Byron Yu is a Professor in Electrical & Computer Engineering and Biomedical Engineering at Carnegie Mellon University, with affiliations to the Neuroscience Institute and Robotics Institute. He is a core faculty member of the Center for the Neural Basis of Cognition. Research focuses on computational neuroscience , neural dynamics , and brain-machine interfaces . Key contributions include dimensionality reduction techniques and neural population activity analysis. Recent publications explore topics such as neural dynamics during motor imagery, BCI optimization, and attentional processing. His work has appeared in Nature Neuroscience , Neuron , and eLife , often as cover articles. Awardees include the Gerard G. Elia Career Development Professorship and AIMBE Fellowship . His lab has mentored numerous PhD and postdoctoral researchers, many now in academic and industry leadership roles.
Mayank R. Mehta is a Professor at the University of California, Los Angeles (UCLA), holding joint appointments in the Departments of Physics & Astronomy, Neurology, and Neurobiology. He is a member of the Brain Research Institute and the W. M. Keck Center for Neurophysics at UCLA. His research bridges experimental and theoretical neuroscience, focusing on how neuronal networks encode space-time, the role of brain rhythms in learning and memory, and the impact of sleep and virtual reality on neural dynamics. His recent publications highlight breakthroughs in understanding hippocampal spatiotemporal selectivity, dendritic activity during behavior, and the causal influence of visual cues on memory neurons. Notable findings include the discovery that dendrites generate ten times more spikes than neuronal cell bodies and the modulation of hippocampal theta rhythms in virtual reality. Research Themes: Neurophysics of spatial-temporal coding Dendritic contributions to learning Virtual reality and brain plasticity Neural oscillations in memory consolidation Key Collaborators: Bert Sakmann (Max Planck Florida Institute) Thomas Hahn (Bernstein Center Heidelberg/Mannheim) Maryam Ghorbani (UCLA) Mehta's lab at UCLA trains graduate and postdoctoral researchers in cutting-edge techniques combining hardware development, electrophysiological recordings, and biophysical modeling. His work has significant implications for treating learning and memory disorders like Alzheimer's disease.
Dr. Juan Alvaro Gallego is a Senior Lecturer (equivalent to Associate Professor) in the Department of Bioengineering at Imperial College London's Faculty of Engineering. He leads the Behaviour and Neural Dynamics Lab (Be.Neural), a multidisciplinary team focused on understanding neural mechanisms underlying motor control and spinal cord learning, with applications in developing neural interfaces to restore movement in conditions like Parkinson’s disease and paralysis. His research integrates behavioral experiments, neural recordings, data analysis, and computational models, funded by the ERC, EPSRC, ARIA, and industry partners like InBrain Neuroelectronics and Meta Reality Labs. Research interests include motor control, neural dynamics, and clinical applications of neural engineering. The lab collaborates across systems neuroscience and biomedical engineering, aiming to translate fundamental discoveries into therapeutic technologies. Key areas of focus include neural manifolds, synaptic plasticity in motor learning, and closed-loop neuroprosthetics for tremor management. Funding sources include the European Research Council, Engineering and Physical Sciences Research Council, and industry collaborations. The Be.Neural Lab’s work is showcased on their dedicated website (https://beneural.ic.ac.uk).
Dr. Cassandra Sampaio Baptista is a Lecturer at the University of Glasgow's School of Psychology & Neuroscience. Her research focuses on brain plasticity in adulthood, particularly exploring how experiences like skill learning or rehabilitation influence structural and functional changes in the brain. She employs neuroimaging techniques such as fMRI neurofeedback and MRI to investigate mechanisms of myelin and white matter plasticity. Her work emphasizes translational applications, including stroke rehabilitation and promoting healthy aging. Key contributions include demonstrating myelin's role in motor learning and developing MRI protocols for white matter analysis. She collaborates on projects funded by the BIAL Foundation (2025–2026) and has supervised multiple postgraduate students. Recent publications highlight studies on oligodendrocyte dynamics, neurofeedback interventions for stroke survivors, and cross-species neuroscience approaches. While no specific awards are listed, her extensive publication record reflects her leadership in neuroplasticity research.
