineering. He directs the Translational Neural Engineering Laboratory and teaches courses including Neural signals and signal processing and Translational neuroengineering . His research bridges neural interfaces, robotics, and neuroprosthetics to restore motor functions in spinal cord injuries, stroke, and amputations. Micera's research integrates implantable neural interfaces, robotic rehabilitation, and hybrid neuro-prosthetic systems. Key focus areas include: Robotic neurorehabilitation for mobility restoration Neural control mechanisms in movement CNS/PNS neural interface development Bioelectronic modulation for sensory feedback His recent publications emphasize machine learning-driven motor recovery prediction, closed-loop sensory feedback systems, and minimally invasive neuroprosthetics. Trends include AI-optimized stimulation protocols, multimodal data fusion for rehabilitation, and clinical translation of neural bypass technologies. Awards: IEEE EMBS Early Career Achievement Award (2009) IEEE EMBS Technical Achievement Award (2021) Micera leads EU-funded projects such as TIME, CLONS, and NeuWalk, focusing on neural prostheses. He advises 8 current and 18 former PhD students in neuroengineering. His lab collaborates with MIT, Harvard, and industry partners (e.g., Plexon) to advance translational neurotechnologies.
Michel M. Maharbiz is a Professor in the Department of Electrical Engineering and Computer Science at the University of California, Berkeley. He leads research on miniaturized bioelectronic interfaces, including neural dust implants and cyborg insects. He holds affiliations with the Berkeley Sensor & Actuator Center (BSAC), Center for Neural Engineering & Prostheses (CNEP), and SWARM Lab. His education includes a Ph.D. in EECS from UC Berkeley (2003) and a B.S. in EE from Cornell University (1997). Maharbiz's research integrates MEMS, ultrasonic systems, and synthetic biology to develop wireless neural interfaces, implantable sensors, and biohybrid devices. Key focus areas are neural dust technology for peripheral nerve recording, magnetoelastic strain sensors for medical applications, and electrochemical biosensing using bacterial flagellar motors. His publications emphasize neural interfaces, ultrasonic implants, and biomedical monitoring. Recent articles explore ultrasonic power delivery (2025), radiation detectors for oncology (2025), and fracture-healing smart plates (2019). Trends include miniaturization of wireless implants, closed-loop therapeutic systems, and novel biomaterials. Scientific Awards: McKnight Technological Innovations in Neuroscience Award (2017) Chan-Zuckerberg Biohub Investigator (2017) NSF CAREER Award (2009) MIT TR10 Top Emerging Technology (2009) Bakar Fellows Spark Award (2012) He directs the Maharbiz Lab, advancing neural dust and bioelectronic interfaces. Projects include impedance-based fracture monitoring, carbon fiber neural arrays, and hernia repair sensors. Funding includes NSF and industry partnerships for implantable device development.
Sohmyung Ha is an Associate Professor of Electrical Engineering and Bioengineering at NYU Abu Dhabi and holds a Global Network position at NYU Tandon School of Engineering. He leads the Integrated BioElectronics Laboratory, focusing on advancing silicon integrated technologies for biomedical applications such as implantable devices and wearable sensors. His expertise spans biomedical circuits, neural interfaces, and wireless power systems. Education: MS (2004, KAIST), PhD (2016, UC San Diego) with a Best Thesis Award. Prior industry experience includes analog circuit design at Samsung Electronics (2006-2010). Academic affiliations include NYU Abu Dhabi, NYU Tandon, and global collaborations. Research interests include high-performance biomedical sensors, neural prosthetics, and energy-efficient bioelectronic systems. Notable achievements include a Best Paper Award (ISCAS 2024) and innovations in impedance spectroscopy and neural interface ICs. Current projects emphasize closed-loop neural interfaces, subcutaneous glucose monitoring, and retinal prostheses. His lab develops miniaturized, power-autonomous systems for healthcare applications.
