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
Professor Julie Harris is a faculty member at the University of St Andrews, holding the position of Professor of Psychology within the School of Psychology and Neuroscience since 2005. She previously held academic posts at Newcastle University and the University of Edinburgh, and conducted postdoctoral research at the Smith-Kettlewell Eye Research Institute in California. Her research focuses on human visual processing, including vision and camouflage, depth perception, binocular stereopsis, and eye movements in natural environments. She earned a BSc in Physics from Imperial College London and a DPhil from Oxford University. Research interests include exploring how visual systems process environmental cues for depth and motion, with applications in camouflage design and stereo display technologies. Her lab employs psychophysical, behavioral, and computational methods. Notable projects address countershading camouflage effectiveness, motion-in-depth perception, and visual-motor interactions in driving scenarios. Selected grants include funding from BBSRC, Leverhulme Trust, and Medical Research Scotland. Collaborations span evolutionary biology, neuroscience, and applied vision science. She supervises PhD students Federico De Filippi and Rebecca Maguire. Awards include the Davida Teller Award Nomination and Fellowship in the Society of Biology. Labs/Teams: Julie Harris Lab (St Andrews), St Andrews Vision Labs, and the Institute of Behavioural and Neural Sciences. Current projects investigate warning signal design, visual perception in virtual environments, and the impact of visual processing on driving ability.
Suresh Krishna is an Associate Professor in the Department of Physiology at McGill University's Faculty of Medicine. His research focuses on the neurophysiological and computational basis of sensory processing, attention, and eye movements, with applications to brain-machine interfaces and human health. He works with human subjects, non-human primates, and open datasets using in-vivo electrophysiology, eye-tracking, and computational modeling. Research interests include visual attention mechanisms, saccadic eye movement control, neural coding of motion perception, and the interplay between attention and decision-making. His work bridges basic neuroscience with translational applications such as improving neural prosthetics and understanding perceptual disorders. Recent work highlights how neural remapping processes during saccades underlie spatial perception, and how attention modulates neural activity patterns in visual cortex. The lab's publications reveal critical insights into the temporal dynamics of attentional shifts and their neural substrates, particularly in areas MT and MST. Dr. Krishna's team also investigates auditory temporal processing in the inferior colliculus, exploring correlations between neuronal responses to sound modulation. Their findings contribute to understanding how sensory systems encode temporal information across modalities. Research is conducted in the M2B3 Lab (http://m2b3.lab.mcgill.ca), which integrates experimental and computational approaches to study brain mechanisms underlying perception and action. No specific awards are listed, but ongoing work involves major contributions to primate neurophysiology and translational neuroscience.
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.
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.
Dr. Elisa Donati is a researcher and independent group leader at the Institute of Neuroinformatics , affiliated with both the University of Zurich and the Swiss Federal Institute of Technology Zurich . Her work bridges neuromorphic engineering, biomedical signal processing, and wearable healthcare technologies, with a focus on creating brain-inspired systems for neuroprosthetics and rehabilitation. Affiliation: Institute of Neuroinformatics, University of Zurich & ETH Zurich Email: elisa@ini.uzh.ch Elisa’s research emphasizes developing neuromorphic signal processing strategies for wearable and embedded systems, enabling real-time closed-loop interactions with the nervous system. She specializes in translating neuroscience insights into energy-efficient technologies for digital health applications, including neuroprosthetics and personalized biomedical devices using neuromorphic hardware. Her recent publications (2024–2025) highlight advancements in gesture recognition via EMG and event-based systems, neuromorphic heart rate monitoring , and spiking neural network architectures . These works span biomedical signal processing, low-power computing, and adaptive algorithms, reflecting her commitment to robust, real-time, and brain-inspired solutions for healthcare. Elisa’s contributions to neuromorphic computing are evident in her exploration of heterogeneous population encoding , event-driven processing , and ultra-low-power microcontrollers . Her projects often integrate wearable systems with neuroscience, aiming to improve prosthetic control and rehabilitation technologies .
