جست‌وجوی استاد و پژوهشگر

Suyi Liمشاهده پروفایل

دانشیار

• Origami Engineering
• Mechanical Metamaterials
• Soft Robotics
• +۶ مورد دیگر

Suyi Li is an Associate Professor in the Department of Mechanical Engineering at Virginia Tech's College of Engineering, where he leads the Dynamic and Architected Robot and structurE (DARE) Lab. Previously, he served as an Assistant Professor at Clemson University from 2016-2022 after completing postdoctoral research at the University of Michigan. Ph.D. in Mechanical Engineering, University of Michigan, Ann Arbor (2014) M.Sc. in Mechanical Engineering, Pennsylvania State University (2008) B.S. Summa Cum Laude in Mechanical Engineering, University of Michigan, Ann Arbor (2006) Dr. Li's research focuses on pioneering new paradigms of intelligent robots and functional structures by exploiting the interplay between geometry, mechanics, actuation, and computation. His work spans origami-inspired morphing structures, physically computing materials that perform machine learning tasks without traditional electronics, and soft/reconfigurable robots that can move like animals or grow like plants. His innovative approach combines mechanical engineering principles with computational thinking to create systems with 'mechano-intelligence'. Analysis of Dr. Li's recent publications reveals a strong trajectory toward embodied intelligence and mechanical computing, where physical structures themselves perform computational tasks. His work increasingly integrates origami/kirigami principles with advanced materials to create systems that can sense, process information, and actuate without conventional electronics. The research shows progression from fundamental mechanics of adaptive structures to sophisticated applications in robotics and computing. Dean's Awards of Excellence – Faculty Fellow, Virginia Tech (2024) C.D. Mote Jr Early Career Award, ASME Design Engineering Division (2022) Gary Anderson Early Achievement Award, ASME Aerospace Division (2021) Junior Researcher of the Year Award, College of Engineering, Clemson University (2020) CECAS Dean's Faculty Fellow, Clemson University (2018) CAREER Award, National Science Foundation (2018) ASME Freudenstein Young Investigator Award Dr. Li has secured nearly two million dollars in research funding, including the prestigious NSF CAREER award and an NSF EFRI project to build mechano-bio hybrid reservoir computers. He advises multiple Ph.D. and Master's students in the DARE Lab, with recent successes including Vishrut Deshpande's Ph.D. defense. His research has generated close to 80 journal and conference papers, demonstrating significant impact in the fields of adaptive structures and materials systems. Dr. Li also serves on editorial boards for several prominent journals including Journal of Intelligent Material Systems and Structures and Philosophical Transactions of the Royal Society A. The DARE Lab at Virginia Tech comprises a multidisciplinary team of researchers working on origami-inspired meta-structures, physically computing materials, and soft robotics. Current projects include developing electronics-free crawling robots with mechanical central pattern generators, creating kirigami-based wearable medical devices, and engineering metamaterials with programmable mechanical properties. The lab actively collaborates with institutions across the country and has received recognition for its innovative approaches to combining mechanical design with computational capabilities.

Zsofia Zaveczمشاهده پروفایل

پژوهشگر

• Cognitive Neuroscience
• Sleep Research
• Electrophysiology
• +۳ مورد دیگر

Zsofia Zavecz is a Research Associate at the University of Cambridge Department of Psychology. Her work focuses on the neurophysiological mechanisms underlying sleep and memory consolidation, with particular emphasis on electrophysiological correlates of lucid dreaming and sleep-dependent learning. Research highlights include: Investigation of EEG functional connectivity during statistical learning Study of transcranial stimulation effects on probabilistic learning Analysis of sleep restriction impacts on hormonal regulation Exploration of cognitive reserve mechanisms in sleep disorders Her neuroscientific investigations span procedural memory systems, neural oscillations, and cross-population studies in both healthy individuals and pediatric sleep-disordered breathing patients.

