Josep Marco Pallares is a Professor at the University of Barcelona's Faculty of Psychology, affiliated with the Department of Cognition, Development and Educational Psychology. He leads the Brain Dynamics and Structure of Human Cognition (BraCo) research group and holds an ICREA Academia Fellowship (2018-2023). His work focuses on neural mechanisms underlying reward processing, music perception, and social cognition using neuroimaging techniques. Education: Licenciatura in Psychology (University of Barcelona, 2000), Doctorate in Neuroscience (2012), and Doctorat (University of Barcelona, 2005) Research interests include brain oscillations in reward systems, music-evoked emotions, and decision-making. His recent studies explore how theta and gamma oscillations underpin pleasantness responses to music and social information. Ongoing projects investigate neural correlates of gambling behaviors and white matter correlates of music reward sensitivity. Awards: ICREA Academia Fellowship (2018) Has supervised doctoral theses on music reward processing and atypical reinforcer anticipation mechanisms. Active in teaching courses on neuroimaging techniques and music psychology at the University of Barcelona. Labs/Teams: Principal Investigator of the BraCo group, collaborating with AGAUR and Ministerio de Ciencia-funded projects.
Dr. Manuel Carro Dominguez is a Researcher at the Department of Neural Control of Movement, ETH Zürich. His work focuses on understanding the neural mechanisms underlying sleep dynamics, arousal regulation, and their impact on motor performance and cardiovascular function. He specializes in techniques such as auditory stimulation, pupil-based neurofeedback, and EEG/ECG monitoring to explore sleep oscillations, cortical excitability, and their clinical applications. His research bridges neuroscience, biomedical engineering, and sleep medicine, with a particular emphasis on enhancing human physiology through targeted interventions during sleep. Key research interests include: sleep modulation via auditory stimuli, pupilometry as a marker of arousal states, and the development of medical devices for gas sensing and closed-loop biofeedback systems. His studies often integrate multidisciplinary approaches to address translational challenges in neurophysiology and cardiovascular health. Recent publications highlight advancements in auditory stimulation effects on cardiac function, the role of K-complexes in sleep dynamics, and the design of gas sensing technologies for biomedical applications. His work contributes to both fundamental neuroscience and applied biomedical engineering, aiming to improve clinical outcomes through innovative sleep-based interventions.
Professor Dario Farina is Chair in Neurorehabilitation Engineering at the Department of Bioengineering, Faculty of Engineering, Imperial College London. He has previously served as Full Professor at Aalborg University, Denmark, and at the University Medical Center Göttingen, Germany, where he founded and directed the Institute of Neurorehabilitation Systems. His research spans biomedical signal processing, neural control of movement, and neurorehabilitation technology, with extensive contributions to electromyography, motor unit analysis, and neural interfaces. Chair in Neurorehabilitation Engineering, Imperial College London Former Full Professor, Aalborg University and University Medical Center Göttingen Founder and Director, Institute of Neurorehabilitation Systems Key Affiliations: Centre for Neurotechnology, Artificial Intelligence Network, Robotics Forum, Neuromechanics and Rehabilitation Technology His research focuses on biomedical signal processing , neural control of movement , and neurorehabilitation technology . He investigates how neural signals control muscles, develops methods to decode motor unit activity from EMG, and designs neural interfaces for prosthetics and rehabilitation. His work integrates computational modeling, signal processing, and clinical applications to improve bionic systems and neurorehabilitation outcomes. The recent publications (2024–2025) show a strong emphasis on high-density EMG , real-time motor unit decomposition , peripheral and cortical neural interfacing , closed-loop control systems , and AI-driven biosignal analysis . Key themes include decoding spinal and cortical signals, improving prosthetic control, understanding tremor mechanisms, and developing open-source tools for motor unit analysis. The work bridges neuroscience, engineering, and clinical practice. Scientific awards and honors include: Royal Society Wolfson Research Merit Award (2016) IEEE EMBS Early Career Achievement Award (2010) Nightingale Prize for best paper in MBEC (2007) Elected Fellow of EAMBES (2016) Elected Fellow of AIMBE (2012) Professor Farina has advised numerous researchers and students in neuroengineering and rehabilitation technology. He has led major research grants in neural interfaces and neurorehabilitation. He is Editor-in-Chief of the Journal of Electromyography and Kinesiology , an editor for IEEE Transactions on Biomedical Engineering and The Journal of Physiology , and has held editorial roles in multiple journals. He was President of ISEK (2012–2014) and is a Senior Member of IEEE. He leads a research group focused on neuromechanics, neural decoding, and bionic systems. The team develops tools like I-Spin live and MUedit for real-time motor unit identification and contributes to open-source platforms such as NeuroMotion . The lab collaborates internationally on projects involving spinal cord stimulation, prosthetic control, and wearable robotics, aiming to translate neural engineering advances into clinical rehabilitation.