Rikky Muller is an Associate Professor of Electrical Engineering and Computer Sciences at UC Berkeley, holding the S. Shankar Sastry Professorship in Emerging Technologies. She is Co-director of the Berkeley Wireless Research Center (BWRC), a Core Member of the Center for Neural Engineering and Prostheses (CNEP), and an Investigator at the Chan-Zuckerberg Biohub. Her research focuses on implantable/wearable medical devices, low-power wireless systems, and neurotechnology for neurological applications. Education: PhD (2013), UC Berkeley; BS and M.Eng. (2004), MIT, all in EECS. Prior roles include IC designer at Analog Devices and co-founder of Cortera Neurotechnologies (acquired). Research interests include neural interfaces, closed-loop neuromodulation, and biomedical microelectronics. Notable contributions include Neural Dust (ultrasonic implants), wireless EEG systems, and seizure prediction hardware. Awards: MIT TR35 Innovator, NAE Gilbreth Lectureship, NSF CAREER Award, IEEE SSCS New Frontier Award Grants: Bakar Fellows, Hellman Fellowship, NSF CAREER Labs: Muller Lab (UC Berkeley EECS), Chan-Zuckerberg Biohub collaborations
Levi J Hargrove is an Associate Professor at Northwestern University, holding dual appointments in the Department of Physical Medicine and Rehabilitation at the Feinberg School of Medicine and the Department of Biomedical Engineering at the McCormick School of Engineering. He is also a Research Scientist at the Center for Bionic Medicine at Shirley Ryan AbilityLab. His work focuses on developing neural control systems for prosthetic limbs, particularly in myoelectric control and pattern recognition, aiming to create clinically viable solutions for amputees. Education: BScE in Electrical Engineering, University of New Brunswick, 2003 MScE in Electrical Engineering, University of New Brunswick, 2005 PhD in Electrical Engineering, University of New Brunswick, 2008 Research Interests: Signal processing, pattern recognition, myoelectric control of powered prostheses, and neural interfaces for bionic limbs. His lab translates research into clinical applications, such as the first thought-controlled bionic leg and Coapt LLC's pattern recognition systems for upper-limb prosthetics. Awards: 2017 American Academy of Orthotists and Prosthetists Research Award 2014 Department of Defense Outstanding Research Team Award 2015 Collaboration Award from Chicago Innovation Grants: Manages a $25 million portfolio from federal, military, and philanthropic sources. Key projects include NSF-funded research on human-robot interaction and DoD grants for prosthetic innovation. Labs: Leads the Regenstein Foundation Center for Bionic Medicine and collaborates with the Neurorehabilitation and Neural Engineering Lab. His work emphasizes translational research, bridging engineering and clinical practice.
Jose M. Carmena is the Chancellor's Professor of Electrical Engineering and Neuroscience at the University of California-Berkeley and Co-Director of the Center for Neural Engineering and Prostheses (CNEP). His research focuses on brain-machine interfaces (BMIs), neuroprosthetics, and sensorimotor learning mechanisms. Ph.D., Robotics, University of Edinburgh (2002) M.S., Artificial Intelligence, University of Edinburgh (1998) M.S., Electrical Engineering, University of Valencia (1997) B.S., Electrical Engineering, Polytechnic University of Valencia (1995) Dr. Carmena's work bridges neural engineering and systems neuroscience, investigating corticostriatal plasticity, wireless neural recording systems (e.g., neural dust), and closed-loop BMI adaptation. His publications reveal expertise in Neuroprosthetic Algorithms , Wireless Neural Interfaces , and Sensorimotor Learning with applications in chronic neuroprosthetic systems. McKnight Technological Innovations in Neuroscience Award (2017) IEEE Fellow (2017) NSF CAREER Award (2010) Sloan Research Fellow (2009) Hellman Fellow (2007) His advisees include Paul Botros, Archit Gupta, and Vivek Athalye. Dr. Carmena has published extensively in journals like Nature , Neuron , and Nature Neuroscience , developing technologies such as ultrasonic neural dust for cortical recording and adaptive control algorithms for prosthetics.
Mario A. Svirsky is the Noel L. Cohen Professor of Hearing Science and Professor of Neuroscience at NYU Grossman School of Medicine. He leads the Laboratory for Translational Auditory Research, focusing on auditory neural prostheses like cochlear implants and their impact on speech perception and neuroplasticity. His work bridges clinical care and scientific discovery, addressing how the brain adapts to sensory deprivation and degraded auditory input. Education: PhD in Biomedical Engineering from Tulane University (1988). Postdoctoral training at MIT and prior academic appointments at Indiana University and Purdue University before joining NYU in 2005. Research: Explores cochlear implant performance optimization, speech perception in hearing-impaired individuals, and neuroplasticity mechanisms. Collaborates with the Froemke Lab on animal models of cochlear implantation. Active in developing computational models and signal processing techniques to improve implant efficacy. Funding: Principal investigator on multiple NIH grants (e.g., R01 DC016839, R01 DC016834) and industry partnerships. His lab’s work has advanced clinical management strategies for cochlear implant users, including those with contralateral hearing aids. Labs/Teams: Directs the Laboratory for Translational Auditory Research, collaborating with multidisciplinary teams including engineers, neuroscientists, and clinical audiologists. Mentors postdocs, audiologists, and medical students in auditory research.
