Edward S. Awh is a Professor in the Department of Psychology at the University of Chicago, affiliated with The Institute for Mind and Biology and the Grossman Institute for Neuroscience, Quantitative Biology and Human Behavior. His research focuses on behavioral and neural studies of memory and attention, employing psychophysics, EEG, and functional MRI. His lab investigates neural mechanisms underlying cognitive processes and their interrelationships. Research interests include tracking the contents of online memories and the locus of covert attention using neural decoding techniques. The lab collaborates on projects involving attention and memory studies, as detailed on their website: Awh/Vogel Lab . The lab currently seeks postdoctoral researchers to join ongoing projects using behavioral, EEG, and fMRI methodologies. Contact via awhvogellab@gmail.com .
Alexei A. Efros is a Professor in the Department of Electrical Engineering and Computer Sciences (EECS) at UC Berkeley, where he holds the Howard Friesen Professorship and is affiliated with the Berkeley Artificial Intelligence Research (BAIR) Lab. He previously served on the faculty at the Robotics Institute of Carnegie Mellon University (CMU) and completed a postdoctoral fellowship at the University of Oxford. His research spans data-driven computer vision, self-supervised learning, computational photography, and applications to computer graphics and robotics. His research interests include: Data-Driven Computer Vision Self-Supervised and Unsupervised Learning Generative Models and Image Synthesis Visual Representation Learning Applications in Robotics and Human-Computer Interaction Intersections with Human Vision and the Humanities The recent publications highlight a strong trend toward self-supervised learning, visual reasoning, and generative modeling, particularly diffusion models and 3D scene understanding. His work increasingly bridges computer vision with language, robotics, and cognitive science, emphasizing interpretability and real-world applicability. There is a clear focus on leveraging unlabeled data and developing methods for robust, generalizable AI systems. His scientific awards and recognitions include: Berkeley Fellowship Google Fellowship Soros Fellowship NSF Fellowship SIGGRAPH Outstanding Doctoral Dissertation Award Facebook Fellowship Adobe Fellowship CMU School of Computer Science Distinguished Dissertation Award ACM Doctoral Dissertation Honorable Mention Alexei Efros has advised numerous PhD students and postdocs, many of whom have gone on to faculty positions at top institutions including CMU, Stanford, MIT, Columbia, NYU, and Georgia Tech. His lab has received research funding from major tech companies and federal agencies, though specific grants are not detailed in the text. He teaches core computer vision and machine learning courses at both undergraduate and graduate levels at UC Berkeley. His research group is highly active, with ongoing projects in 3D perception, generative modeling, and vision-language systems. He leads a vibrant research lab at UC Berkeley, part of the BAIR consortium, collaborating with leading researchers such as Jitendra Malik, Trevor Darrell, Pieter Abbeel, and Angjoo Kanazawa. His lab fosters strong interdisciplinary connections with institutions worldwide, including Oxford, INRIA, and École Normale Supérieure.
Jonathan Winawer is an Associate Professor of Psychology and Neural Science at New York University (NYU). He leads the Winawer Laboratory for Human Visual Perception and Neuroscience, which is affiliated with the NYU Psychology Department, NYU Center for Neural Science, NYU Neuroscience Institute, and collaborates with the NYU Comprehensive Epilepsy Center and Stanford University's Human Intracranial Cognitive Program. Ph.D., Massachusetts Institute of Technology (2007) M.S., City College of the City University of New York (2005) A.B., Columbia University (1995) His research focuses on the biological basis of visual perception, including computational models of the visual pathways using fMRI, EEG, ECoG, and psychophysics. Key areas include: Encoding of visual stimuli in neural pathways Perceptual memory's influence on cognition Neural circuit properties underlying imaging signals Individual differences in visual perception Publications highlight interdisciplinary approaches spanning computational neuroscience, neuroimaging, and psychophysics, with recent work on population receptive fields, spatial frequency tuning, and memory-related cortical dynamics. He has mentored numerous students and postdocs, many of whom have advanced to academic and research roles at institutions like Stanford, Columbia, and the University of Amsterdam. Department of Psychology, NYU Center for Neural Science, NYU Neuroscience Institute, NYU Comprehensive Epilepsy Center, NYU Stanford University collaborations
Belkis Ezgi Arikan is a researcher at Justus Liebig University Giessen , affiliated with the Department of Psychology and Sports Science . Her work focuses on sensorimotor integration, tactile suppression, and neural mechanisms underlying action-outcome monitoring. She collaborates with Prof. Dr. Fiehler and Dr. Voudouris on project A4 (Predictive somatosensory processing during voluntary movements). Department: Psychology and Sports Science Collaborators: Dr. Dimitris Voudouris, Prof. Dr. Katja Fiehler Her research investigates: How the brain processes self-generated vs. externally generated sensory feedback Neural correlates of tactile suppression networks Role of cerebellum and angular gyrus in temporal recalibration Modulation of BOLD responses during action monitoring Recent publications reveal trends in predictive coding , sensorimotor recalibration , and neural suppression mechanisms across tactile, visual, and multisensory domains. Her work employs neuroimaging techniques like fMRI and behavioral paradigms to study self-motion perception and feedback processing. She contributes to understanding how the brain distinguishes self-initiated from external sensory events, with implications for motor learning and perceptual timing mechanisms.
