Christopher Honey is an Associate Professor in the Department of Psychological & Brain Sciences at Johns Hopkins University, affiliated with the Krieger School of Arts & Sciences. His research focuses on computational cognitive neuroscience, exploring how the brain processes sequential information such as language and memory. He holds a PhD from Indiana University and has held positions at Princeton University and the University of Toronto before joining JHU in 2016. Education: PhD in Psychological and Brain Sciences, Indiana University Postdoctoral Fellowship at Princeton University with Uri Hasson Bachelor’s in Applied Mathematics and English Literature, University of Cape Town Research Interests: Neural dynamics of memory and perception Temporal processing in the brain Cognitive modeling using computational methods Neuroimaging data standards (e.g., BIDS) Publications highlight his work on brain state fluctuations, neuroimaging data structures, and memory enhancement. His lab develops tools for analyzing fMRI and EEG data, emphasizing real-world applications like smartphone-based cognitive interventions. Lab and Collaborations: Active projects on narrative processing and hippocampal replay Development of open-source neuroscience tools like iELVis Focus on translational research for aging populations
Frank Russo is a Professor in the Department of Psychology at Toronto Metropolitan University, where he holds the NSERC-Sonova Senior Research Chair in Auditory Cognitive Neuroscience. He leads the Science of Music Auditory Research and Technology (SMART) Lab and holds affiliate and adjunct positions at the University Health Network and the University of Toronto, respectively. Research Interests: Dr. Russo's work lies at the intersection of auditory cognitive neuroscience, music psychology, and rehabilitation. His research explores how humans perceive music and speech, particularly under challenging conditions such as hearing loss or non-native accents. He investigates the cognitive and neural mechanisms of listening effort, emotional speech processing, and the social and therapeutic benefits of music, especially through community choirs and digital interventions. Publication Trends: His recent publications emphasize objective measurement of listening effort using functional near-infrared spectroscopy (fNIRS), music-based interventions for Parkinson’s disease and dementia, vocal and emotional responses to singing, and multisensory integration in beat perception. The work is highly translational, bridging basic cognitive neuroscience with clinical and community applications. Scientific Awards and Honors: NSERC-Sonova Senior Research Chair in Auditory Cognitive Neuroscience Fellow of the Canadian Psychological Association Fellow of Massey College Fellow of the Canadian Society for Brain, Behavior and Cognitive Science Past President of the Canadian Acoustical Association Advising and Grants: Dr. Russo actively mentors students and researchers, as evidenced by his co-authorship with numerous junior colleagues. He has secured major funding through NSERC and industry partnerships, enabling the development of impactful technologies such as hearing aid algorithms, sensory substitution systems, and digital therapeutics. His SingWell project fosters collaboration across academic, clinical, and community sectors. Labs and Teams: He directs the SMART Lab at Toronto Metropolitan University, a hub for interdisciplinary research on music, hearing, and cognition. The lab collaborates extensively with KITE Research Institute, Rehabilitation Sciences at the University of Toronto, and various community organizations focused on aging, hearing loss, and neurodegenerative conditions.
Dr. Pulin Gong is an Associate Professor in the School of Physics at the University of Sydney. His research focuses on understanding the self-organizing mechanisms of neural circuits' spatiotemporal dynamics and their computational principles. He investigates distributed dynamic computation via propagating neural waves, irregular neural activity variability, and coherent spatiotemporal patterns in large-scale neural data. His work combines experimental and computational approaches to unravel neural coding principles. Research interests include: Distributed dynamic computation (e.g., visual feature integration) Irregular neural dynamics and membrane potential fluctuations Coherent spatiotemporal wave patterns (e.g., spiral waves) Recent projects involve analyzing cortical wave patterns in mice and primates, fractional neural sampling, and Lévy walk dynamics in neural systems. Collaborators include institutions like Fudan University and Kyoto University. Current research student: Andrew LY, working on cortico-cortical loop dynamics and AI applications.
Dr. Jonathan Cant is an Associate Professor at the Department of Psychology, University of Toronto Scarborough (UTSC). His research focuses on cognitive neuroscience, particularly visual perception and cognition using fMRI and behavioral techniques. Born in Hamilton, Ontario, educated at Western University (Psychology) and Harvard University (postdoctoral) Expertise: Object perception, ensemble processing, texture/shape perception, scene recognition The Cant Lab investigates high-level human visual cortex organization, with a focus on the ventral stream's role in perception. Key research includes dissociating shape and surface property processing, material properties in cognition, and object-scene interactions in neural systems. Recent publications highlight ensemble encoding of facial expressions (2025), cross-modal ensemble coding (2024), and texture-shape relationships in ventral cortex (2015). His work bridges modular/distributed cortical organization theories and explores neural substrates for 3D shape vs. material compliance. Teaching includes PSY5222 (Visual Cognitive Representation), PSYC75 (Cognitive Psychology Laboratory), and PSYC51 (Cognitive Neuroscience of Vision). The lab welcomes motivated students and researchers through direct email applications.
