Find Academic Supervisors

Behnaam AazhangView profile

Professor

• Signal and Data Processing
• Information Theory
• Neuroengineering
• +4 more

Behnaam Aazhang is the J.S. Abercrombie Professor of Electrical and Computer Engineering at Rice University and Director of the Rice Neuroengineering Initiative (NEI). He holds a B.S., M.S., and Ph.D. from the University of Illinois at Urbana-Champaign. His roles include leading the multi-university Rice Neuroengineering Initiative and directing the Center for Neuroengineering. He has held an Academy of Finland Distinguished Visiting Professorship (FiDiPro) at the University of Oulu (2006-2014) and received an Honorary Doctorate from the University of Oulu in 2017. Education: Ph.D. in Electrical Engineering, University of Illinois at Urbana-Champaign (1986) M.S. in Electrical Engineering, University of Illinois at Urbana-Champaign (1983) B.S. in Electrical Engineering, University of Illinois at Urbana-Champaign (1981) Research Interests: Dr. Aazhang’s work focuses on signal/data processing, information theory, and neuroengineering applications. Key areas include: Neuronal circuit connectivity and learning impacts Real-time closed-loop neuromodulation for neurological disorders (epilepsy, Parkinson’s, depression) Patient-specific cardiac pacing systems Cybersecurity in cloud computing Awards & Honors: 2022 Rice Outstanding Doctoral Thesis Advisor Award 2019 SIGMOBILE Test of Time Award 2017 Honorary Doctorate (University of Oulu) 2013 IEEE Communication Society Advances in Communication Award AAAS and IEEE Fellowships (2012 and 1999) Grants & Advising: His research is supported by multi-university collaborations and grants. He has advised numerous graduate students in electrical engineering and neuroengineering, though specific names are not listed here. Labs & Teams: Leads the Aazhang Lab and the Rice Neuroengineering Initiative, focusing on translational technologies for neurological and cardiac disorders, including non-invasive neuromodulation and cloud security systems.

Xilin LiuView profile

Assistant Professor

• Integrated Circuits
• Biomedical Engineering
• Brain-Machine Interfaces
• +5 more

Xilin Liu is an Assistant Professor at the Edward S. Rogers Sr. Department of Electrical & Computer Engineering (University of Toronto) and the Center for Advancing Neurotechnological Innovation to Application (CRANIA) . He obtained his PhD from the University of Pennsylvania and previously worked at Qualcomm Inc. in California. Expertise in integrated circuits and systems for brain-machine interfaces , neuromodulation , and edge AI Published in top venues including Nature Electronics , IEEE JSSC , and ISSCC Recipient of multiple best paper awards and IEEE Senior Member His research spans three main themes: High-speed data converters for wireless/wireline communication IC design for neural interfacing Accelerating machine learning via hardware Recent publications focus on closed-loop neuromodulation , ultra-wideband transceivers , and flexible biomedical sensors . These works integrate analog IC design , edge AI , and real-time neural interfacing across medical rehabilitation , parkinson's monitoring , and memory research . Awards include: IEEE Solid-State Circuits Society Predoctoral Achievement Award (2016) Best Paper Award at BioCAS (2015) ECE Department Teaching Award (2022) Multiple conference best paper finalists His lab collaborates with UHN , EMBS , and global institutions while maintaining strong commitments to equity, diversity, and inclusion (EDI) in research practices.

