Brain Machine Interfaces Professors and Supervisors | ApplySharif

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Daniel HannonView profile

Professor

Tufts UniversityUnited States

Daniel Hannon is a Professor of the Practice in the Department of Mechanical Engineering at Tufts University School of Engineering . His work bridges industry practice and academic research in human factors engineering, with a focus on transportation human factors , medical product design , educational technology , and team performance . As an educator, he specializes in teaching human factors engineering at undergraduate and graduate levels through courses like Applied Behavioral Stats Eng, Human-Machine System Design, and Special Topics in Assistive Design. Education: Ph.D. in Experimental Psychology, Brown University (1991) M.Sc. in Experimental Psychology, Brown University (1987) B.A. in Psychology, Nazareth College (1985) M.S. in Community Mental Health Counseling, Southern New Hampshire University (2008) Hannon's research interests span visual perception , cognitive systems engineering , universal design , and assessments of speech-motor coordination in autism . His recent work includes developing noninvasive biomarkers for mental state and serious games for collaborative dark network discovery . His publications highlight interdisciplinary collaborations with institutions like MIT Lincoln Laboratory , U.S. Department of Defense , and National Science Foundation . Notable grants include MIDAS (Multisensory Interactive Data Analysis System) and InterLACE (Interactive Learning and Collaborative Environment). Scientific awards include the Award of Excellence from ASME , Ergonomics in Design Best Paper Award , and Employee Excellence Award from the U.S. Department of Transportation . Hannon's professional activities include developing academic certificates (Assistive Design, Human Factors in Data Science) and coordinating the Human Factors Engineering Speaker Series at Tufts University. He serves in organizations like the Human Factors and Ergonomics Society and American Psychological Association .

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Ian HowardView profile

Associate Professor

University of PlymouthUnited Kingdom

Ian Howard is Associate Professor of Computational Neuroscience at University of Plymouth's School of Engineering, Computing and Mathematics. His multidisciplinary research examines brain development across motor systems, from infant speech acquisition to adult motor learning, using robotic interfaces and computational modeling. Research spans multiple periods of brain development and motor systems: infant speech acquisition, adult arm movement learning, and robotic interface design. Current projects investigate motor imagery benefits, haptic feedback in skill acquisition, and voice pathology detection using machine learning. Robotics innovations include novel manipulanda for sensorimotor research and 3D-printed robotic segments with variable-stiffness actuators. Publications demonstrate consistent focus on computational modeling of biological learning processes. Teaches machine learning, control engineering, and mobile robotics. Professional affiliations include societies for neuroscience and robotics research. Research collaborations extend internationally through robotic interface sharing.

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Joseph SchmidtView profile

Associate Professor

University of Central FloridaUnited States

Joseph Schmidt is an Associate Professor of Psychology at the University of Central Florida, where he directs the Attention and Memory Laboratory. His research integrates eye-tracking and EEG/ERP methodologies to study attention-memory interactions. Key focus areas include: Neural and behavioral correlates of visual working memory Attention guidance in real-world contexts Visual search errors in medical imaging Oculomotor patterns in neurological disorders His work bridges cognitive psychology and neuroscience, examining how memory representations shape attentional selection. Current projects investigate cognitive expectations in visual search, EEG classification methods, and attentional deficits in clinical populations.

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Armando BarretoView profile

Professor

Florida International UniversityUnited States

Armando Barreto is a Professor in the Department of Electrical & Computer Engineering at Florida International University (FIU). He holds a Ph.D. in Electrical Engineering from the University of Florida (1993), an M.S.E.E. from FIU (1989), and a Mechanical-Electrical Engineering degree from the National Autonomous University of Mexico (1987). His research focuses on digital signal processing with applications in biomedical systems, including EEG analysis, adaptive algorithms, neural networks, and real-time embedded systems. He also explores human-computer interaction through sensor technologies like MEMS, inertial measurement units, and multi-touch interfaces. His work addresses accessibility challenges for visually impaired users through dynamic image precompensation and assistive technologies. Key contributions include innovations in signal denoising, affective computing via pupil dynamics analysis, and multimodal data fusion for early detection of neurodegenerative diseases like Alzheimer’s. His research bridges theoretical signal processing with practical applications in healthcare, virtual reality, and wearable devices. Barreto’s publications span over three decades, demonstrating sustained leadership in sensor-based systems, medical signal processing, and computational neuroscience. He collaborates with interdisciplinary teams to advance technologies addressing clinical and accessibility challenges.