Dr. Hayriye Cagnan is a Senior Lecturer (equivalent to Associate Professor) at Imperial College London and Associate Unit Member at the MRC Brain Network Dynamics Unit. She holds a PhD in Neuroscience from the University of Amsterdam and Philips Research Laboratories (2010), an MSc in Engineering and Physical Science in Medicine from Imperial College London, and a BS in Electrical and Electronics Engineering from Cornell University as a Fulbright Scholar. Her research develops theory-driven strategies for selective modulation of brain rhythms using: Theoretical disease models and stimulation paradigms Dynamic neuromodulation approaches Wearable devices for remote therapy optimization Advanced signal processing techniques Her recent publications (2015-2025) demonstrate consistent focus on tremor pathophysiology, neural oscillations in Parkinson's disease, and advanced brain stimulation technologies. Research employs computational modeling, EEG, magnetoencephalography, and both invasive/non-invasive stimulation techniques. Awards & Fellowships: Fulbright Scholarship (2000-2004) British Chevening Scholarship (2004) MRC Skills Development Fellowship (2015) MRC Career Development Award (2018) Dr. Cagnan leads an independent research group originally established at the MRC Brain Network Dynamics Unit in 2018, maintaining close collaborations with clinical neuroscientists and engineers to translate basic research into therapeutic applications.
Lee Miller is a Professor in the Department of Neurobiology, Physiology, and Behavior at the University of California, Davis, College of Biological Sciences. His research integrates neural engineering, physiology, and computational methods to develop communication restoration technologies and investigate sensory processing mechanisms. His primary research interests include neural engineering for speech neuroprosthetics, electrophysiological analysis of speech production, auditory neuroscience, and geometric approaches to neuromuscular signal decoding. He employs surface electromyography (EMG), electroencephalography (EEG), and computational modeling to study brain-machine interfaces for speech restoration and multisensory integration. Recent publications reveal a dominant focus on EMG-based speech neuroprostheses, with geometric and topological analysis of neuromuscular signals emerging as a key methodology. His lab has pioneered non-invasive approaches to speech articulation decoding, created standardized EMG databases, and investigated neural mechanisms of attention in speech-in-noise processing. This work bridges engineering innovation with fundamental neuroscience to address communication disorders. Professor Miller leads the Miller Lab at UC Davis, which specializes in neural engineering for communication restoration. The lab develops real-time speech synthesis systems from neural signals and investigates the physiological basis of speech production and perception using multimodal recording techniques.
Prof. Jan Theeuwes is a Full Professor of Cognitive Psychology at the Vrije Universiteit Amsterdam's Faculty of Behavioural and Movement Sciences, leading the ERC-funded research group on statistical learning and attention. He holds additional roles as Distinguished Visiting Research Professor at the William James Center for Research (Lisbon) and Visiting Professor at Zhejiang University (China). With over 474 publications and two ERC Advanced Grants (2013 & 2019), his work spans visual attention, statistical learning, and applied human factors in road design. He pioneered the 'Self-Explaining Roads' concept, revolutionizing global road safety design, and co-developed Open Sesame, a widely used open-source experiment builder. His research integrates EEG, fMRI, and computational modeling, addressing topics like distractor suppression, emotion, and leadership influence. Over 25 PhD students have graduated under his mentorship, many securing academic roles across Europe. Education: Cum laude degrees in Experimental Psychology (Tilburg University) and a PhD (VU Amsterdam, 1992). Key awards include the Bertelson Award (2001) and KNAW membership (2010). He advises the Dutch Department of Transportation and founded the Institute for Brain and Behavior Amsterdam (IBBA) in 2016. Ancillary roles include leadership in European psychological societies and consultancy for Attention Architects, applying eye-tracking research in corporate settings.
Il Memming Park is a Professor and Group Leader at the Centre for Restorative Neurotechnology within the Champalimaud Research division of the Champalimaud Foundation in Lisbon, Portugal. His work bridges computational neuroscience, machine learning, and statistical modeling to understand neural dynamics and computation. Dr. Park's research focuses on developing statistical and machine learning methods for analyzing neural time series data. His lab investigates the appropriate language for neural dynamics that can explain and generate specific predictions on neural data and behavior. He builds on foundations of dynamical systems and stochastic processes to create models of neural computation tightly tied to biology. His publications reveal a strong emphasis on developing methods like variational latent Gaussian processes and exponential family dynamical systems to extract meaningful patterns from complex neural recordings. His work spans both theoretical developments in computational methods and their application to real neural data from areas like visual cortex, parietal cortex, and other brain regions involved in perception and decision making. Dr. Park has previously held positions at Stony Brook University and the University of Texas at Austin, where he was affiliated with departments of Neurobiology and Behavior, Applied Mathematics and Statistics, Psychology, and Neuroscience. His lab at Champalimaud includes multiple PhD students, postdoctoral researchers, and research staff working collaboratively on various aspects of neural data analysis and modeling. The team employs an interdisciplinary approach combining neuroscience, statistics, machine learning, and dynamical systems theory.