Ramana Vinjamuri is an Associate Professor in the Department of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County (UMBC). He holds a secondary appointment as Visiting Professor at the Indian Institute of Technology, Hyderabad, India. His academic journey includes a Ph.D. in Electrical Engineering from the University of Pittsburgh (2008), M.S. in Bioinstrumentation from Villanova University (2004), and B.Tech. in Electrical and Electronics Engineering from Kakatiya University (2002). Dr. Vinjamuri's research focuses on Brain-Machine Interfaces (BMIs) for upper-limb prostheses control , neuroprosthetics and exoskeletons , machine learning in motor control , and neurophysiological signal processing . His work extends synergy-based models to control 37-dimensional hand movements, addresses human-robot interaction through emotionally intelligent systems, and develops neurotechnologies for substance use disorder using wearable sensors and AI. NSF CAREER Award (2019) NSF IUCRC BRAIN Center Planning Grant (2020) Harvey N Davis Distinguished Teaching Assistant Professor Award (2018) His publications demonstrate expertise in EEG and EMG signal analysis , deep learning for motor decoding , synergy modeling , and humanoid robot control . The Vinjamuri Lab at UMBC involves graduate, undergraduate, and high school researchers, with international collaborations in India and the US.
Aaron Young is an Associate Professor in the Woodruff School of Mechanical Engineering at Georgia Institute of Technology and a program faculty member in the Biomedical Engineering School. He serves as Director of the Exoskeleton and Prosthetic Intelligent Controls (EPIC) Lab, focusing on robotic human augmentation through advanced control systems for prosthetics and exoskeletons. Education: Postdoctoral Fellow, University of Michigan (2014-2016) Ph.D., Northwestern University (2014) M.S., Northwestern University (2011) B.S., Purdue University (2009) Dr. Young's research addresses clinically viable control systems for wearable robotic devices, emphasizing intent recognition , EMG signal processing , and machine learning integration. His work targets mobility impairments from stroke, amputation, cerebral palsy, and neurological injuries, aiming to reduce metabolic costs, restore natural biomechanics, and enhance community ambulation. Key innovations include data-driven control frameworks , biomechanical terrain adaptation , and anthropometry-based personalization . His recent publications highlight advancements in deep learning for real-time biomechanics , EMG-informed joint estimation , and adaptive assistance systems . The EPIC Lab's facilities feature a terrain park with force plates , motion capture systems , and HumoTech simulation platforms for device testing. Scientific Awards: New Faces of Engineering (IEEE USA, 2017) Military Health System Team Award (2015) NSF Graduate Fellowship (2010) NDSEG Fellowship (2010) IEEE EMBC 3rd Place (2013) Projects include NSF-funded hip exoskeletons for stroke survivors, DoD-powered prostheses for amputees, and Pediatric knee exoskeletons for cerebral palsy. The lab cultivates interdisciplinary expertise in robotics , biomedical engineering , and human-machine interaction .
Matt Russell is a PhD candidate in Computer Science at Tufts University, focusing on Brain-Computer Interfaces (BCI) within the Human-Computer Interaction Lab. His research emphasizes measuring mental workload via fNIRS and EEG, with applications in LLM-based interfaces and BCI design. He has taught Data Structures (C++) twice as a professor and served as a teaching assistant for multiple computer science courses. His work bridges neuroscience and engineering to enhance adaptive interface technologies. Education: PhD Candidate in Computer Science, Tufts University Research Interests: Russell’s multidisciplinary research explores implicit BCI design, mental workload analysis, and neuroergonomics. Key areas include fNIRS/EEG-based state classification, LLM interface integration, and real-time BCI systems for memory enhancement. His studies often involve human subject trials to evaluate cognitive and physiological responses. Publications: His articles span 2011 to 2025, focusing on neuroimaging techniques (fNIRS/EEG), BCI innovation, and HCI applications. Recent work explores AI collaboration impacts and low-cost EEG systems for cognitive task decoding. Teaching & Advising: Russell has instructed Data Structures (C++) and supported courses in graphics, cybersecurity, and concurrency. He actively contributes to pedagogical efforts in computer science education. Labs & Projects: His research is conducted in the Human-Computer Interaction Lab at Tufts, with open-source projects hosted on GitHub.