J. Anthony Movshon is a Professor at New York University (NYU) in the Department of Psychology and a key member of NYU's Center for Neural Science (CNS). His research focuses on the primate visual system, particularly the encoding and decoding of visual information in cortical areas like V1 and MT, and its role in behavior and perception. Education: Doctorate in Visual Neurophysiology and Psychophysics from Cambridge University Research Interests: Movshon investigates the functional architecture of the visual cortex, emphasizing motion, form, and color processing. His work explores how neural activity relates to perceptual decisions and motor behavior, using electrophysiological recordings, neuroimaging, and computational models. He also studies developmental disorders like amblyopia and their impact on visual system organization. Publications: His recent work spans visual texture selectivity in V2, contextual modulation in neural responses, motion processing in MT, and decoding mechanisms in visual cortex. These studies employ interdisciplinary approaches blending neurophysiology, computational neuroscience, and cognitive modeling. Labs & Collaborations: Movshon leads the Visual Neuroscience Laboratory at NYU, collaborating with researchers such as Michael Hawken, Lynne Kiorpes, and Eero Simoncelli.
Marc V Fuccillo is an Associate Professor of Neuroscience at the Perelman School of Medicine, University of Pennsylvania, where he leads a research laboratory focused on understanding the neural circuit mechanisms underlying behavioral control. His work bridges molecular, synaptic, and behavioral approaches to investigate how striatal circuits regulate mouse behavior from simple motor patterns to complex goal-directed actions. Fuccillo holds dual appointments in the Neuroscience and Cell and Molecular Biology Graduate Groups at Penn and maintains an active laboratory investigating the synaptic and circuit basis of neuropsychiatric disorders. Education: B.A. in Molecular and Cellular Biology and Music Performance (Violin) from Brown University (1998) Ph.D. in Developmental Genetics from New York University School of Medicine (2007) M.D. from New York University School of Medicine (2008) Fuccillo's research centers on the synaptic and circuit mechanisms of behavioral control, with particular emphasis on striatal circuits. His laboratory employs a range of technologies including mouse genetics, in vitro electrophysiology, in vivo imaging, and quantitative behavioral analysis to explore how neural circuits of the striatum regulate behavior and how disruptions in these circuits contribute to neuropsychiatric disorders. His work has particularly focused on autism-associated abnormalities in behavioral control, examining how synaptic adhesion molecules like neuroligins and neurexins shape circuit function and behavior, with significant findings regarding D1 dopamine receptor positive medium spiny neurons in the nucleus accumbens. Analysis of Fuccillo's recent publications reveals a strong focus on striatal circuit function across multiple dimensions. His work spans molecular neuroscience (examining synaptic adhesion molecules), cellular physiology (studying specific neuron types in striatal circuits), systems neuroscience (mapping circuit connectivity), and behavioral neuroscience (quantifying motor learning and decision-making). A unifying theme is how disruptions in specific molecular pathways lead to circuit-level abnormalities that manifest as behavioral phenotypes relevant to neuropsychiatric disorders, with particular attention to autism, OCD, and schizophrenia models. Scientific Recognition: Publications in high-impact journals including Nature Neuroscience, Current Biology, Cell Reports, and Neuron Research supported by multiple NIH grants including NIMH F32, NIMH K01, and HHMI Gilliam Fellowship awards for lab members Fuccillo actively mentors a diverse group of trainees including postdoctoral fellows, graduate students, and undergraduates. His laboratory has produced numerous successful alumni who have gone on to faculty positions, medical residencies, and graduate programs at prestigious institutions. His mentoring approach emphasizes technical skill development across multiple neuroscience disciplines while fostering independent scientific thinking. Current research in his lab is supported by NIH funding focused on understanding the molecular architecture of striatal circuits and their role in behavioral control, with three major research directions exploring molecular logic of striatal circuits, circuit mechanisms of behavioral control, and striatal dysfunction in neuropsychiatric disease models. The Fuccillo Laboratory operates within the Department of Neuroscience at the University of Pennsylvania, with access to state-of-the-art facilities for molecular, electrophysiological, imaging, and behavioral neuroscience research. The lab maintains active collaborations with other neuroscience research groups at Penn and beyond, creating a rich intellectual environment for studying the neural basis of behavior. Current research directions include investigating whether there is a molecular logic to striatal circuit composition, how striatal circuits shape behavioral control, and what mouse models of autism, schizophrenia, and OCD can reveal about striatal circuit dysfunction in disease pathophysiology.