Timothy H. MurphyView profile

Professor

• Neuroscience
• Stroke Recovery
• Brain Circuit Mapping
• +5 more

Dr. Timothy H. Murphy is a Professor in the Department of Psychiatry at the University of British Columbia's Faculty of Medicine. He is also an Associate Member of the School for Biomedical Engineering and a Member of the Djavad Mowafaghian Centre for Brain Health. Dr. Murphy leads the Dynamic Brain Circuits in Health and Disease initiative and the Division of Neuroscience and Translational Psychiatry at UBC. Dr. Murphy received his Ph.D. from Johns Hopkins University in 1989 and his B.Sc. from Saint Mary's College Maryland in 1984. His research focuses on understanding brain circuit structure-function relationships in relation to stroke recovery, psychiatric disorders, and neurological diseases. He specializes in mesoscale imaging techniques to study cortical activity patterns and develop automated approaches for brain imaging and stimulation. His laboratory develops innovative tools including open-source hardware for automated mouse brain imaging, synthetic data generation for behavioral analysis, and chronic recording systems that enable simultaneous mesoscale cortical imaging with subcortical or peripheral nerve activity monitoring. Research from the Murphy Lab has significantly advanced our understanding of how brain circuits reorganize after stroke and in models of psychiatric disorders. Dr. Murphy's recent publications reveal trends in mesoscale cortical imaging, development of synthetic data for behavioral analysis, and exploration of circuit-level changes in neurological and psychiatric disease models. His work bridges basic neuroscience with potential clinical applications for stroke recovery and mental health treatments. Dr. Murphy has mentored numerous students and postdoctoral fellows who have gone on to successful careers in neuroscience and related fields. His laboratory has received funding to support innovative approaches to understanding brain circuit function and recovery mechanisms. The Murphy Lab maintains strong collaborative ties across UBC and develops open-source tools that are widely adopted by the neuroscience community. Their work on automated home-cage imaging systems, synthetic behavioral data generation, and chronic recording technologies represents significant methodological advances in the field.

• Neuroscience
• Sleep Research
• Neural Engineering
• +3 more

Dr. Manuel Carro Dominguez is a Researcher at the Department of Neural Control of Movement, ETH Zürich. His work focuses on understanding the neural mechanisms underlying sleep dynamics, arousal regulation, and their impact on motor performance and cardiovascular function. He specializes in techniques such as auditory stimulation, pupil-based neurofeedback, and EEG/ECG monitoring to explore sleep oscillations, cortical excitability, and their clinical applications. His research bridges neuroscience, biomedical engineering, and sleep medicine, with a particular emphasis on enhancing human physiology through targeted interventions during sleep. Key research interests include: sleep modulation via auditory stimuli, pupilometry as a marker of arousal states, and the development of medical devices for gas sensing and closed-loop biofeedback systems. His studies often integrate multidisciplinary approaches to address translational challenges in neurophysiology and cardiovascular health. Recent publications highlight advancements in auditory stimulation effects on cardiac function, the role of K-complexes in sleep dynamics, and the design of gas sensing technologies for biomedical applications. His work contributes to both fundamental neuroscience and applied biomedical engineering, aiming to improve clinical outcomes through innovative sleep-based interventions.

• Biomedical Engineering
• Neurorehabilitation Technology
• Biomedical Signal Processing
• +12 more

Professor Dario Farina is Chair in Neurorehabilitation Engineering at the Department of Bioengineering, Faculty of Engineering, Imperial College London. He has previously served as Full Professor at Aalborg University, Denmark, and at the University Medical Center Göttingen, Germany, where he founded and directed the Institute of Neurorehabilitation Systems. His research spans biomedical signal processing, neural control of movement, and neurorehabilitation technology, with extensive contributions to electromyography, motor unit analysis, and neural interfaces. Chair in Neurorehabilitation Engineering, Imperial College London Former Full Professor, Aalborg University and University Medical Center Göttingen Founder and Director, Institute of Neurorehabilitation Systems Key Affiliations: Centre for Neurotechnology, Artificial Intelligence Network, Robotics Forum, Neuromechanics and Rehabilitation Technology His research focuses on biomedical signal processing , neural control of movement , and neurorehabilitation technology . He investigates how neural signals control muscles, develops methods to decode motor unit activity from EMG, and designs neural interfaces for prosthetics and rehabilitation. His work integrates computational modeling, signal processing, and clinical applications to improve bionic systems and neurorehabilitation outcomes. The recent publications (2024–2025) show a strong emphasis on high-density EMG , real-time motor unit decomposition , peripheral and cortical neural interfacing , closed-loop control systems , and AI-driven biosignal analysis . Key themes include decoding spinal and cortical signals, improving prosthetic control, understanding tremor mechanisms, and developing open-source tools for motor unit analysis. The work bridges neuroscience, engineering, and clinical practice. Scientific awards and honors include: Royal Society Wolfson Research Merit Award (2016) IEEE EMBS Early Career Achievement Award (2010) Nightingale Prize for best paper in MBEC (2007) Elected Fellow of EAMBES (2016) Elected Fellow of AIMBE (2012) Professor Farina has advised numerous researchers and students in neuroengineering and rehabilitation technology. He has led major research grants in neural interfaces and neurorehabilitation. He is Editor-in-Chief of the Journal of Electromyography and Kinesiology , an editor for IEEE Transactions on Biomedical Engineering and The Journal of Physiology , and has held editorial roles in multiple journals. He was President of ISEK (2012–2014) and is a Senior Member of IEEE. He leads a research group focused on neuromechanics, neural decoding, and bionic systems. The team develops tools like I-Spin live and MUedit for real-time motor unit identification and contributes to open-source platforms such as NeuroMotion . The lab collaborates internationally on projects involving spinal cord stimulation, prosthetic control, and wearable robotics, aiming to translate neural engineering advances into clinical rehabilitation.