Jonathan Cannonمشاهده پروفایل

استادیار

• Timing and Rhythm Perception
• Neural Dynamics
• Dynamical Systems Theory
• +۶ مورد دیگر

Jonathan Cannon is an Assistant Professor in the Department of Psychology, Neuroscience & Behaviour at McMaster University's Faculty of Science. His research focuses on timing and rhythm in perception and action, with particular interest in timing-related neural dynamics in the basal ganglia, cerebellum, and supplementary motor area. His work combines mathematical modeling with experimental approaches to understand the neural basis of rhythm perception and production. Dr. Cannon's research interests span timing and rhythm perception , neural dynamics , dynamical systems theory , Bayesian cognition , neural oscillations , and autism research . His approach centers on formulating and simulating neurophysiological and cognitive models, drawing on dynamical systems theory and Bayesian cognitive frameworks. His work incorporates psychophysics, EEG experiments, and collaborations with experimentalists to investigate how the brain processes rhythmic information. Analysis of his recent publications reveals a strong focus on the intersection of rhythm perception, motor control, and autism spectrum disorder. His work demonstrates how beat perception co-opts motor neurophysiology, with particular attention to predictive processes in rhythmic cognition. His research shows reduced precision of motor and perceptual rhythmic timing in autistic adults, while also finding intact sequence learning abilities in certain contexts. Dr. Cannon teaches advanced courses including Machine Learning Methods for Brain Modelling and Neural Data Analysis (PSYCH 734), Computational Models in Neuroscience (NEUROSCI 3MN3), and Neuroscience Seminars. His teaching reflects his interdisciplinary approach that bridges mathematics, neuroscience, and cognitive science. Beyond his academic work, Dr. Cannon is an active musician who performs on violin and guitar, particularly in klezmer and folk music contexts. He has also demonstrated entrepreneurial spirit through founding Flying Leap Games and developing the storytelling game 'Wing It,' which successfully crowdfunded and reached numerous retailers.

Bärbel Finkenstädt Randمشاهده پروفایل

مربی

• Statistical Methodology
• Machine Learning
• Bayesian Inference
• +۶ مورد دیگر

Bärbel Finkenstädt Rand is a Senior Tutor at the Warwick Medical School , University of Warwick, with extensive research contributions at the intersection of statistics, machine learning, and biomedical sciences. Her work focuses on developing advanced methodologies for analyzing temporal and spatio-temporal data, particularly in circadian rhythms and disease dynamics. Research Themes : Bayesian inference, Hidden Markov Models, circadian rhythm stability, transcriptional bursting, and wearable sensor data analysis. Collaborations : Chronotherapy Group at Warwick, Université Paris-Saclay, and interdisciplinary teams across medicine, genetics, and computational biology. Publications reveal a strong emphasis on circadian health monitoring, gene expression dynamics, and epidemic modeling using stochastic frameworks. Her recent work prioritizes personalized medicine applications through telemonitored biomarkers and IoT platforms . Methodological Innovations include spline-based HMMs, distributed delay systems, and harmonic modeling for nonstationary time series. Applications span oncology, sleep medicine, and population ecology.

Anthony Hornofمشاهده پروفایل

استاد

• Human-Computer Interaction
• Cognitive Modeling
• Eye Tracking
• +۹ مورد دیگر

Anthony Hornof is a Professor in the Department of Computer Science at the University of Oregon, part of the College of Arts and Sciences. He has been a faculty member since 1999 and was granted tenure in 2005. His research is centered on human-computer interaction, with strong emphases on cognitive modeling, eye tracking, and assistive technology. He leads an active research laboratory and has secured substantial funding from the National Science Foundation and the Office of Naval Research. University: University of Oregon School: College of Arts and Sciences Department: Department of Computer Science Position: Professor Email: hornof@uoregon.edu, hornof@cs.uoregon.edu Office: 356 Deschutes Hall Phone: (541) 346-1372 Education: B.A. in Computer Science, Columbia University, 1988 M.S. in Computer Science and Engineering, University of Michigan, 1996 Ph.D. in Computer Science and Engineering, University of Michigan, 1999 Research Interests: Dr. Hornof's research lies at the intersection of human cognition and computing. He is particularly interested in understanding and modeling the perceptual, cognitive, and motor processes involved in human-computer interaction. His work uses eye tracking both as an evaluation tool for cognitive models and as a real-time input method for creative expression and accessibility. A major focus is assistive technology, especially developing tools like EyeDraw that enable children with severe motor impairments to create art using only eye movements. He also explores eye-controlled musical compositions, bridging technology and artistic expression. His research is grounded in participatory design, involving end-users directly in the development process. Publication Trends: His recent publications demonstrate a consistent focus on modeling human behavior in complex interactive tasks. Key themes include visual search strategies, dual-task performance, cognitive modeling using eye-tracking data, and accessibility. His work spans top venues in HCI (CHI, TOCHI), cognitive science (CogSci, ICCM), and specialized conferences like ETRA and NIME. There is a strong methodological thread involving data calibration, model validation, and the development of predictive tools for interface design. Scientific Awards: Best Paper Award (Top 1%) at CHI 2014 (two papers) Honorable Mention Paper (Top 5%) at CHI 2010 Siegel-Wolf Award for Best Applied Paper at ICCM 2010 Advising and Grants: Dr. Hornof actively seeks to mentor exceptional undergraduate students, graduate students, and postdoctoral researchers in his lab. He emphasizes rigorous and creative scientific research. He has been awarded over $2.9 million in single-investigator research grants from prestigious agencies including the National Science Foundation (NSF) and the Office of Naval Research (ONR). Notably, he served as an NSF Program Director from 2012 to 2014, contributing to funding decisions for approximately $65 million in research. Labs and Teams: He leads the Human-Computer Interaction Laboratory at the University of Oregon, where interdisciplinary research is conducted on cognitive modeling, eye tracking, and assistive technologies. His team has developed software such as VizFix for visualizing eye-tracking data and has ported the Eyegaze system to Macintosh. The lab fosters collaborations with new media artists and musicians, and engages in participatory design with children who have disabilities.