James Tung is an Associate Professor at the University of Waterloo’s Faculty of Engineering, Department of Mechanical and Mechatronics Engineering. His research focuses on assistive technology, rehabilitation engineering, and mobility solutions for individuals with disabilities. He leads the Neural and Rehabilitation Engineering (NRE) Lab, which develops wearable sensors, robotics, and machine learning tools to enhance mobility and monitor motor rehabilitation. He teaches courses including BME 355 (Physiological Systems Modelling), BME 540 (Neural and Rehabilitation Engineering), and ME/MTE engineering modules. The lab collaborates with clinical and industry partners to translate research into practical solutions, addressing real-world mobility challenges and aging demographics. His research spans real-world gait analysis, fall risk assessment, and prosthetic design, with a focus on pediatric neurodevelopmental disorders and elderly mobility. The NRE Lab emphasizes interdisciplinary work, combining biomechanics, robotics, and data science to improve healthcare outcomes. Lab Alumni: Includes researchers like Robin Murdock (Myant Inc.), Andrew Hart, and Raj Senthilkumar, contributing to prosthetics and gait analysis. Partnerships: Engages clinical and industry stakeholders for knowledge translation and commercialization. Current projects include developing smart rollators, biofeedback prosthetics, and sensor-based assessment tools to address mobility limitations in aging populations and individuals with disabilities.
John Serences is a Professor in the Department of Psychology at the University of California, San Diego (UCSD). He leads the Perception and Cognition Lab, which participates in the Neuroscience Graduate Program. His research focuses on how behavioral goals and attention influence perception, memory, and decision-making, employing techniques like psychophysics, computational modeling, EEG, and fMRI. Key projects explore serial dependence, neural adaptation in visual cortex, and the interplay between sensory processing and mnemonic storage. Recent work highlights mechanisms reconciling repulsive neuronal adaptation with attractive behavioral biases. Affiliations: Department of Psychology, UCSD; Neuroscience Graduate Program. Research Themes: Visual perception, working memory, decision-making, neuroimaging. His lab investigates neural dynamics underlying cognitive processes, with particular emphasis on how attentional modulations and stimulus history shape neural representations. Notable contributions include studies on adaptive sensory coding and the role of top-down signals in perceptual stability.
Gunnar Blohm is an Assistant Professor in the Department of Biomedical and Molecular Sciences at Queen's University, affiliated with the School of Medicine and Faculty of Health Sciences. His research focuses on sensorimotor neuroscience, particularly 3D sensorimotor control, eye-hand coordination, and computational modeling of neural processes. He holds a Ph.D. from Université Catholique de Louvain and has held postdoctoral positions at York University and his alma mater. Cross-appointed to the School of Computing, Department of Psychology, and Department of Mathematics and Statistics, he is also Vice-Director of the Connected Minds initiative. His research integrates behavioral experiments, brain imaging (MEG/EEG), and patient studies to understand how sensory information is transformed into goal-directed actions. Key areas include visuomotor transformations, multisensory integration, and Bayesian processes in neural computations. Blohm leads the Computational Sensorimotor Neuroscience Lab, emphasizing collaborative projects like Neuromatch Academy and contributions to open science initiatives. Affiliated with Queen's Centre for Neuroscience Studies and Ingenuity Labs, his work bridges computational approaches with clinical applications, aiming to develop frameworks for understanding brain dysfunction and clinical tools. His recent articles explore topics like saccade dynamics, pupil responses, and generative adversarial collaborations in scientific discourse.
Michael J. Shelley is the Lilian and George Lyttle Professor of Applied Mathematics and holds joint appointments in Mathematics, Neural Science, and Mechanical Engineering at New York University's Courant Institute of Mathematical Sciences. He also serves as Co-Director of the Applied Mathematics Laboratory and Director of the Center for Computational Biology at the Flatiron Institute. Education: PhD (Applied Mathematics) from the University of Arizona (1985), MS (Applied Mathematics) from the University of Arizona (1984), BA (Mathematics) from the University of Colorado (1981). Research: Focuses on complex phenomena in active matter, biophysics, and complex fluids. Key areas include fluid-structure interactions (e.g., swimming/flying mechanics), cytoskeletal dynamics, and collective behavior in biological systems. Collaborates closely with experimentalists through the Applied Math Lab and Flatiron Institute. Labs & Affiliations: Co-Director, Applied Mathematics Laboratory; Director, Center for Computational Biology (Simons Foundation); affiliated with NYU’s Courant Institute and Department of Mathematics. Notable Work: Models for microtubule-motor assemblies, active suspensions, and fluid-structure interactions. Pioneered computational frameworks for Stokes suspensions and fiber dynamics in viscous fluids.