Rikky MullerView profile

Associate Professor

• Neural Engineering
• Medical Devices
• Low-Power Electronics
• +6 more

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

Tim DenisonView profile

Professor

• Neural interface technologies
• Algorithm technologies for neurological disease treatment
• Physiologic closed-loop systems
• +7 more

Professor Tim Denison FREng holds a joint appointment in the Department of Engineering Science and Nuffield Department of Clinical Neurosciences at the University of Oxford, where he serves as the Royal Academy of Engineering Chair in Emerging Technologies and an MRC Investigator. His research focuses on the fundamentals of physiologic closed-loop systems and developing next-generation neural interface technologies for treating chronic neurological diseases. Professor Denison received his A.B. in Physics from The University of Chicago, followed by M.S. and Ph.D. degrees in Electrical Engineering from MIT. He later completed an MBA at The University of Chicago, where he was named a Wallman Scholar. His research spans neural engineering, closed-loop neuromodulation systems, and computational neuroscience, with particular emphasis on deep brain stimulation, neural oscillations, and adaptive neurostimulation techniques. His work integrates engineering principles with clinical neuroscience to develop innovative treatments for neurological disorders. Professor Denison's approach combines computational modeling with experimental validation to optimize brain stimulation parameters for individual patients. Professor Denison has received numerous prestigious awards, including membership in the Bakken Society (2012, Medtronic's highest technical honor), the Wallin leadership award (2014), election to the College of Fellows for the American Institute of Medical and Biological Engineering (2015), and recognition as a Fellow of the Royal Academy of Engineering (FREng). As a former Technical Fellow at Medtronic PLC and Vice President of Research & Core Technology for the Restorative Therapies Group, Professor Denison brings significant industry experience to his academic work. His research group focuses on developing advanced neurostimulation technologies that incorporate chronobiology principles and adaptive algorithms to improve treatment outcomes for neurological conditions.

Boubker ZaaimiView profile

Lecturer

• Neuroscience
• Neuromodulation
• Brain-Computer Interfaces
• +5 more

Dr. Boubker Zaaimi is a Lecturer in Neuroscience at Aston University, affiliated with the School of Life & Health Sciences under the College of Health and Life Sciences. His 15+ years of experience focus on implanting electrodes in animal models (rodents to primates) to study brain activity modulation, particularly in stroke and epilepsy contexts. He specializes in brain-machine interfaces, optogenetics, and closed-loop protocols to regulate neural activity. Key projects include the CANDO project (Newcastle University) and collaborations with DARPA and industry partners like Autifony Therapeutics. His research uses magnetoencephalography (MEG) to advance human brain activity recording and modulation techniques. Employment History: Multiple postdoctoral roles at Newcastle University, Northwestern University, and City College, NY, culminating in his current faculty position. Research Interests: Optogenetic control, neural dynamics in primates, spinal cord plasticity, and neuromodulation therapies. His work bridges basic science and clinical applications, with recent focus on non-invasive neurostimulation (e.g., brain-responsive music) and closed-loop systems for epilepsy management. Over 19 peer-reviewed articles highlight his contributions to understanding neural pathways and developing therapeutic interventions.