Viola S. Stoermer is Assistant Professor in Psychological and Brain Sciences at Dartmouth College, directing the BrainStörmer Lab. Her research examines cognitive and neural mechanisms of perception, attention, and memory using EEG and behavioral methods. Research investigates fundamental limits of selective attention and working memory capacity. Key findings demonstrate how meaningful objects expand memory capacity and how attention warps feature perception. Studies reveal cross-modal interactions where sounds influence visual processing and resolve ambiguities. Publications establish representational frameworks for attention, showing how feature-based selection operates globally. Research combines psychophysics with neural measures to characterize perceptual bottlenecks and capacity limits. Current Research Areas: Principles of selective attention in feature/space Meaningfulness effects on working memory capacity Auditory influences on visual perception
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.
Jeff Moher is an Associate Professor of Psychology and Co-Chair of the Department of Psychology at Connecticut College, where he has been teaching since 2017. He also serves as the Data, Information, and Society Pathway Co-Coordinator, demonstrating his leadership within the institution. His educational background includes a Ph.D. and M.A. from Johns Hopkins University and a B.S. from the University of Michigan. This strong academic foundation has prepared him for his research and teaching career in cognitive psychology. Moher's research focuses on cognitive psychology and cognitive neuroscience, particularly visual attention and cognition in action. His work investigates why distractions occur, when they are likely to arise, and what mechanisms humans can harness to avoid them. He has found that humans employ various cognitive mechanisms to minimize distractions based on explicit knowledge, task goals, object properties, and recent experience, though he has also discovered surprising limitations in attentional selection. His research is particularly relevant given that over 3,000 people are killed annually in the United States from distracted driving. His recent publications show a consistent trajectory examining attentional mechanisms, distraction, and visual processing across different contexts. His work frequently employs sophisticated methodologies to measure both cognitive and motor responses to distractions, revealing how seemingly minor distractions can accumulate to induce serious performance costs. Moher's research is currently funded by grants from the National Science Foundation and the National Institutes of Health, indicating the significance and quality of his work. He likely mentors numerous students through the department's research groups, contributing to their development as researchers. He directs the CAMELab (Center for Attention, Movement, and Embodied Learning), which utilizes multiple methodologies including eye-tracking, electroencephalography, three-dimensional reach-tracking, and psychophysics to approach questions about attention and distraction. Current projects in his lab explore why salient distractors cause people to give up quickly during visual search, the brain mechanisms involved in learning to ignore distractions, how internal distractions impact physical interactions with the world, and how hand movement paths reveal information about attentional processes.
Alan Stocker is a Professor in the Department of Psychology at the University of Pennsylvania, affiliated with the Neuroscience Graduate Group, Bioengineering Graduate Group, and Computational Neuroscience Initiative. His research focuses on understanding how prior beliefs and expectations shape visual perception, combining theoretical models with psychophysical and physiological experiments. Key areas include optimal inference frameworks, neural coding efficiency, and decision-making under uncertainty. Education: PhD in Physics (ETH Zurich, 2002); MSc in Biomedical Engineering and Materials Science (ETH Zurich, 1995). Prior appointments include postdoctoral work at New York University and ETH Zurich. Research Interests: Behavioral Neuroscience, Cognitive Neuroscience, Sensation and Perception. Specific projects explore statistical properties of visual environments, subjective expectations from past decisions, and neural computations underlying perception. Advising: Current advisees include Cheng Qiu (Postdoc), Ansh Soni, and Mengting Fang (Graduate Students). Courses taught: Perception, Visual Neuroscience, and Probabilistic Models in Perception and Cognition. Labs/Teams: Leads the Computational Perception and Cognition (CPC) Laboratory, emphasizing theory-driven experimentation. Collaborates widely across disciplines including bioengineering and electrical systems engineering.
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.