Alexander Breussمشاهده پروفایل

پژوهشگر

• Biomedical Engineering
• Robotics in Healthcare
• Sleep Disorders
• +۳ مورد دیگر

Dr. Alexander Breuss is part of the Sensory-Motor Systems Professorship at ETH Zürich, focusing on developing innovative robotic and sensor technologies for medical applications, particularly in sleep disorder treatment and home healthcare. His work integrates biomedical engineering, robotics, and machine learning to address challenges in sleep medicine and cardiovascular diagnostics. Key projects include the Somnomat Care robotic bed for vestibular stimulation and the Somnomat Casa system for nocturnal interventions. His research spans sensorized devices for sleep monitoring, clinical trials for rhythmic movement disorders, and cardiovascular disease prognosis using imaging and hemodynamic analysis. Dr. Breuss collaborates on interdisciplinary projects, combining engineering and clinical insights to advance healthcare technologies. His research interests include the design of medical devices for home environments, non-invasive monitoring systems, and closed-loop robotic systems for therapeutic applications. Notable contributions include lightweight wearable sensors for movement disorders and automated sleep position classification using neural networks. He has published extensively on topics such as pleural effusion in aortic stenosis and ECG-based cardiac prognosis, highlighting his cross-disciplinary approach to biomedical challenges. No scientific awards are explicitly mentioned for Dr. Breuss. His work is centered at the Sensory-Motor Systems Lab, where he contributes to advancing technologies that improve patient care and sleep quality through robotics and sensor innovation.

Usha Goswamiمشاهده پروفایل

استاد

• Cognitive Developmental Neuroscience
• Developmental Psychology
• Educational Neuroscience
• +۷ مورد دیگر

Professor Usha Goswami is a leading academic in Cognitive Developmental Neuroscience at the University of Cambridge, serving as Professor of Cognitive Developmental Neuroscience and Director of the Centre for Neuroscience in Education. She is also a Fellow at St John's College, Cambridge. Her work focuses on understanding the neural and cognitive foundations of language acquisition, reading development, and developmental disorders such as dyslexia. Key areas of interest include the role of rhythm perception, speech processing, and EEG-based studies of neural entrainment in typical and atypical development. Her research integrates insights from neuroscience, cognitive psychology, and education, emphasizing translational approaches to improve literacy interventions. She has conducted longitudinal studies on infants and school-aged children, examining predictors of language outcomes and the impact of rhythmic training on executive function. Her work bridges developmental linguistics, auditory neuroscience, and educational policy, with a focus on universal speech structures in child-directed communication. Professor Goswami’s contributions include pioneering studies on the neural basis of phonological awareness and the application of machine learning to decode speech information from EEG data in infants. She has also explored cross-linguistic patterns in poetry and infant-directed speech, highlighting universal acoustic features underlying language acquisition. Her research has significant implications for understanding and remediating developmental disorders, particularly dyslexia and developmental language disorder. Her lab, the Centre for Neuroscience in Education, focuses on translating neuroscientific findings into practical educational strategies. Current projects include investigating rhythm-based interventions for children with language difficulties and analyzing the acoustic properties of speech in diverse linguistic contexts.