Kelly BijankiView profile

Associate Professor

• Neuromodulation
• Affective neural circuits
• Electrophysiology
• +9 more

Kelly Bijanki is an Associate Professor of Neurosurgery, Director of Intracranial Monitoring Research, and holds joint appointments in Psychiatry and Neuroscience at Baylor College of Medicine. Her work bridges clinical neurosurgery and neuroscience, focusing on understanding the neural basis of affective disorders and developing neuromodulation therapies. She directs the Translational Neuromodulation Lab, where she leverages stereotactic electroencephalography (sEEG) to study deep brain structures critical to emotional functioning. Dr. Bijanki's research explores the electrophysiological, neurobiological, and behavioral correlates of neuromodulation of affective neural circuits. Her lab primarily works with patients undergoing intracranial monitoring for epilepsy or depression, using this unique platform to conduct in-vivo studies of neural correlates to affective function. Her work has identified novel stimulation-based strategies for evoking positive affect and anxiolysis, including the discovery that stimulation to the cingulum bundle evokes changes in anxiolysis, mirth, and euphoria, which was featured as a cover article in the Journal of Clinical Investigation and highlighted in the NIH Director's Blog. Analysis of her recent publications reveals a consistent focus on mapping neural circuits involved in emotion processing, particularly using stereo-EEG informed deep brain stimulation approaches. Her work spans multiple psychiatric conditions including depression, obsessive-compulsive disorder, and anxiety disorders, with a strong emphasis on translating electrophysiological findings into therapeutic applications. The integration of computational approaches, particularly machine learning for decoding neural activity related to mood states, represents a growing trend in her research program. Her scientific achievements include: United States Patent (US:11,241,575) for a novel stimulation-based strategy for evoking positive affect and anxiolysis Journal of Clinical Investigation cover article (March 2019) on cingulum stimulation enhancing positive affect NIH Director's Blog feature highlighting her groundbreaking work Multiple NIH grants including R01, R21, and K01 awards Dr. Bijanki mentors a diverse team including graduate students, postdoctoral fellows, and undergraduate researchers. Her research program is generously funded by multiple NIH grants (R01-MH127006, R01-MH130597, K01MH116364, R21NS104953, UH3NS103549), as well as support from the ARCO Foundation, Caroline Wiess Law Fund, American Foundation for Suicide Prevention, and NARSAD. She maintains strong collaborations with researchers at institutions including UTSW, Iowa, Duke, UCLA, Brown, UPenn, and WashU. The Translational Neuromodulation Lab operates at the intersection of clinical neurosurgery, neuroscience, and engineering, utilizing stereo-EEG as a research platform to study deep brain structures involved in emotional processing. The lab employs multiple methodologies including advanced surgical neuroimaging, affective electrophysiology, autonomic surveillance, facial motor analysis, and pulse-evoked potentials to comprehensively characterize mood-relevant neural circuits. Their current flagship project involves using explainable artificial intelligence to map the relationship between mood and intracranial neural activity, with the goal of developing naturalistic patterns of intracranial stimulation for therapeutic applications.

• Closed-loop neurotechnology
• Neuromodulation
• Machine learning
• +4 more

Dr. Eric Meyers is an Assistant Professor in the Department of Bioengineering at the Erik Jonsson School of Engineering and Computer Science, University of Texas at Dallas. He holds a Ph.D. in Biomedical Engineering and dual Bachelor's/Master's degrees in Electrical Engineering from the same institution. His research focuses on closed-loop neurotechnology, neuromodulation, and bioelectronic medicine to enhance recovery from nervous system injuries. Key projects include developing wearable EMG sleeves for stroke rehabilitation and closed-loop neuromodulation systems to restore motor function. Education: B.S. (2012), M.S. (2018), Electrical Engineering; Ph.D. (2017), Biomedical Engineering – all from UTD His research interests span machine learning applications in neurorehabilitation, biomarker discovery for neurological conditions, and clinical translation of bioelectronic therapies. Recent work emphasizes wearable devices for real-time motor function assessment and neuromodulation-driven recovery strategies. Publications highlight advancements in EMG-based neural interfaces, closed-loop algorithms for stroke therapy, and innovative FES systems. His lab actively collaborates on projects funded by NIH and industry partnerships, with a focus on translating technologies to clinical settings.