Professor Dirk Bernhardt-Walther is an academic at the University of Toronto, serving as Program Director of the Cognitive Science Program and Department of Psychology . He investigates neural and computational mechanisms underlying high-level sensory perception, focusing on real-world scenes, mid-level vision, and visual aesthetics. Education: PhD in Computation and Neural Systems (Caltech, 2006), M.Phil (University of Cambridge) Research Focus: His lab employs fMRI, MEG, EEG , and GAN-generated stimuli to study scene categorization, perceptual organization, and aesthetic processing. Recent work explores curvature perception, emotion representation in scenes, and neural dissociations between computational and subjective visual metrics. Laboratory Members: The Bernhardt-Walther Lab includes PhD students like Gaeun Son (scene perception), Charlotte Leferink (scene representation), and Dela Farzanfar (aesthetic processing), alongside postdocs and collaborators. Advising: Supervises graduate students in projects combining computational modeling, psychophysics, and neuroimaging, particularly those with backgrounds in computer science or cognitive neuroscience.
James T. Enns is a Professor and Distinguished University Scholar in the Department of Psychology within the Faculty of Arts at the University of British Columbia. His research primarily focuses on the role of attention in human vision, with secondary interests in developmental psychology and human-machine interaction. Dr. Enns' research interests span perception, attention, vision, cognition, development, and human-machine interaction. His work explores how the human mind selects information, with particular emphasis on visual attention mechanisms. His laboratory research investigates the fundamental processes of visual perception and how attention modulates these processes across different contexts and developmental stages. Analysis of Dr. Enns' publication record reveals consistent engagement with visual perception, attentional mechanisms, and cognitive processing. His research demonstrates expertise in both theoretical frameworks and experimental methodologies related to visual attention, with applications spanning basic cognitive science to potential implementations in human-computer interaction systems. His work often bridges theoretical cognitive psychology with practical applications. Canadian Society for Brain, Behaviour and Cognitive Science Donald O. Hebb Distinguished Contribution Award (2013) Distinguished University Scholar, UBC (2004) Robert E. Knox Master Teaching Award (2004) Royal Society of Canada Fellow (2002) Killam Faculty Research Prize (1994) Killam Faculty Research Fellowship (1993) Society of Experimental Psychology Fellow Dr. Enns has served as Editor for the Journal of Experimental Psychology: Human Perception and Performance, and as Associate Editor for Psychological Science, Consciousness and Cognition, and Visual Cognition. His research has been supported by grants from NSERC, the Canadian Foundation for Innovation, the Australian Research Council, BC Health, and Nissan. He has authored textbooks on perception, edited research volumes on the Development of Attention, and published numerous scientific articles on vision, attention, and cognitive science. Dr. Enns is currently accepting graduate students and continues to mentor the next generation of cognitive scientists. Dr. Enns leads the UBC Vision Lab, which focuses on how the human mind selects information. The lab conducts research on visual attention, perception, and cognitive processes using a variety of experimental methodologies.
Hakwan Lau is a tenured Professor of Psychology at the University of California, Los Angeles (UCLA), where he is also a member of the Brain Research Institute. Additionally, he serves as Co-Director of the IBS Center for Neuroscience Imaging Research in South Korea, leading the Systems and Intervention Neuroscience (SIN) group. His work spans consciousness, metacognition, and perceptual reality monitoring, employing advanced neuroimaging and computational techniques. Education: Born and raised in Hong Kong, Hakwan Lau pursued graduate studies in England. He was previously an Associate Professor at Columbia University in New York before moving to UCLA, where he is now tenured. From 2017-2020, he was primarily based at the University of Hong Kong. Research Interests: Lau's lab investigates why we have subjective experiences , focusing on visual awareness, spatial attention, and metacognition. They use fMRI, decoded neurofeedback (DecNef), psychophysics, and computational modeling to explore how conscious perception arises and its clinical applications, such as treating phobias and PTSD. Research Trends: His recent work emphasizes decoded neurofeedback interventions for clinical conditions like phobias and PTSD, metacognitive mechanisms underlying confidence judgments, and neural correlates of subjective experience . The research bridges theoretical neuroscience with practical therapeutic applications, often using innovative techniques like closed-loop fMRI. Scientific Awards: While specific awards are not listed in the provided text, Lau has mentored 15 former trainees who are now independent PIs , reflecting his significant impact on the field. Advising and Grants: Lau actively advises numerous PhD students and postdocs across UCLA, the University of Hong Kong, and collaborative institutions. His lab supports projects ranging from AI-driven fMRI analysis to clinical neurofeedback trials . Labs and Teams: Lau leads the Metacognition and Consciousness Lab at UCLA, now relocated to the RIKEN Center for Brain Science near Tokyo. His team includes researchers from diverse backgrounds, focusing on interdisciplinary approaches to consciousness and metacognition.