Steven Zucker is the David & Lucile Packard Professor of Biomedical Engineering & Computer Science at Yale University, with additional appointments in Applied & Computational Mathematics. His work bridges computational vision, neurophysiology, and differential geometry to model human visual perception and cortical computation. Research Interests : Zucker's research focuses on computational vision , leveraging differential geometry to develop theories for curve detection, shading analysis, stereo vision, and 3D shape description. He also explores interdisciplinary applications in plant biology through auxin dynamics and political science via diffusion geometry. Article Trends : Recent publications emphasize 3D shape estimation from shading and texture flows curvature-driven neural computation models applications in plant venation and heart myofibril geometry psychophysical studies of color and orientation flows Scientific Contributions : Recognized as a Packard Professor, Zucker has pioneered Hamilton-Jacobi skeletons and curve indicator random fields . His work spans computer vision, neuroscience, and mathematical modeling.
Virginia de Sa is a Professor in the Department of Cognitive Science at the University of California, San Diego. Her research integrates computational modeling, psychophysics, and machine learning to investigate visual and multi-sensory perception, with a focus on understanding how humans learn and perceive through neural mechanisms. Her work emphasizes the synergy between human learning and machine learning, applying insights from both fields to advance understanding of perception. Notable projects include developing brain-computer interface (BCI) systems and analyzing biases in facial expression recognition algorithms. She leads the de Sa Lab, which explores the neural basis of learning through interdisciplinary methods, including EEG analysis and biologically inspired algorithms. Key research directions include improving BCI usability through adaptive spatial filtering, investigating pain assessment via facial and electrophysiological data fusion, and enhancing AI fairness in facial expression analysis. Dr. de Sa has contributed to grants such as the NSF-funded CHS project to enhance BCI reliability and collaborates on initiatives like AI-READI to improve healthcare data practices. Her lab’s BCI division focuses on interpreting EEG data for assistive technologies, while her work on divisive normalization bridges biological insights with artificial neural network design. Ongoing efforts explore zero-shot learning and the generalization of neural models to unseen tasks. Dr. de Sa’s interdisciplinary approach spans neuroscience, computer science, and engineering, with a commitment to advancing both theoretical understanding and practical applications in human-computer interaction.
Kuo-Fen Lee, PhD is a Professor at the Salk Institute for Biological Studies, holding the prestigious Helen McLoraine Chair of Molecular Neurobiology. He leads the Clayton Foundation Laboratories for Peptide Biology, where his research focuses on nerve regeneration, spinal cord injury, and molecular mechanisms underlying neural development and neurodegenerative diseases. His work bridges basic neuroscience with potential therapeutic applications for conditions like ALS, paralysis, and Alzheimer's disease. Dr. Lee received his educational training from multiple prestigious institutions: a degree in Plant Pathology from National Taiwan University; an MS in Cancer Enzymology and Cell Differentiation from National Yang-Ming Medical College, Taiwan; a PhD in Endocrinology from Baylor College of Medicine, Houston; and completed his postdoctoral training at the Whitehead Institute for Biomedical Research. His primary research interests center on understanding why humans cannot regenerate damaged nerves while many other animals can. Dr. Lee has made significant discoveries regarding the p45 protein, which promotes nerve regrowth in mice but is absent in humans (who instead have p75, which inhibits nerve growth). His laboratory also studies neuregulin signaling, neuromuscular synapse formation, and the role of various proteins like nestin in neural development and maintenance. His work often employs mouse models to investigate spinal cord injury, pain pathways, and neurodegenerative conditions. Analysis of Dr. Lee's recent publications reveals a consistent focus on molecular neurobiology with particular emphasis on neural signaling pathways, synaptic maintenance, and nerve regeneration mechanisms. His research spans from basic molecular mechanisms to potential therapeutic applications, with increasing attention to pain pathways, Alzheimer's disease models, and the intersection of neuroscience with immunology and metabolism in recent years. As holder of the Helen McLoraine Chair of Molecular Neurobiology, Dr. Lee has received significant institutional recognition for his contributions to neuroscience. While specific awards aren't detailed in the provided text, his sustained funding and leadership position indicate substantial peer recognition in his field. Dr. Lee's research program involves extensive collaboration with other neuroscience laboratories, as evidenced by his numerous co-authored publications across various neuroscience subdisciplines. His work has been consistently funded, allowing for the maintenance of an active research laboratory focused on nerve regeneration and molecular neurobiology. The Clayton Foundation Laboratories for Peptide Biology serves as the primary research environment for Dr. Lee's team, where they investigate molecular mechanisms of nerve development, regeneration, and degeneration using advanced genetic, molecular, and cellular approaches. The laboratory maintains active research programs in multiple areas of neural signaling and development.