Allon GuezView profile

Professor

• Control Systems
• Robotics
• Artificial Intelligence
• +7 more

Allon Guez is a Professor in the Department of Electrical and Computer Engineering at Drexel University. His research focuses on control systems, robotics, artificial intelligence, medical robotics, and automated decision making. He actively bridges academia and industry through high-tech entrepreneurship. Education PhD in Electrical Engineering, University of Florida MS in Electrical Engineering, University of Florida MBA in Finance, Drexel University BS in Electrical Engineering, Technion - Israel Institute of Technology His research portfolio spans medical robotics, automated decision making systems, and advanced control algorithms. Key areas include wearable safety devices, radiation control in imaging systems, and closed-loop brain stimulation technologies. Notable contributions include founding ControlRad (radiation reduction systems) and GraceFall (fall detection technology). His work demonstrates a strong emphasis on translating academic research into commercial medical devices. Recent publications highlight innovations in: Fetal brainwave monitoring Postural disturbance detection Seizure prediction algorithms Magnetic microrobotics Dynamic CT collimation Cardiac tissue modeling

Karim OweissView profile

Professor

• Neuroscience
• Biomedical Engineering
• Electrical Engineering
• +5 more

Karim Oweiss is a Pre-eminent Professor at the University of Florida, with joint appointments in the Department of Biomedical Engineering (Herbert Wertheim College of Engineering), Electrical and Computer Engineering, and Neuroscience (McKnight Brain Institute). He holds a Ph.D. in Electrical Engineering and Computer Science from the University of Michigan (2002). His research focuses on neural mechanisms of sensorimotor integration and the development of clinically viable brain-machine interfaces (BMIs) to restore damaged neurological function. His work spans computational neuroscience, neural decoding, optogenetics, and advanced neurotechnology, with a strong emphasis on closed-loop systems and neural plasticity. 2025 : Chemogenetic stimulation of phrenic motor output and diaphragm activity 2024 : Chemogenetic phrenic motoneuron activation enables increased tidal volume 2023 : Compressive sensing of functional connectivity maps from patterned optogenetic stimulation Oweiss has received the NSF Excellence in Neural Engineering Award (2001) and is a Senior Member of the IEEE. He has published extensively on topics including neural decoding, compressive sensing, and multiscale neural interfacing. As editor of Statistical Signal Processing for Neuroscience and Neurotechnology (2010), he has contributed significantly to the field's methodological foundations. His lab develops tools like NeuroQuest for large-scale neural data analysis and implantable neuroprocessors for wireless BMI applications.

Enrico OpriView profile

Assistant Professor

• Neuromodulation
• Deep Brain Stimulation (DBS)
• Neurological Disorders
• +4 more

Dr. Enrico Opri is an Assistant Professor in the Department of Biomedical Engineering at the University of Michigan , where he directs the Opri Lab. His research focuses on engineering novel methodologies to automate and enhance clinical procedures in neuromodulation for neurological disorders such as Parkinson’s, Tourette syndrome, essential tremor, and epilepsy. Research Focus Neurophysiological activity in basal ganglia-thalamocortical circuits Therapeutic effects of neuromodulation (e.g., Deep Brain Stimulation, cortical stimulation mapping) Identification of neurological biomarkers for improved clinical procedures Advancements in closed-loop neurostimulation systems Article Trends Dr. Opri's recent publications emphasize closed-loop deep brain stimulation (DBS) systems, computational modeling of neural activity, and the identification of biomarkers for neurological disorders. Key subfields include Parkinson’s disease motor dynamics, Tourette syndrome tic detection, essential tremor treatment, and cortico-thalamic coupling mechanisms. His work bridges biomedical engineering and clinical neuroscience, focusing on translating technological innovations into therapeutic applications.