Aniruddh Patelمشاهده پروفایل

استاد

• Music Cognition
• Music-Language Relations
• Rhythmic Processing
• +۱ مورد دیگر

Dr. Aniruddh Patel is Professor of Psychology at Tufts University's School of Arts and Sciences. His pioneering research program in music cognition examines the mental processes underlying music perception and production, with emphasis on music-language relationships, rhythmic processing, and cross-species studies. He employs diverse methodologies including brain imaging, behavioral experiments, and comparative research with nonhuman animals. Education includes a PhD in Organismic and Evolutionary Biology from Harvard University. Dr. Patel previously served as Senior Fellow at The Neurosciences Institute (2005-2012) and President of the Society for Music Perception and Cognition (2009-2011). He is currently Fellow in the Azrieli Brain, Mind, and Consciousness program at the Canadian Institute for Advanced Research. His research output focuses on evolutionary foundations of rhythm perception, cross-species comparisons of musicality, and neural mechanisms underlying auditory illusions and predictive processing, with recent expansion into clinical applications for neurodevelopmental disorders. Fellow, Azrieli Brain, Mind, and Consciousness Program (CIFAR)

• Critical Care Neurology
• Electroencephalography (EEG)
• Neuroimaging
• +۸ مورد دیگر

Dr. Jennifer Ahjin Kim is an Assistant Professor in the Department of Neurology at Yale School of Medicine. She specializes in neurocritical care, focusing on quantitative analysis of electroencephalography (EEG) and neuroimaging for early diagnosis and treatment optimization in patients with severe neurologic injuries. Her clinical interests include traumatic brain injury, subarachnoid hemorrhage, stroke, and post-traumatic epilepsy. PhD in Neuroscience, Brown University (2012) MD from Brown University (2012) Neurology Residency, Massachusetts General Hospital/Brigham & Women's Hospital (2016) Neurocritical Care Fellowship, Massachusetts General Hospital/Brigham & Women's Hospital (2019) Dr. Kim’s research integrates multimodal data (EEG, MRI, CT) with machine learning to predict secondary complications after brain injuries. She actively contributes to clinical trials like BOOST3 and ASPIRE, aiming to improve outcomes for patients with traumatic brain injury, stroke, and hemorrhage. Her recent work emphasizes automated detection of epileptiform discharges, predictive modeling for delayed cerebral ischemia, and application of NLP to CT reports. Collaborations include frequent partnerships with Guido Falcone, Lawrence Hirsch, and Emily Gilmore. Dr. Kim leads the Kim Laboratory, which focuses on bedside monitoring technologies and secondary prevention strategies.

Petr Janataمشاهده پروفایل

استاد

• Cognitive Neuroscience
• Music Psychology
• Auditory Perception
• +۴ مورد دیگر

Petr Janata is a Professor in the Department of Psychology at the University of California, Davis, and a faculty member at the UC Davis Center for Mind and Brain. His research centers on cognitive neuroscience of music, investigating neural mechanisms underlying music-evoked autobiographical memories and the experience of "groove." He serves on the Board of the Society for Music Perception and Cognition and co-founded the UC Music Experience Research Community Initiative (UC MERCI). Janata's educational background includes: Ph.D. in Biology (Neuroscience) from the University of Oregon (1996) B.A. in Interdisciplinary Studies (Biology/Psychology) from Reed College (1990) His research employs behavioral experiments, fMRI, EEG, and computational modeling to explore how music engages memory, emotion, and sensorimotor systems. Key projects examine music-evoked remembering, the psychology of groove, auditory attention mechanisms, and timbre-emotion links. His work reveals how music activates domain-general brain networks for expectation, memory, and emotional processing. Recent publications (2018-2025) show increasing focus on cross-cultural emotional responses to music, neural correlates of nostalgia, mental replay mechanisms, and clinical applications of music cognition. His lab develops innovative paradigms like the Groove Enhancement Machine (GEM) to manipulate sensorimotor synchronization while measuring subjective enjoyment. Janata's scientific recognition includes: Guggenheim Fellowship (2010) Dual Fulbright Fellowships (1990-91, 2010-11) Music Has Power Award from the Institute of Music and Neurological Function (2010) He has delivered over 100 invited lectures globally and served as scientific advisor to Coro Health LLC before founding Meamer, Inc. in 2017 to connect people through memories and music. His translational work bridges basic cognitive neuroscience with real-world applications in health and technology. The Janata Lab at UC Davis integrates neuroimaging, behavioral testing, and computational modeling to advance understanding of music cognition. Current projects explore lifespan neural changes in music processing, adaptive virtual partners for synchronization studies, and sonification systems for physiological monitoring.