Edward F. Chang, MD is a distinguished Professor and Chair of the Department of Neurological Surgery at the University of California, San Francisco (UCSF) School of Medicine. He co-directs the Center for Neural Engineering and Prostheses, a collaborative enterprise between UCSF and UC Berkeley, and leads the Chang Lab focused on speech neuroscience and neural engineering. As a practicing neurosurgeon, he specializes in treating adults with difficult-to-control epilepsy, brain tumors, trigeminal neuralgia, hemifacial spasm, and movement disorders. Dr. Chang's educational background includes a B.A. in Chemistry from Amherst College (1997), an M.D. from UCSF (2004), a Neurological Surgery residency at UCSF (2010), and a postdoctoral fellowship in Cognitive Neuroscience at UC Berkeley (2009). His research focuses on the brain mechanisms for speech, movement, and learning, with particular emphasis on advanced brain mapping methods to preserve crucial areas for speech and motor functions. He has pioneered work in speech neuroprostheses, developing technology that allows patients with paralysis to communicate through brain signals. His work integrates engineering, neurology, and neurosurgery to develop state-of-the-art biomedical technology to restore function for patients with neurological disabilities such as paralysis and speech disorders. Analysis of his recent publications reveals a strong trend toward developing advanced neuroprosthetic technologies, particularly speech decoding systems, and exploring the neural basis of speech production across multiple languages. His research also spans epilepsy surgery optimization, deep brain stimulation for psychiatric conditions, and molecular profiling of brain tumors. Blavatnik National Laureate for Life Sciences (2015) Elected to the National Academy of Medicine (2020) Inaugural Bowes Biomedical Investigator at UCSF HHMI Faculty Scholar Dr. Chang leads multiple NIH-funded research projects totaling millions of dollars, including a pilot clinical trial for speech neuroprosthesis and studies on the neural coding of speech across human languages. He has mentored numerous researchers in the field of neural engineering and speech neuroscience, though specific student names aren't listed in the provided materials. His work has resulted in groundbreaking technologies that have helped restore communication abilities to individuals with paralysis. As co-director of the Center for Neural Engineering and Prostheses, Dr. Chang leads a multidisciplinary team of engineers, neurologists, and neurosurgeons working at the intersection of neuroscience and technology. His lab has been instrumental in developing brain-computer interfaces that translate neural activity into speech, with recent publications demonstrating streaming brain-to-voice neuroprostheses that restore naturalistic communication.
Jon Sensinger is a Professor in the Department of Electrical and Computer Engineering at the University of New Brunswick and Director of the Institute of Biomedical Engineering (IBME). Based in R.N. Scott Hall 207, Fredericton, his research focuses on rehabilitation technologies. His work spans prosthetics, exoskeletons, computational motor control, and human-centered system optimization. The 'curiosity driven control' research stream explores adaptive interfaces that respond to user intent through novel learning algorithms. As IBME Director, he oversees interdisciplinary research bridging engineering, neuroscience, and clinical practice. This includes neural-machine interfaces, assistive device design, and rehabilitation robotics aimed at enhancing mobility and function.
Associate Professor Patrick Dumond holds a Ph.D., M.A.Sc., and B.A.Sc. from the University of Ottawa. He is affiliated with the Department of Mechanical Engineering, Faculty of Engineering. His research focuses on vibration/acoustic system design, inverse eigenvalue methods, biomechanical design, design theory, musical acoustics, and experiential engineering education. He actively contributes to the Centre for Entrepreneurship and Engineering Design (CEED) and advises students in engineering competitions. His work bridges mechanical engineering with biomedical and educational applications, emphasizing practical, hands-on learning. Education: All degrees earned at the University of Ottawa—Ph.D. (2015), M.A.Sc. (uOttawa), B.A.Sc. (uOttawa). Research interests include vibration systems, biomedical prosthetics (e.g., hip joint prostheses), and machine learning for fault diagnosis. He has published extensively on topics like bearing fault detection, data fusion, and educational program design. Professional Involvement: CEED co-development, advising student teams, and advancing multidisciplinary engineering education. Labs/Teams: Core contributor to the Centre for Entrepreneurship and Engineering Design (CEED).
Sean Meehan, PhD, serves as an Associate Professor in the Department of Kinesiology and Health Sciences, having joined the department in summer 2018 after previously holding an assistant professorship at the University of Michigan's School of Kinesiology from 2011 to 2018. His academic career focuses on elucidating neural mechanisms underlying skilled motor behavior and sensorimotor integration. Professor Meehan's research program investigates how the brain transforms sensory inputs into precise motor commands, with particular emphasis on circuit-level adaptations during skill acquisition and cognitive modulation through attention allocation. Utilizing transcranial magnetic stimulation (TMS) and electroencephalography (EEG), his work bridges fundamental neuroscience with clinical applications in brain injury rehabilitation, examining mechanistic changes in sensorimotor processing following acquired neurological damage. Analysis of his 2020-2025 publications reveals dominant research trajectories in concussion neurophysiology, neural plasticity in motor circuits, and attention-motor interactions. His studies consistently employ TMS to probe cortical excitability dynamics, with significant contributions to understanding sport-related concussion effects, cerebellar modulation of motor adaptation, and neurodevelopmental aspects of pediatric motor skills, demonstrating strong translational potential for rehabilitation protocols. Information regarding Professor Meehan's student advising responsibilities and external research grant funding was not available in the provided source material.