David J. Field is a Professor of Psychology at Cornell University, affiliated with the College of Arts and Sciences. His research focuses on theories of sensory coding, visual processing, and the relationship between natural environmental structure and sensory system representations. He is an active member of the Graduate Field of Psychological Sciences and Human Development. His work spans computational neuroscience and visual perception, with a particular emphasis on efficient coding principles and neural responses to natural scenes. Key research interests include the spatiotemporal dynamics of visual processing, sparse coding models, and the application of advanced imaging techniques like dynamic electrode-to-image (DETI) mapping. His studies often bridge neuroscience with computer science, exploring how neural systems encode visual information efficiently. Recent publications emphasize the role of behavioral goals in shaping neural coding and the statistical properties of natural scenes. Dr. Field teaches courses such as PSYCH 3420 (Human Perception: Application to Computer Graphics, Art, and Visual Display) and contributes to graduate training programs in psychological sciences. His work has been published in top journals, reflecting a strong focus on interdisciplinary approaches to understanding perception and neural representation.
Dr. Burkhard Maess is a Research Professor and Group Leader at the Max Planck Institute for Human Cognitive and Brain Sciences, leading the Methods and Development Group Brain Networks. His research focuses on auditory and language processing, signal analysis, and dynamic modeling of neuronal networks. He holds a Diploma in Physics (University of Leipzig, 1987) and a PhD in Physics (University of Leipzig, 1990). His career includes postdoctoral positions at the Academy of Sciences of the GDR and the Free University of Berlin before joining the MPI in 1995. Since 2000, he has led research groups on MEG/EEG signal analysis and cortical network dynamics. His work integrates advanced neuroimaging techniques like MEG and EEG to study sensory processing, neural network dynamics, and the effects of aging on auditory attention. Key contributions include developing high-resolution BEM-FMM methods for source localization and analyzing cross-frequency coupling in neuroscience data. His group also explores spinal cord electrophysiology and the neural underpinnings of perceptual decision-making. Dr. Maess’ research spans cognitive neuroscience, biomedical engineering, and computational modeling, with a focus on bridging empirical findings with theoretical frameworks in neuroscience.
Teresa Cheung is an Adjunct Professor in the Department of Engineering Science at Simon Fraser University’s Faculty of Applied Sciences. Her research focuses on neuroimaging techniques, particularly magnetoencephalography (MEG), and their applications to understanding brain networks in health and disease. She holds a Ph.D. in Physics from SFU (2012) and completed a postdoctoral fellowship at the University of Cambridge (2012–2013). Research interests include: MEG instrumentation and optically pumped magnetometers (OPM) Cortical-cerebellar networks and cerebellar activity localization Neuroimaging of neurological disorders like major depressive disorder and epilepsy Functional and structural connectome analysis across the human lifespan Multimodal integration of MEG, MRI, fMRI, and DTI data Recent work emphasizes the relationship between cardiovascular health, brain aging, and cognitive resilience. Her studies span clinical applications (e.g., depression biomarkers) and technical advancements in neuroimaging systems. Collaborations include multi-site studies on depression and aging cohorts like the Cam-CAN project. Publications highlight innovative methods in MEG system design, neural network dysfunction analysis, and lifespan brain dynamics. Her work bridges engineering, neuroscience, and clinical research to advance non-invasive brain imaging and neurophysiological understanding.
Gagan Wig is an Associate Professor at the University of Texas at Dallas, School of Behavioral and Brain Sciences, with adjunct appointments in Psychiatry at UT Southwestern Medical Center. He directs the Wig Neuroimaging Lab, focusing on brain network connectivity across lifespan, healthy/pathological aging, and brain health disparities. His research employs structural/functional MRI, DTI, and TMS to study large-scale brain networks and their relationship to memory and attention. Professional preparation includes: Post-doctoral Associate in Neurology, Washington University School of Medicine (2012) Post-doctoral Associate in Psychology, Harvard University (2009) Ph.D. in Cognitive Neuroscience, Dartmouth College (2006) B.S. in Behavioral Neuroscience, University of British Columbia (2001) Research explores how brain networks change during aging and how socioeconomic status moderates these changes. His work reveals that education protects against brain network decline and that participant diversity is crucial for advancing brain aging research. Publications focus on neuroimaging of lifespan changes, Alzheimer's biomarkers, socioeconomic impacts on brain health, and methodological innovations in network analysis. Recent work demonstrates how functional network organization supports cognition despite Alzheimer's pathology and how data quantity affects network segregation measures. Awards include the Understanding Human Cognition Scholar Award from James S. McDonnell Foundation (2006). He has received significant funding including a $2.9M NIH grant studying socioeconomic links to Alzheimer's susceptibility and DARPA support for novel data sonification approaches.