Takako Fujioka is an Associate Professor of Music at Stanford University, affiliated with the Center for Computer Research in Music and Acoustics (CCRMA). Her research focuses on the neural mechanisms underlying auditory perception, auditory-motor coupling, and music-supported therapy for neurorehabilitation. She holds a Ph.D. in Physiology from the Graduate University for Advanced Studies, Japan, and M.Sc./B.Eng. degrees in Electrical Engineering from Waseda University. Her work combines neurophysiological techniques such as MEG and EEG to study brain plasticity in development, aging, and stroke recovery. Notable contributions include investigating how music influences motor and cognitive recovery in stroke patients, as well as exploring the neural basis of musical perception through rhythmic synchronization and pitch discrimination studies. Supported by awards from the Canadian Institutes of Health Research during her postdoctoral work at the Rotman Research Institute, her research bridges clinical neuroscience and music cognition. Dr. Fujioka’s expertise spans auditory neuroscience, neurorehabilitation, and technology-assisted music therapy. She has pioneered studies on tactile mapping for cochlear implant users and networked music performance systems, emphasizing cross-modal perception and human-technology interaction. Her findings contribute to both theoretical understanding of auditory processing and practical applications in medical and educational settings. Awards: Canadian Institutes of Health Research Awards (postdoctoral phase) Labs/Teams: CCRMA, Stanford Music Perception Laboratory, Rotman Research Institute collaborations Key Themes: Neuroplasticity, Music-Mediated Rehabilitation, Auditory-Motor Integration, Multisensory Processing Her recent work examines aging-related changes in binaural hearing and the role of beta/gamma oscillations in rhythmic processing. She advocates for translational research that connects neural mechanisms with real-world therapeutic interventions.
Steve Chase is a Professor at Carnegie Mellon University , affiliated with the Biomedical Engineering , Electrical and Computer Engineering , Neuroscience Institute , and Robotics Institute departments. His research spans Computational Neuroscience , Neural Engineering , and Systems Neuroscience , with a focus on neural circuits, motor control, and brain-computer interfaces (BCI). Research Areas: Sensation & Perception, Methods Development, Diseases & Disorders, Physiological & Anatomical Methods. Lab Highlights: Development of the RotaWheel, memory trace studies in the motor cortex, and investigations into BCI stabilization and learning dynamics. Scientific Contributions: His lab has published extensively in journals like Neuron , Nature Computational Science , eLife , and PNAS , with notable works on neural activity patterns, dimensionality reduction in calcium imaging, and sensory constraints on motor cortex modulation. Students and postdocs in his lab have received awards, including the CNBC best paper award.
Owen R. White is a Professor in the Department of Epidemiology & Public Health at the University of Maryland School of Medicine, serving as Associate Director of the Institute for Genome Sciences and Associate Director of Research Collaboration & Development. He leads a team of 25 scientists and engineers developing genomic annotation pipelines and data analysis tools for state-of-the-art research in microbiome and multi-omic studies. His academic background includes: BS in Biotechnology from the University of Massachusetts (1985) PhD in Molecular Biology from New Mexico State University (1992) Postdoctoral Fellowship in Genome Informatics at the Institute for Genomic Research (TIGR) (1994) Dr. White's research spans bioinformatics, genomics, transcriptomics, and metagenomics with emphasis on data management, metadata standards, ontologies, and cloud systems. His work has been foundational for large-scale initiatives like the Human Microbiome Project (HMP) and Integrative Human Microbiome Project (iHMP), generating over 50,000 datasets totaling 10 terabytes of multi-omic data. Analysis of his recent publications reveals a strong trend toward neuroscience multi-omics (BRAIN Initiative), cloud-based data infrastructure, and ethical data sharing frameworks. His work consistently bridges microbiome research with emerging fields like single-cell analysis and Alzheimer's disease biomarker discovery through integrated data platforms. Notable awards include: Benjamin Franklin Award for Open Access in the Life Sciences (2015) Kumho Science International Award in Plant Molecular Biology and Biotechnology (2001) As Principal Investigator for major NIH-funded centers, he has secured sustained support for the HMP Data Analysis and Coordination Center and iHMP Data Coordination Center. His team's work combines fee-for-service models with collaborative research funding to maintain cutting-edge genomic analysis capabilities. The Institute for Genome Sciences houses his computational team responsible for developing production annotation pipelines, database systems, and visualization tools that serve researchers across the University of Maryland School of Medicine and national consortia.