Ralf Haefner is an Assistant Professor in the Departments of Brain & Cognitive Sciences and Physics & Astronomy at the University of Rochester, holding this joint appointment since 2014. His interdisciplinary research bridges neuroscience and physics to investigate computational principles of perception and decision-making. Education and professional background: PhD, Oxford University, 1999 Visiting Research Fellow, Department of Neurobiology, Harvard Medical School Swartz Fellow, Sloan-Swartz Center for Theoretical Neurobiology, Brandeis University Haefner's research program centers on computational neuroscience , with primary focus on how the brain forms perceptual beliefs and uses them for decisions through Bayesian modeling . He employs machine learning tools to construct mathematical models explaining neural responses and behavior, particularly in the visual domain. His work addresses neural representation of uncertainty, causal inference mechanisms, and probabilistic computation in cortical circuits. Analysis of recent publications (2023-2025) reveals three dominant trends: (1) causal inference frameworks applied to motion perception and segmentation, (2) Bayesian modeling of perceptual biases and confidence computations, and (3) integration of generative and discriminative neural computations. His work extends beyond traditional neuroscience into scientific methodology through 'Generative Adversarial Collaborations' for improving research discourse. Honors and Awards: Swartz Fellowship, Sloan-Swartz Center for Theoretical Neurobiology NSF CAREER Award (2022) for 'Approximate inference at the intersection of neuroscience and machine learning' Haefner secured significant research funding through his NSF CAREER award, which supports foundational work on probabilistic inference at the neuroscience-ML interface. While specific students aren't listed, his active publication record and lab infrastructure suggest ongoing mentorship of graduate students and postdocs. His research has clinical relevance as shown by studies on perceptual abnormalities in autism spectrum disorder, indicating translational potential for understanding neurological conditions.
Dr. Ayşe Nihan AVCI is an Assistant Professor at the Department of Interior Architecture, Faculty of Architecture at Çankaya University. She holds a PhD in Design (2022), Master's in Interior Architecture (2017), and Bachelor's in Interior Architecture (2010) from the same institution. Her research focuses on lighting design's impact on health and well-being, biophilic design principles, and OLED/LED lighting technologies. She has been a full-time faculty member since 2015, progressing from Research Assistant (2015-2022) to Doctoral Researcher (2022-2024) before her current role. Education: PhD in Design, Çankaya University (2017-2022) MSc in Interior Architecture, Çankaya University (2014-2017) BSc in Interior Architecture, Çankaya University (2005-2010) Research Interests: Her work integrates lighting science with human-centric design principles, emphasizing: Salutogenic lighting strategies for health promotion OLED technology's circadian rhythm effects Biophilic daylighting in historical buildings Visual comfort in workplaces Publications: Over 15 peer-reviewed articles (2016–2025) focus on OLED/LED lighting applications, circadian rhythms, and daylighting in heritage buildings. Recent work explores salutogenic design in coffee shop environments and workplace environmental quality. Awards: No specific awards listed, but active in academic service: Member of Aydınlatma Türk Milli Komitesi since 2017 Member of TMMOB İç Mimarlar Odası since 2010 Reviewer for journals including PLANARCH Grants & Projects: Led a university-supported research project (2020–2021) on lighting design's health impacts. Currently teaches courses on lighting design, materials science, and interior design fundamentals.
Anna Levina is an Assistant Professor for Computational Neuroscience at the University of Tübingen , affiliated with the Department of Computer Science under the Faculty of Science. Her research focuses on the self-organization of neuronal activity, critical dynamics in neural networks, and the excitation/inhibition balance in cortical circuits. Current positions: Assistant Professor (since 2018), Group Leader (2017-2018), Equality Officer (Computer Science) Previous roles: IST Fellow (2015-2017), Associated Researcher (2011-2015), Postdoc/PI (2011-2015), Postdoc (2008-2011) Her research integrates mathematical modeling , statistical physics , and computational neuroscience to study criticality phenomena, neural avalanches, and adaptive network dynamics. Key interests include: Self-organized criticality in neural systems Excitation/Inhibition balance mechanisms Network topology and dynamics Timescale analysis in neural processing Stochastic modeling of neural activity Recent publications reveal trends in understanding critical dynamics across biological and artificial networks, with applications to memory systems, sensorimotor integration, and disease modeling. She has received recognition as an IST Fellow .