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Eduardo MirandaView profile

Professor

University of PlymouthUnited Kingdom

Professor Eduardo Miranda is a visionary academic and composer specializing in computer music, AI, and neuroscience. As Head of the Interdisciplinary Centre for Computer Music Research (ICCMR) at the University of Plymouth, he pioneers innovations like brain-computer music interfaces (BCMI) and quantum computing applications in music. His work bridges art and science, focusing on assistive technologies for people with disabilities and dementia through projects like RadioMe. He holds a PhD from the University of Edinburgh (1995), specializing in AI for music, and has supervised over 20 doctoral students globally. His research spans biocomputing, quantum music systems, and neurotechnology, with grants exceeding £5M. Notable collaborations include work with the BBC Concert Orchestra and Jarvis Cocker, and his opera Lampedusa uses particle physics data from the Large Hadron Collider. Research Interests: - AI and Machine Learning in Music - Quantum Computing for Creativity - Biocomputing and Living Organisms as Processors - Music Neurotechnology for Health - Ethical AI in Creative Industries - Historical Computing (e.g., Charles Babbage’s legacy) - Music-Based Palliative Care Projects & Impact: - RadioMe : AI-driven radio personalization for dementia patients. - QuTune : Quantum computing tools for musicians. - Music and the Brain research group at the Brain Research & Imaging Centre (BRIC). - Development of bio-inspired algorithms for composition and performance. Teaching: Courses in AI, quantum computing, unconventional computing, and music technology. Advising & Grants: Supervised 22+ PhD completions. Secured £5M+ in research funding. Doctoral alumni work globally in academia (e.g., McGill University) and industry (e.g., Arm microprocessors). Recognition: Featured in Forbes for quantum music innovation. Keynote speaker at Royal Institution and EG Conference. First classical composer to perform in the Metaverse.

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Mansour YouseffiView profile

Senior Lecturer

University of BradfordUnited Kingdom

Dr. Mansour Youseffi is a Senior Lecturer (Reader) in Biomaterials at the University of Bradford's School of Engineering, part of the Faculty of Engineering and Digital Technologies. He leads modules in Materials Science and Engineering, Rehabilitation and Prosthetics, and other biomedical-focused courses. His research spans biomaterials, biotribology, cell and tissue engineering, and medical device development, with a focus on applications in orthopedics, cancer treatment, and regenerative medicine. Since 1992, he has secured over £740k in research funds, supervised 25 PhD graduates, and authored 25 books, 5 patents, and 250+ publications. His work includes advancements in engineered biomaterials for cancer immunotherapy, medical imaging techniques, and smart prosthetics. He currently advises 3 PhD students and collaborates with interdisciplinary teams in Advanced Materials Engineering and Medical Engineering research groups. Key research topics include biocompatible materials for implants, AI-driven medical imaging analysis, and biomaterials for tissue engineering. His contributions address global health challenges, including cancer diagnostics and disparities in healthcare access across regions like the UK and Saudi Arabia.