Psyche Louiمشاهده پروفایل

دانشیار

• Music Perception and Cognition
• Auditory Cognitive Neuroscience
• Creativity and Creative Practice
• +۳ مورد دیگر

Psyche Loui is an Associate Professor of Creativity and Creative Practice in the Department of Music at Northeastern University, leading the Music, Imaging, and Neural Dynamics (MIND) Lab. She holds a PhD in Psychology from UC Berkeley and dual bachelor’s degrees in Psychology and Music from Duke University. Her research focuses on the neuroscience of music perception, including how music influences attention, emotion, and neurological conditions like ADHD. Her work has been supported by major grants from the NSF and NIH, and she has received awards such as the Templeton Positive Neuroscience Award and a NSF CAREER Award. Education : PhD in Psychology (Cognition, Brain, and Behavior), University of California, Berkeley Bachelor’s in Psychology and Music, Duke University Research & Grants : Loui’s research explores how neural mechanisms underpin music perception and cognition, with recent studies investigating the efficacy of algorithmically generated music for improving focus in ADHD. Her grants include NIH funding for projects like ‘Gamma-Music-Based Intervention for Alzheimer’s’ ($2.7M) and NSF support for ‘Reward Prediction in Creative Perception.’ Awards : National Science Foundation CAREER Award (2020) Templeton Positive Neuroscience Award (2010) Multiple Grammy Awards (text reference) Labs & Teams : Loui directs the MIND Lab, which uses neuroimaging and electrophysiology to study music-brain interactions. Collaborations include work with Brain.fm on attention-focused music interventions and global studies on cross-cultural music patterns. Teaching : Courses include Music Cognition , Acoustics and Psychoacoustics , and Creative Cognition , bridging theory with practical applications in neuroscience and education.

Wendy Huddlestonمشاهده پروفایل

دانشیار

• Visual Attention
• Motor Attention
• Cognitive Neuroscience
• +۵ مورد دیگر

Wendy Huddleston is an Associate Professor in the Department of Physical Therapy at the University of Wisconsin-Milwaukee. Her research focuses on the cortical mechanisms underlying motor selection during visually guided goal-directed behavior, particularly the interaction between visual attention, motor attention, and cognitive neuroscience. She directs the Visuomotor Lab and serves as a mentor in the Rehabilitation Science and Technology graduate programs. She utilizes functional magnetic resonance imaging (fMRI) and psychophysical testing to study sensory processing for movement preparation. Her funded projects include investigations into individual differences in attentional mapping, cross-modal attention mechanisms, and the neurophysiological basis of movement variability. Collaborations extend to the Medical College of Wisconsin and the Center for Imaging Research. Huddleston's professional affiliations include the American Physical Therapy Association, Society for Neuroscience, Center for Imaging Research (MCW), and the Evidence-Based Practice Institute. Her work bridges rehabilitation science, biomechanics, and cognitive neuroscience to advance understanding of sensorimotor integration.