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.
Oskari Ville Pakari is a Lecturer at the School of Basic Sciences, École polytechnique fédérale de Lausanne (EPFL), affiliated with both the Institute of Physics (IPHYS) and the Swiss Plasma Center (SPH-ENS). He contributes to teaching and research, particularly in reactor physics and radiation detection. His research focuses on nuclear reactor diagnostics , gamma noise analysis , and neutron spectroscopy . He actively develops mixed reality visualization tools for radiation detection data and participates in the European CORTEX project for reactor monitoring. Selected publications highlight his work in gamma-ray imaging , neutron noise simulations , and detector system validation using advanced statistical methods like bootstrapping and Welch's technique. Teaching activities include courses on Radiation biology, protection, and applications Radiation and reactor experiments He advises PhD student Saliba Michel and collaborates with international institutions such as CEA, KIT, and LRS (Laboratory of Reactor Physics and Systems Behaviour) at EPFL.
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.
Dr. Lauren Emberson (she/her/hers) is an Associate Professor in the Department of Psychology at the University of British Columbia, Faculty of Arts. She directs the Baby Learning Lab, which is part of UBC's Early Development Research Group, a consortium focused on infant and child development. Prior to her position at UBC, Dr. Emberson was an Assistant Professor at Princeton University where she co-founded and co-directed the Princeton Baby and Princeton Kid Labs. Education: Postdoctoral Associate, University of Rochester (PI Aslin) Ph.D, Cornell University (PIs Amso, Goldstein, Spivey) B.Sc, University of British Columbia Dr. Emberson's research focuses on learning, perception (audition, vision, crossmodal or multisensory), language development, face/object perception, and attention in infants. She investigates these capacities using behavioral and neuroimaging techniques, particularly fNIRS (functional near infrared spectroscopy), working primarily with very young infants (birth through 1 year) and preterm/premature infants. Her work examines how infants' learning capacities contribute to rapid development of perception in ecological contexts, with implications for understanding how early life experiences affect later outcomes. Analysis of Dr. Emberson's recent publications reveals a consistent focus on infant perception, learning mechanisms, and neuroimaging methodology. Her work increasingly incorporates advanced fNIRS techniques while maintaining focus on fundamental questions about how infants learn from their environment. There's a growing emphasis on individual differences, cross-cultural comparisons, and applications to infants facing developmental challenges. Dr. Emberson serves on the editorial board of Infancy (journal of the International Congress of Infancy Studies) and is a consulting editor for the Journal of Cognitive Neuroscience . Her research has been published in top journals including PNAS, Current Biology, Psychological Science, Cognition, Developmental Science, and the Journal of Neuroscience. Dr. Emberson has secured significant research funding from prestigious organizations including the Bill and Melinda Gates Foundation, James S. McDonnell Foundation, Natural Sciences and Engineering Research Council (NSERC), Canadian Institutes of Health Research (CIHR), and the National Institutes of Health (NIH). She collaborates with clinicians at BC Women's and Children's Hospitals to understand how different early life experiences impact learning and brain development. Dr. Emberson is currently accepting graduate students into her research program. The Baby Learning Lab, under Dr. Emberson's direction, is part of UBC's Early Developmental Research Group and collaborates with multiple institutions. The lab strives to provide interactive research experiences for infants and families while advancing scientific understanding of early cognitive development. The lab acknowledges that it operates on the traditional, ancestral, and unceded territory of the xʷməθkʷəy̓əm (Musqueam) people.
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.
Marisa Carrasco-Queijeiro is the Julius Silver Professor of Psychology and Neural Science at New York University, affiliated with the Department of Psychology and the Center for Neural Science. She holds a PhD from Princeton University (1989) and has held academic positions at Wesleyan University and NYU, including department chair from 2001–2007. Her research focuses on the interplay between visual perception, attention, and neurophysiological mechanisms. She uses psychophysical methods to study visual search efficiency, spatial resolution, and how attention modulates early visual processing. Key contributions include demonstrating that attention enhances perceptual resolution at attended locations and challenging traditional serial/parallel search models through time-course analyses and cueing experiments. Her work spans visual search efficiency, eccentricity effects, perceptual organization, and contrast sensitivity. Notable findings include attention's role in reducing eccentricity-based performance declines and the modulation of spatial resolution via covert attention. Methodologies include fMRI, EEG, MEG, and computational modeling. Awards: Guggenheim Fellow (1999), NSF Young Investigator Award (1993–1999), Porter Ogden Jacobus Fellowship (1987–1988). Lab: Carrasco Lab at NYU investigates visual perception development in children and adult cognition. Located at 6 Washington Place, Room 971, NYC. Her lab integrates cognitive neuroscience and psychological approaches to understand attention's neural underpinnings. Current projects explore developmental visual perception and attention's impact on early visual processing via neuroimaging and behavioral studies.