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Susan SchneiderView profile

Professor

University of QuebecCanada

Susan Schneider is the William F. Dietrich Distinguished Professor of Philosophy of Mind at Florida Atlantic University (FAU), affiliated with the Stiles-Nicholson Brain Institute and the Dorothy F. Schmidt College of Arts and Letters. She serves as Founding Director of the Center for the Future Mind and co-director of the MPCR Lab, focusing on AI, consciousness, and astrobiology. Her research explores the philosophical implications of AI, including conscious AI ethics, integrated information theory, and existential risks. Schneider has held the NASA Chair and Library of Congress Distinguished Scholar roles, contributing to AI policy development in Congress. She has authored influential books like *Artificial You* and appears frequently in media (PBS, History Channel). Her work bridges philosophy, cognitive science, and technology to address cutting-edge questions about mind, AI, and the future of intelligence. Key affiliations include FAU’s Gruber Sandbox facility, where AI systems are developed using neuroscience and philosophy insights. Collaborations with NASA and YHouse explore AI consciousness testing and interstellar probes. Schneider’s recent work involves patenting AI consciousness tests and publishing in journals like *Journal of Consciousness Studies*. She lectures globally, addressing forums such as Harvard’s Kennedy School and the World Science Festival. Education: Not explicitly listed, but her roles imply advanced academic training in philosophy and cognitive science. Grants/Awards: NASA-funded projects, Library of Congress Chair, and Forbes recognition for *Artificial You*. Media Engagement: TV appearances (Star Talk, History Channel), TED talks, and op-eds in *New York Times* and *Scientific American*. Her research trends emphasize interdisciplinary approaches to AI ethics, consciousness measurement, and future technology governance. Articles and talks highlight the urgency of addressing AI’s existential risks and philosophical boundaries. Labs like MPCR Lab exemplify her commitment to merging theory with practical AI development.

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Joseph T. FrancisView profile

Professor

University of HoustonUnited States

Joseph T. Francis is a full Professor in the Department of Biomedical Engineering at the University of Houston. He holds a Ph.D. in Neuroscience from The George Washington University and a B.S. in Biology with Honors from SUNY Buffalo. His career spans postdoctoral work at Johns Hopkins University and SUNY Downstate Medical School, followed by faculty roles at SUNY Downstate (2006–2018) and the University of Houston (2015–present). Education Ph.D., Neuroscience, The George Washington University B.S., Biology With Honors, State University of New York at Buffalo His research focuses on Brain-Machine Interfaces (BMIs) and somatosensory neuroprosthetics, aiming to translate neural activity (spiking, LFPs, EEG, fNIRS) into robotic motion and deliver sensory feedback to the brain or periphery. He also investigates sensorimotor learning and neural plasticity. Dr. Francis has secured significant funding from NIH, NSF, and DARPA for projects such as: Regenerative Micro-Electrode Peripheral Nerve Interface (NIH, 2022–2027) Multimodal Brain-Computer Interface for Human-Robot Interaction (NSF, 2021) Synthetic Brain Through Hybrid Systems (DARPA, 2010–2015) His work combines computational neuroscience with experimental approaches, emphasizing cortical plasticity, reward expectation mechanisms, and naturalistic BMI control systems.

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Shonda BernadinView profile

Associate Professor

Florida State UniversityUnited States

Shonda Bernadin, Ph.D., is an Associate Professor in the Department of Electrical & Computer Engineering at the FAMU-FSU College of Engineering, a joint institution of Florida Agricultural and Mechanical University and Florida State University. She holds a B.S. from Florida A&M University, an M.S. from the University of Florida, and a Ph.D. from Florida State University. Her research spans digital signal processing, speech recognition, artificial intelligence, autonomous vehicles, and engineering education. She directs the Speech Processing and Data Analysis Laboratory (SPADAL) and focuses on broadening STEM participation through K-12 outreach, including ACEE summer camps and CROP-ENG programs. Dr. Bernadin’s work emphasizes engineering education innovation, including evidence-centered assessment design and strategies to improve retention and diversity in engineering. She has authored numerous peer-reviewed publications on topics like neural networks, sensor-based defect detection, and cybersecurity threats in AI systems. Her teaching philosophy prioritizes creating inclusive, effective learning environments through engaging methods and technology integration. Professional activities include leadership in engineering education reform and collaborations with organizations such as ASTERIX to enhance STEM workforce diversity. Her lab’s research often intersects technology development with societal impact, addressing challenges in healthcare, autonomous systems, and additive manufacturing quality control.