Jason Ritt is an Associate Professor of Brain Science (Research) and Scientific Director of Quantitative Neuroscience at the Robert J. and Nancy D. Carney Institute for Brain Science, Brown University. He holds affiliations with the Data Science Institute and collaborates across disciplines on quantitative research methods. Education : B.S., M.A., and Ph.D. in Neuroscience from Boston University (1997–2003). Research : Focuses on neural processing during active sensing and neuroengineering for neurostimulation. Combines electrophysiology, optogenetics, and theoretical approaches in rodent models. Develops closed-loop systems for studying sensory neural prosthetics and brain-machine interfaces. Key areas include synaptic diversity, neurocontrol algorithms, and sensory restoration. Teaching : Instructs NEUR 2100 NeuroPracticum, integrating hands-on neuroscience research training.
Dr. Sabine Krabbe is a Group Leader at the German Center for Neurodegenerative Diseases (DZNE) in Bonn, Germany, where she leads research on neural circuit mechanisms underlying adaptive learning and state-dependent decision-making. Her work integrates neuroscience, molecular biology, and behavioral approaches to understand how internal states influence behavior and how these processes are disrupted in neurological disorders. Dr. Krabbe's research focuses on the interactions between midbrain circuits of the substantia nigra and ventral tegmental area with their output structures such as the striatum and amygdala. She investigates how these networks integrate internal states with environmental cues to produce appropriate behavioral responses. Her laboratory employs state-of-the-art techniques including deep-brain calcium imaging at single-cell resolution in mice, opto- and pharmacogenetic manipulations, anatomical tracings, and molecular approaches to characterize neural circuit elements in detail. Her recent publications reveal significant insights into amygdala interneuron plasticity during fear learning, brain-wide representational drift in memory consolidation, and the molecular mechanisms underlying Parkinson's disease progression. Her work demonstrates how activity patterns within specific neural circuits change in early stages of neurodegenerative diseases and how this dysfunction contributes to cognitive deficits and emotional disturbances. Dr. Krabbe is actively involved in the neuroscience community, organizing the BonnBrain Conference 2026 and sharing research through social media platforms. She has established herself as an emerging leader in the field of systems neuroscience with a particular focus on the neural basis of emotional states and decision-making processes.
David Melcher is Professor of Psychology and Program Head in Psychology at New York University Abu Dhabi (NYUAD), where he also serves as a Global Network Professor. He is affiliated with the Division of Science and leads the Perception and Active Cognition Lab, focusing on the integration of perception, attention, memory, and action within a cognitive neuroscience framework. PhD in Psychology and Cognitive Science, Rutgers University (2001) Former researcher and professor in Italy and the UK Current leadership: Program Head, Psychology, NYUAD David Melcher's research centers on cognitive neuroscience , particularly how perception, attention, working memory, eye movements, and self-motion interact to shape cognition and behavior. His lab emphasizes active cognition —the idea that perception is not passive but dynamically shaped by action, context, and goals. He investigates how temporal dynamics in neural processing organize perceptual experiences and guide decision-making. His work spans both healthy and clinical populations, exploring individual differences in spatial and temporal processing across the lifespan. The 15 most recent publications reflect a consistent focus on temporal organization in cognition , perception-action coupling , and neural mechanisms of attention and memory . Keywords across these works include cognitive neuroscience, perception, and neuroimaging, with subfields ranging from eye movement research and neural synchrony to computational modeling and clinical neuropsychology. Collectively, they demonstrate a trajectory toward integrative models of brain function that bridge behavioral, neuroimaging, and computational approaches. Among his notable recognitions is the Distinguished Scientific Award for Early Career Contribution to Psychology from the American Psychological Association (2011), highlighting the early impact of his work in cognitive neuroscience. Distinguished Scientific Award for Early Career Contribution to Psychology, APA (2011) David Melcher has advised numerous students through capstone projects in psychology and computer science, fostering interdisciplinary research at the intersection of cognitive science and technology. His research has been generously supported by major funding agencies including the European Research Council , the US National Institutes of Health , the Italian Ministry of Research and Education , and the Chinese Ministry of Foreign Expert Affairs . He also contributes to the academic community as a member of the editorial boards of Journal of Vision , Psychonomic Bulletin & Review , Perception , and iPerception . He leads the Perception and Active Cognition Lab at NYUAD, which employs a multidisciplinary approach combining behavioral experiments, neuroimaging (fMRI, EEG, MEG), eye-tracking, computational modeling, and clinical assessments. The lab’s research aims to understand how the brain constructs stable percepts from dynamic sensory input, particularly during active engagement with the environment.