Surjo R. SoekadarView profile

Professor

• Clinical Neurotechnology
• Brain-Computer Interfaces (BCI)
• Neuromodulation
• +8 more

Surjo R. Soekadar is the Einstein Professor of Clinical Neurotechnology at Charité – University Medicine Berlin. He leads the Clinical Neurotechnology Laboratory , which focuses on developing noninvasive neurotechnologies for treating neurological and psychiatric disorders through closed-loop brain stimulation and advanced brain-machine interfaces (BCI/BMI). His work integrates real-time EEG/MEG monitoring with electromagnetic stimulation to modulate pathological brain oscillations and enhance neuroplasticity in conditions like stroke, spinal cord injury, and psychiatric disorders. Education : Studied medicine in Mainz, Heidelberg, and Baltimore Clinical Training : Residency in Psychiatry and Psychotherapy at University of Tübingen Academic Journey : 2008-2011 Research Fellow at NINDS (USA); 2017 Venia Legendi at University of Tübingen; 2018 First Professor of Clinical Neurotechnology in Germany His research interests span: • Closed-loop neurostimulation combining real-time brain state monitoring with targeted intervention • Next-generation BCI using optically pumped magnetometers (OPM) for mobile MEG recordings • Neurorehabilitation through exoskeleton control and sensory feedback • Neurophysiological modeling of entropy measures and phase flows Recent publications highlight: • Adaptive deep brain stimulation protocols • Real-time phase-sensitive tACS applications • OPM-based BCI innovations • Stroke recovery mechanisms through corticospinal tract analysis Scientific recognition includes: International BCI Research Award BIOMAG Award NARSAD Young Investigator Award Funded by the European Research Council (ERC) , his lab trains doctoral students like David Haslacher (EEG/MEG integration), Khaled Nasr (multicoil TMS optimization), and Annalisa Colucci (entropy-driven BCI development). The team also explores quantum AI applications in clinical decision-making and bidirectional BCI systems using OPM and tES.

• Biomedical Engineering
• Neuroscience
• Neural Engineering
• +6 more

Hayriye Cagnan is a Senior Lecturer (Associate Professor) in the Department of Bioengineering at Imperial College London’s Faculty of Engineering. She specializes in neural engineering and movement disorders, focusing on deep brain stimulation (DBS) and tremor pathophysiology. Her research integrates computational modeling, signal processing, and clinical neuroscience to develop adaptive neurotherapies. Cagnan holds a Ph.D. in Neuroscience from the University of Amsterdam and Philips Research, and has held postdoctoral positions at the University of Oxford and University College London. Education: B.Sc. in Electrical and Electronics Engineering (Cornell University, 2000–2004) – Fulbright Scholar M.Sc. in Engineering and Physical Science in Medicine (Imperial College London, 2004–2005) – Chevening Scholar Ph.D. in Neuroscience (University of Amsterdam/Philips Research, 2010) Research Interests: Her work addresses neural mechanisms underlying Parkinson’s disease, essential tremor, and other movement disorders. Key areas include: Development of adaptive DBS systems for tremor management Neural circuit dynamics and oscillations in basal ganglia networks Non-invasive neurostimulation techniques (e.g., TMS, tRNS) Machine learning for optimizing neurotherapeutic interventions Publications: Recent work emphasizes closed-loop systems, phase-specific stimulation, and translational neuroscience. Her studies explore how DBS modulates movement speed, reward processing, and neural oscillatory patterns in Parkinsonian patients. Awards: MRC Career Development Award (2018) MRC Skills Development Fellowship (2015) British Chevening Scholarship (2004) Lab & Collaboration: Leads the Neuroengineering and Dynamic Systems Lab at Imperial, collaborating with clinicians and engineers to advance neuromodulation therapies. Active in initiatives like NEUROMOD+ for next-generation neurotherapies.