Sebastian Seung is a Professor at Princeton University , affiliated with both the Department of Computer Science and the Princeton Neuroscience Institute . His career spans Harvard University (Ph.D., 1990), Bell Laboratories, and Massachusetts Institute of Technology before joining Princeton in 2014. An External Member of the Max Planck Society and 2008 Ho-Am Prize recipient, Seung merges machine learning with neuroscience . Research Focus : Pioneering connectomics , Seung developed technologies for reconstructing neural circuits from high-resolution brain images, including FlyWire for collaborative brain mapping. His work explores brain function, development, and plasticity , drawing parallels between fly visual systems and convolutional networks . Awards & Affiliations : 2008 Ho-Am Prize in Engineering External Member, Max Planck Society Technical Contributions : Led breakthroughs in 3D connected component labeling and high-throughput EM imaging for mammalian brains, partnering with NIH’s BRAIN Initiative to scale connectomics to whole mouse brains. Seung’s team has shifted from EM analysis to interpreting connectomes , focusing on neural circuit function and biological mechanisms in flies and mice. His lab alumni network spans institutions, advancing AI and neuroscience globally.
Alexei Koulakov is a Professor at Cold Spring Harbor Laboratory (CSHL) and the Charles Robertson Professor of Neuroscience. His research focuses on applying mathematical and computational approaches to unravel the principles of brain organization, particularly in sensory systems like olfaction and vision. Koulakov's work explores how neural circuits form during development, the role of genetic and experiential factors, and the evolutionary basis of brain architecture. Education: PhD in Physics from the University of Minnesota (1998). Key Research Areas: Olfactory system development, neural network modeling, and AI inspired by biological computation. Koulakov's recent publications emphasize cross-disciplinary integration of neuroscience and AI, including NeuroAI initiatives and DeepNose models predicting olfactory percepts. His team investigates how innate abilities are encoded genomically and how experience shapes neural networks. Scientific contributions include studies on primacy coding in olfaction, stochastic learning mechanisms , and high-throughput neural mapping . Awards include the Charles Robertson Professorship , reflecting his leadership in theoretical neuroscience. Koulakov collaborates extensively, with notable work on genomic bottlenecks , odor mixture interactions , and neural integrator models . His lab at CSHL is at the forefront of NeuroAI research, leveraging brain circuit insights to advance artificial intelligence.
Suel-Kee Kim is an Associate Research Scientist in Neuroscience at the Yale School of Medicine, Yale University. Their research focuses on neurodevelopment, stem cell biology, and cellular mechanisms underlying neurological disorders. Key areas include neural fate determination from pluripotent stem cells, molecular programs in macaque brain development, and transcriptomic analysis of neural differentiation pathways. Notable contributions include studies on cellular recovery post-ischemia, impaired neurogenesis in congenital hydrocephalus, and retinoic acid's role in prefrontal cortex patterning. Collaborations with leading labs like the Sestan Lab emphasize interdisciplinary approaches in neuroscience and regenerative medicine. Publications highlight innovative work in stem cell microenvironment engineering, forensic transcriptomics of flies, and pancreatic islet differentiation for diabetes therapy. Their research bridges basic science and translational applications in neurology and regenerative medicine.
Professor Andrew Jackson of Newcastle University is a leading researcher in neuroscience and neuroengineering, focusing on neural interfaces, optogenetics, and epilepsy. His work spans brain-computer interfaces, spinal cord stimulation, and sleep-dependent memory processes. Key research areas: closed-loop optogenetic systems, motor cortex dynamics, cerebellar-neocortical communication, and seizure pathway analysis. Collaborations with experts like Dr. Boubker Zaaimi, Professor Yujiang Wang, and Dr. Wei Xu. Develops implantable low-power platforms for real-time neural monitoring and stimulation. His recent publications highlight advancements in neuroprosthetics for motor recovery post-stroke/spinal injury, cortical chloride homeostasis in epilepsy, and mechanisms of brain self-regulation during movement and sleep. Technologies pioneered include flexible neural electrodes, temperature self-monitoring optoelectronics, and wearable bioelectrical signal systems. His work integrates computational neuroscience with clinical applications in motor disorders and epilepsy.
Christine Eckhardt is an Assistant Professor in the Department of Neurology at the T.H. Chan School of Medicine (UMass Chan Medical School), specializing in Neurocritical Care. She earned her MD from Harvard Medical School and holds an MS degree. Education: MD, Harvard Medical School, Boston, MA MS (unspecified field) Dr. Eckhardt's research focuses on neurocritical care, neurotoxicity syndromes, and EEG-based diagnostics. She develops quantitative EEG methods for assessing immune effector cell-associated neurotoxicity (ICANS) and delirium severity, with applications in CAR T-cell therapy and critical care neurology. Her recent publications (2022–2023) emphasize automated neurotoxicity detection , EEG signal processing , and health equity disparities in heart failure care. Key subfields include neurocritical care, computational neuroscience, and clinical outcome modeling.