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Xiaopeng ZhaoView profile

Professor

University of TennesseeUnited States

Xiaopeng Zhao is a Professor in the Department of Mechanical, Aerospace, and Biomedical Engineering at the University of Tennessee, Knoxville, where he has been a faculty member since 2007. His research focuses on computational neuroscience, biomedical informatics, brain-computer interfaces, and AI applications in healthcare, particularly dementia care. Education: PhD in Engineering Science and Mechanics, Virginia Tech (2004) MS in Engineering, Tsinghua University, China (1999) BS in Engineering, Tsinghua University, China (1996) Research Interests: Dr. Zhao's work spans multiple interdisciplinary fields including brain-computer interfaces, wearable healthcare technologies, computational physiology, signal processing, machine learning, and epidemic modeling. His recent focus has been on developing AI-driven solutions for dementia care, including social robotics, explainable AI models, and personalized healthcare interventions. His research also encompasses biomechanics, micro- and nano-systems, impact and vibration analysis, system identification, and nonlinear dynamics. He applies advanced computational techniques to understand complex biological systems and develop innovative healthcare technologies. Scientific Awards: NSF CAREER Award (2009) Winner of Physionet/Computing in Cardiology Challenge (2010, 2011) Southeastern Conference Visiting Faculty Travel Grant (2016) Faculty Understanding Science in Open Networks Award on Human-Technology Frontier (2018) University of Tennessee Engagement and Outreach Grant (2019) University of Tennessee Faculty Fellow (2019) Professional Service: Dr. Zhao is actively involved in professional organizations including IEEE Engineering in Medicine and Biology Society (EMBS), American Society of Mechanical Engineers (ASME) - Dynamic Systems & Control Division (DSCD), Biomedical Engineering Society, and Society for Industrial and Applied Mathematics (SIAM). Contact: xzhao9@utk.edu | 313 Perkins Hall, University of Tennessee, Knoxville

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Graham HealyView profile

Assistant Professor

Dublin City UniversityIreland

Graham Healy is Assistant Professor and COMSCI Programme Board Chair at Dublin City University's School of Computing. His research develops hybrid human-computer interaction systems using bioelectric signals (EEG), eye-tracking, and machine learning. Current projects include the CASTLE multimodal dataset, AMBER BCI dataset for naturalistic settings, and DERCo EEG-reading comprehension corpus. Dr. Healy creates interactive retrieval systems like VEAGLE (eye gaze-assisted video browsing) and LifeInsight (lifelog search engine), winning competitive evaluations at Video Browser Showdown and Lifelog Search Challenge events. His neuroergonomics research investigates pre-stimulus EEG for predicting driver reaction times, while health informatics projects develop machine learning models for early gestational diabetes prediction using electronic health records. With PhD expertise in brain-computer interfaces from DCU, Dr. Healy's work spans experimental neuroscience, information retrieval, and clinical applications. Recent publications address reproducibility challenges in medical AI and validate diagnostic coding in electronic health systems. His NeuroScore framework evaluates GAN performance using neural responses, advancing quality assessment in synthetic media.

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Thomas NaselarisView profile

Associate Professor

University of Minnesota Twin CitiesUnited States

Thomas Naselaris is an Associate Professor at the University of Minnesota, specializing in cognitive neuroscience and neuroimaging. His research focuses on decoding brain activity using advanced fMRI techniques and machine learning models, particularly in understanding visual perception, mental imagery, and memory. He leads the development of benchmark datasets like the Natural Scenes Dataset (NSD) and NSD-Imagery, which have become foundational for studying human visual cortex dynamics. His work integrates computational methods with neuroimaging to uncover how the brain represents and processes complex visual information. Notable contributions include reconstructing seen images from fMRI data and analyzing neural representations across different brain regions. He collaborates on large-scale studies involving ultra-high-field MRI and interdisciplinary approaches combining electrophysiology (iEEG) with fMRI. Key research themes include the role of generative models in visual processing, signal-to-noise dynamics in neural responses, and systems consolidation in memory. His grants include collaborative research proposals funded by CRCNS, focusing on evaluating machine learning architectures using benchmark datasets. Ongoing projects aim to bridge cognitive neuroscience with artificial intelligence, emphasizing interpretable models and scalable brain mapping techniques.