Shantanu Jadhavمشاهده پروفایل

استاد

• Learning and Memory
• Decision Making
• Neurophysiology
• +۵ مورد دیگر

Shantanu Jadhav is a Professor of Psychology at Brandeis University, with affiliations to the Neuroscience Program, the Volen National Center for Complex Systems, and the Sloan-Swartz Center for Theoretical Neurobiology. He earned his B.Tech. from IIT Bombay, Ph.D. from UC San Diego, and completed postdoctoral training at UCSF and UC Berkeley. Research Focus: Neural mechanisms of learning, memory, and decision-making in rodent models Investigation of hippocampal-prefrontal interactions via multielectrode recordings, optogenetics, and computational analysis Role of neural oscillations (theta, gamma, sharp-wave ripples) in memory consolidation and cognitive flexibility Implications for neurological disorders like Alzheimer’s, autism, and schizophrenia Recent work highlights the coordination of dopamine activity with rule representations in the prefrontal cortex and hippocampus, the role of prefrontal ripples in suppressing hippocampal reactivation during sleep, and geometric transformations in cognitive maps enabling cross-environment generalization. His lab has shown that awake sharp-wave ripples are critical for spatial memory and that cross-region neural synchronization underpins memory-guided decisions. Scientific Recognition: Peter and Patricia Gruber International Research Award (2013) Sloan Research Fellow (2015-2017) NARSAD Young Investigator Award (2015-2018) Whitehall Foundation Award (2016-2020) SFARI Core Member (2022-2025) The Jadhav Lab at Brandeis trains postdoctoral fellows, graduate students (via the Neuroscience and Psychology Graduate Programs), and research assistants. Current studies explore hippocampal-prefrontal network dynamics, dopamine signaling in cognitive flexibility, and geometric representations in memory abstraction.

• Sleep
• Circadian rhythms
• Bioinformatics
• +۴ مورد دیگر

Ron C Anafi serves as Associate Professor of Medicine (Sleep Medicine) at the Hospital of the University of Pennsylvania and holds key affiliations as Faculty Scholar at the Penn Institute for Bioinformatics, Co-Investigator at the Center for Subcellular Genomics, and member of both the Chronobiology and Sleep Institute and ITMAT. His work bridges computational biology with clinical sleep medicine within the Perelman School of Medicine. His educational trajectory includes a B.S.E. in Biomedical Engineering and Philosophy from Tulane University (1995), followed by a Ph.D. in Applied Mechanics (2002) and M.D. (2004) from the University of Minnesota. This dual training underpins his unique approach to circadian research. Dr. Anafi's laboratory pioneers computational methods to decode sleep and circadian influences on human physiology, focusing on neurodegeneration and cancer. By applying machine learning and systems biology to large-scale omics data, his team reconstructs molecular rhythms from cross-sectional human tissue databases—overcoming the critical barrier of limited longitudinal sampling in patients. His research demonstrates how circadian disruptions in ribosomal function link to Alzheimer's pathology and how tumor clock strength predicts breast cancer outcomes. Analysis of his 15 most recent publications (2022-2025) reveals intensifying focus on cell-type-specific circadian disruptions in neurodegenerative diseases, with significant expansion into cancer chronobiology and contactless sleep monitoring technologies. His methodological innovations like CYCLOPS enable rhythmic signal extraction across diverse tissues—from brain to skin—while increasingly integrating multi-omics layers to identify therapeutic targets. As mentor in the Genomics and Computational Biology and Neuroscience graduate groups, he guides students through rotation projects at his Translational Research Laboratories facility (Suite 2100, 125 South 31st Street). His research is supported by NIH grants investigating circadian mechanisms in Alzheimer's disease and cancer progression, with recent work exploring sex-specific metabolic impacts of circadian genes and non-invasive sleep monitoring.

Ali Yousefiمشاهده پروفایل

دانشیار

• Neuroscience Data Analysis
• Biomedical Engineering
• Brain-Computer Interfaces (BCI)
• +۶ مورد دیگر

Dr. Ali Yousefi is an Associate Professor in the Department of Biomedical Engineering at the University of Houston's Cullen College of Engineering. His research focuses on developing statistical and computational methods for analyzing neuroscience data, particularly in linking neural activity to biological/behavioral signals. Key areas include model identification, Bayesian analysis, and real-time neural decoding for applications like brain-computer interfaces and closed-loop stimulation systems. Education: B.S. (Electrical Engineering, Iran University of Science & Technology, 1998), M.S. (Electrical Engineering, Sharif University of Technology, 2000), Ph.D. (Electrical Engineering, University of Southern California, 2014). Postdoctoral training at Harvard Medical School (2019) and Boston University (2019). Research Interests: Neural data analysis frameworks Dynamic neural ensemble modeling Closed-loop brain stimulation systems Bayesian statistical inference High-dimensional data decoding Labs/Teams: Principal Investigator of Yousefilab, focused on neurotechnology and BCI development. Active in interdisciplinary collaborations combining engineering, neuroscience, and machine learning. Key Contributions: Developed methodologies for neural signal decoding, including Bayesian Gaussian process models and latent variable techniques. Pioneered real-time cognitive state prediction and closed-loop systems for enhancing cognitive control in humans.