Stefano Fusi is an Associate Professor of Neuroscience at Columbia University's Vagelos College of Physicians and Surgeons, with joint affiliations at the Mortimer B. Zuckerman Mind Brain Behavior Institute and Kavli Institute. His laboratory focuses on computational modeling of neural circuits and neuromorphic engineering. Education PhD in Physics, Hebrew University of Jerusalem (1999) BS in Physics, Sapienza University of Rome (1992) Research Focus Fusi investigates how biological complexity supports neural computation through three primary domains: theoretical analysis of neural circuit dynamics, representational geometry in learning systems, and hardware implementations of brain-inspired algorithms. His work bridges machine learning, neurophysiology, and theoretical physics, emphasizing high-dimensional representations and memory optimization. Recent publications demonstrate consistent focus on neural coding principles across hippocampus, prefrontal cortex, and sensory systems, with innovations in modeling working memory, stress responses, and cross-species computational paradigms. Collaborations & Labs Leads an interdisciplinary laboratory collaborating with Columbia experimental neuroscientists, MIT engineers, and Stanford computational researchers to validate theoretical models. Current projects include neuromorphic hardware development and neural decoding of emotional states.
Chang S. (CS) Nam is a Professor of Industrial and Systems Engineering at North Carolina State University, with affiliations in the UNC/NCSU Joint Department of Biomedical Engineering and the Department of Psychology. He holds editorial roles as Editor-in-Chief of Brain-Computer Interfaces journal and is a Fellow of the Human Factors and Ergonomics Society. His research focuses on advancing human-centered technologies through neuroergonomics, brain-computer interfaces (BCIs), and rehabilitation engineering, supported by grants from NSF, AFRL, AFOSR, and the Laboratory for Analytic Sciences. Education: Ph.D. in Industrial Engineering, Virginia Tech (2003) MSIE in Industrial Engineering, State University of New York at Buffalo (2000) Research Interests: His work spans neurorehabilitation, haptic interaction design, and BCI applications, aiming to bridge human cognitive and neural processes with technological systems. Key areas include adaptive human-computer interaction, EEG-based emotion recognition, and spatial augmented reality for skill training. Grants & Awards: Recipient of NSF CAREER Award (2010), Air Force Summer Faculty Fellowship (2018), and the Leland S. Kollmorgen Spirit of Innovation Award (2019) Editor of Brain-Computer Interfaces Handbook: Technological and Theoretical Advances (CRC Press) Advising & Labs: Advises students like Lingchao Mao and Priscille Koutouan Leads the Brain-Computer Interface and Neuroergonomics Lab, developing BCI systems for communication in vegetative states and neurorehabilitation
Michael J. Frank is the Edgar L. Marston Professor of Psychology and Professor of Brain Science at Brown University's School of Cognitive, Linguistic, and Psychological Sciences. He holds academic affiliations with the Carney Institute for Brain Science and specializes in cognitive neuroscience, computational neuroscience, and decision-making processes. Frank earned his Ph.D. in Neuroscience & Psychology from the University of Colorado at Boulder in 2004, and joined Brown University in 2011 after serving as a Professor at the University of Arizona. His research integrates computational modeling and experimental methods to explore neural mechanisms underlying reinforcement learning, decision-making, and cognitive control, with a focus on prefrontal cortex-basal ganglia interactions and dopamine modulation. Frank's honors include the Troland Research Award (2021), Kavli Fellowship (2016), and the Cognitive Neuroscience Society Young Investigator Award (2011). He is an editor for eLife, Behavioral Neuroscience, and the Journal of Neuroscience. His lab, based at http://ski.clps.brown.edu, investigates topics such as neural circuit models of cognitive control, neuropsychological testing, and translational applications of computational models in psychiatry. Frank's research emphasizes interdisciplinary approaches, combining behavioral experiments, neuroimaging (fMRI, EEG), and pharmacological studies to dissect brain-behavior relationships. Key findings include insights into dopamine's role in motivation, decision-making deficits in schizophrenia, and computational phenotyping of mental disorders. His work bridges basic science and clinical applications, aiming to inform therapeutic strategies for neurological and psychiatric conditions.