Michael N. Economo, PhD, is an Assistant Professor in the Department of Biomedical Engineering at Boston University. His research focuses on neural circuits controlling movement, leveraging cutting-edge optical, electrophysiological, and genetic tools. He holds affiliations with Neuroscience & Neuroengineering and Photonics & Optical Systems programs. Education: PhD in Biomedical Engineering from Boston University, B.S. Biomedical Engineering and B.A. Mathematics from Duke University. Research Interests: Systems neuroscience, motor control, long-range neural circuits, computational neuroscience, neurotechnology. His lab investigates how neural circuits across brain regions coordinate movement using advanced techniques like optogenetics, in vivo imaging, and transcriptomics. Key Projects: Orofacial motor control, voltage imaging with TICO microscopy, neural circuit dissection. Technologies: Neuropixels probes, fluorescent voltage indicators, single-cell RNA sequencing. Notable Awards: NSF CAREER (2023), Scialog Fellow (2023), Whitehall Foundation Young Investigator Award (2021). Advising & Grants: Supervises graduate students (e.g., Munib Hasnain, Jackie Birnbaum) and postdocs (e.g., Vicky Moya, Yujin Han). Lab members focus on motor planning, neuromodulation, and neural dynamics. Labs/Teams: The Economo Lab collaborates on neurotechnology development and integrates interdisciplinary approaches from engineering and biology. Affiliated with BU’s Graduate Program in Neuroscience.
Nikolaus Kriegeskorte is a Professor of Psychology and Neuroscience, and Director of Cognitive Imaging at the Mortimer B. Zuckerman Mind Brain Behavior Institute at Columbia University. He is affiliated with the Departments of Psychology, Neuroscience, and Electrical Engineering. Institution: Columbia University Academic Roles: Professor of Psychology and Neuroscience; Director of Cognitive Imaging Email: nk2765@columbia.edu Location: Jerome L. Greene Science Center, 3227 Broadway, L3-064 Research Focus: The lab explores the cognitive neuroscience of vision, modeling biological visual systems with artificial neural networks. Key areas include developing statistical inference and visualization techniques to bridge theory and experimental data, understanding representational geometry in neural systems, and optimizing deep learning frameworks for neuroscience. Recent Publications: Highlighted work spans neural network modeling of visual perception, representational similarity analysis, and the topology of brain representations. The lab's methods, such as the TorchLens Python package, enable transparent extraction and visualization of hidden layer activations in neural networks. Grants: Projects are supported by funding from the National Science Foundation (NSF) - Cognitive Neuroscience and the National Institutes of Health (NIH) - NIMH. Laboratory: The Visual Inference Lab (kriegeskortelab.zuckermaninstitute.columbia.edu) is located at Quad 3D, Zuckerman Institute, 3227 Broadway.
Megan Carey is a Researcher at the Champalimaud Foundation , leading the Carey Lab . Her research focuses on understanding how cellular and synaptic mechanisms in the cerebellum influence motor behavior and learning. Key projects include studies on cerebellar neural circuits, locomotor adaptation, and sensory-motor integration. Her recent work highlights cross-species comparisons (mice and flies), zebrafish visual system neurobiology, and pharmacological modulation of motor learning. The lab employs genetic perturbations, optogenetics, and behavioral analysis to dissect neural circuit dynamics. Notable collaborators include senior scientists, postdoctoral researchers, and PhD students. The lab's publications span high-impact journals like J. Neurosci. , eLife , and Neuron , with funding from HHMI and NIH.
Marlene Behrmann is the Thomas S. Baker University Professor of Psychology and Cognitive Neuroscience at Carnegie Mellon University (CMU), affiliated with the Dietrich College of Humanities and Social Sciences. She leads the Behrmann Lab, which moved to the University of Pittsburgh in 2023. Her research focuses on visual cognition, object recognition, and neural mechanisms of perception, with a particular emphasis on face and word recognition. Behrmann holds a B.A. and M.A. in Speech and Hearing Therapy and a Ph.D. in Psychology from the University of Toronto. She is a leader in her field, recognized by her induction into the National Academy of Sciences (2015) and the American Academy of Arts and Sciences (2019). Her work combines neuropsychological studies of patients with brain damage, neuroimaging, and computational modeling to explore visual processing. Recent research highlights include studies on dorsal-ventral pathway interactions, functional reorganization post-hemispherectomy, and autism-related sensory processing differences. Behrmann has advised numerous graduate students and postdocs, contributing to their academic and professional development. Key awards include her National Academy of Sciences membership and American Academy of Arts and Sciences fellowship. Her lab collaborates widely, publishing in top journals like Cerebral Cortex , PNAS , and Trends in Cognitive Sciences . She also engages in translational research to improve interventions for perceptual and cognitive disorders.