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George MatsopoulosView profile

Professor

National Technical University of AthensGreece

George Matsopoulos is Professor in Biomedical Engineering at the National Technical University of Athens, heading the Biomedical Engineering Laboratory. His research focuses on medical image processing, diagnostic support systems, and health information technologies. With over 300 publications, he develops computational methods for medical data analysis and leads the BIOMIG research group specializing in medical informatics and neuroimaging applications. Primary research areas include multidimensional medical data fusion, digital biosignal processing, telemedicine systems, and visualization techniques. His laboratory utilizes advanced computational tools including ITK, VTK, and CUDA to address clinical challenges in medical imaging and diagnostics.

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Leo SugrueView profile

Associate Professor

University of California, San FranciscoUnited States

Dr. Leo Sugrue is an Associate Professor in the Department of Radiology and holds a joint appointment in the Department of Psychiatry at the University of California, San Francisco (UCSF). He specializes in Neuroradiology, with a focus on imaging brain circuits involved in neuropsychiatric disorders such as obsessive-compulsive disorder (OCD), depression, and movement disorders. His work integrates advanced imaging techniques like functional MRI (fMRI), diffusion MRI (dMRI), and focused ultrasound to develop personalized treatments. He co-directs the UCSF Neuroscience Program in Focused Ultrasound and directs the Laboratory for Precision Neuroimaging, which merges genetic, behavioral, and imaging data to understand brain disorders. Dr. Sugrue earned his MD from Johns Hopkins School of Medicine and a PhD in Neuroscience from Stanford University, with postdoctoral training at Stanford and UCSF. Education: Johns Hopkins (MD), Stanford (PhD in Neuroscience) Residency: UCSF Diagnostic Radiology Fellowship: UCSF Neuroradiology His research interests include neuromodulation, imaging genetics, and molecular imaging. He has received awards such as the Haile T. Debas Excellence in Teaching Award (2019) and the ARRS/ASNR Research Scholar Award (2016). His lab's work emphasizes translational approaches to brain disorders, aiming to tailor treatments to individual patients' needs. Key contributions include studies on OCD treatment using deep brain stimulation (DBS), the role of DNA methylation in Alzheimer's progression, and the development of imaging pipelines for focused ultrasound therapies. Dr. Sugrue collaborates across disciplines, including psychiatry, neurosurgery, and neurology, to advance circuit-based diagnostics and interventions.

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Sadasivan Puthusserypady KumaranView profile

Associate Professor

Technical University of DenmarkDenmark

Sadasivan Puthusserypady Kumaran is an Associate Professor at the Department of Health Technology, Technical University of Denmark. His research focuses on Biomedical Signal Processing, Brain-Computer Interfaces (BCIs), and Home Health Care systems. He holds a PhD from the Indian Institute of Science, with prior roles at National University of Singapore and Raytheon Systems Canada. He leads interdisciplinary projects in digital health and neurorehabilitation. B.Tech: Electrical Engineering, University of Calicut (1986) M.Tech: Instrumentation & Control Systems, University of Calicut (1989) PhD: Electrical Communication Engineering, Indian Institute of Science (1995) Research interests span neurophysiological signal analysis, assistive technologies, and AI-driven healthcare solutions. Recent work emphasizes cardiovascular risk prediction through ECG/sleep data, wheelchair control via EOG signals, and BCI systems for stroke rehabilitation. Notable achievements include Best Paper Awards (2020), Best Poster Award (2015), and recognition for teaching excellence (2017). Advising 5 active PhD projects: Brain-to-Text BCI systems, musculoskeletal digital twins, cardiovascular event prediction, neurology tool development, and wearable health monitoring. Collaborates with clinical and engineering teams across Denmark and internationally. Led the development of Digital Health and Biomedical Signal Processing research groups at DTU, advancing translational healthcare technologies.

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