جست‌وجوی استاد و پژوهشگر

Martin Schrimpfمشاهده پروفایل

استادیار

• neuroAI
• computational neuroscience
• computer vision
• +۵ مورد دیگر

Professor Martin Schrimpf is a Tenure Track Assistant Professor at EPFL, holding dual appointments in the School of Life Sciences (SV) and the School of Computer and Communication Sciences (IC). His research bridges computational neuroscience, deep learning, and cognitive science to model human natural intelligence in vision and language. He leads the NeuroAI Lab, focusing on aligning artificial neural networks with brain mechanisms and human behavior. Education: PhD in Brain and Cognitive Sciences from MIT (2017–2022), MSc in Software Engineering from TUM/LMU/UNA (2014–2017), and BSc in Information Systems from TUM (2011–2014). His work has been recognized with awards including the Neuro-Irv Open Science Prize, McGovern Fellowship, and Takeda AI+Health Fellowship. He co-founded Integreat, a social impact startup recognized with Google.org’s Impact Challenge and TUM’s Social Impact Award. Research interests include neuroAI, brain-like models, and clinical translation (e.g., visual prosthetics). He has published in top venues like Neuron, Nature Human Behavior, NeurIPS, and ICLR. Current projects involve developing topographic language models (TopoLM) and investigating causal language network interactions using LLMs. Teaching: Courses include Neuroscience Foundations for Engineers and Brain-like Computation and Intelligence . Supervised over 26 students, including PhD candidates Badr Alkhamissi, Ben Lönnqvist, and Yingtian Tang. Active in grants from SNSF, NeuroX, and EPFL’s AI Center. Labs/Teams: NeuroAI Lab at EPFL Neuro-X Institute. Future directions include advancing brain-inspired models for clinical applications and expanding interdisciplinary collaborations between neuroscience and AI.

• Neural circuit mechanisms
• Adaptive learning
• State-dependent decision-making
• +۴ مورد دیگر

Dr. Sabine Krabbe is a Group Leader at the German Center for Neurodegenerative Diseases (DZNE) in Bonn, Germany, where she leads research on neural circuit mechanisms underlying adaptive learning and state-dependent decision-making. Her work integrates neuroscience, molecular biology, and behavioral approaches to understand how internal states influence behavior and how these processes are disrupted in neurological disorders. Dr. Krabbe's research focuses on the interactions between midbrain circuits of the substantia nigra and ventral tegmental area with their output structures such as the striatum and amygdala. She investigates how these networks integrate internal states with environmental cues to produce appropriate behavioral responses. Her laboratory employs state-of-the-art techniques including deep-brain calcium imaging at single-cell resolution in mice, opto- and pharmacogenetic manipulations, anatomical tracings, and molecular approaches to characterize neural circuit elements in detail. Her recent publications reveal significant insights into amygdala interneuron plasticity during fear learning, brain-wide representational drift in memory consolidation, and the molecular mechanisms underlying Parkinson's disease progression. Her work demonstrates how activity patterns within specific neural circuits change in early stages of neurodegenerative diseases and how this dysfunction contributes to cognitive deficits and emotional disturbances. Dr. Krabbe is actively involved in the neuroscience community, organizing the BonnBrain Conference 2026 and sharing research through social media platforms. She has established herself as an emerging leader in the field of systems neuroscience with a particular focus on the neural basis of emotional states and decision-making processes.

Stefano Fusiمشاهده پروفایل

دانشیار

• Computational Neuroscience
• Theoretical Neuroscience
• Neural Circuit Modeling
• +۲ مورد دیگر

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.

Frank E. Garceaمشاهده پروفایل

عضو هیئت علمی

• Cognitive Neuroscience
• Neuroimaging
• Neurology
• +۴ مورد دیگر

Frank E. Garcea, Ph.D., is a Research Assistant Professor in the Department of Neurosurgery and Neuroscience at the University of Rochester School of Medicine and Dentistry. His research focuses on the cognitive and neural mechanisms underlying tool use, apraxia, and stroke recovery. He employs neuropsychological testing, fMRI, and lesion-symptom mapping to study brain injury effects on functional connectivity and action knowledge. Education: Bachelor of Science in Psychology, St. John Fisher College (2006–2010) PhD in Brain and Cognitive Sciences, University of Rochester (2012–2017) Research Interests: Dr. Garcea investigates how brain regions like the parietal cortex and dorsal/ventral streams mediate object manipulation and tool use. His work explores stroke-related disconnection syndromes, motor speech coordination networks, and translational brain mapping to preserve neural function during surgery. He collaborates on projects involving epilepsy patients undergoing electrocorticography to study action-related neural pathways. Labs & Affiliations: Principal Investigator of the Garcea Lab at URMC, focusing on tool use deficits in brain tumor/stroke survivors. Affiliated with the Del Monte Institute for Neuroscience and the Neurobiology & Anatomy Program. His lab integrates neuroimaging, lesion analysis, and clinical care to advance personalized brain mapping strategies.

Nicolas Davidenkoمشاهده پروفایل

دانشیار

• Cognitive Psychology
• Perception
• Face Recognition
• +۵ مورد دیگر

Nicolas Davidenko is an Associate Professor in the Department of Psychology at the University of California, Santa Cruz (UCSC). He leads the High Level Perception Lab, focusing on behavioral and computational studies of human perception, particularly face recognition, spatial orientation, and visual ambiguity. His work emphasizes 'top-down' processes like attention and expectations. Davidenko holds a Ph.D. in Psychology from Stanford University (2006), an M.S. in Statistics from Stanford (2004), and an A.B. in Mathematics from Harvard (1998). His research explores how humans perceive and interpret complex visual information, including studies on illusions, virtual reality, and misophonia. He has developed parametric models of faces to study memory encoding and drawing accuracy. Notable achievements include a Top-10 Finalist placement in the 2015 Best Illusion of the Year Contest for his 'Mind-controlled motion' research. He teaches courses such as PSYC 121 (Perception), PSYC 139K (Face Recognition), and advanced cognitive research seminars. Davidenko also runs the CSASS Matlab Workshops, training researchers in statistical tools. His lab includes graduate students and postdocs, with alumni like Jennifer Day (Ph.D. ’19) and Pat Samermit (Ph.D. ’18). Recent projects include investigations into vection in VR environments, cross-sensory modulation of aversive sounds, and time perception in virtual reality. His work bridges cognitive psychology, neuroscience, and computational modeling, contributing to understanding how perception shapes human interaction with the environment.

• Neuroimaging
• Neuroscience
• Functional Magnetic Resonance Imaging (fMRI)
• +۳ مورد دیگر

Prof. Stephen Mayhew is a Professor at Aston University's School of Life & Health Sciences, affiliated with the College of Health and Life Sciences. He leads the Cognition & Neuroscience Research Group (CNRG) and contributes to the Aston Research Centre for Health in Ageing. His research focuses on multimodal neuroimaging (EEG/fMRI/MRI/MEG) to study brain activity in health and cognition, particularly negative BOLD responses and their role in neural inhibition and behavior. Recent work includes investigating task-demand effects on BOLD responses, brain state dynamics during rest, and neurovascular coupling methods. Education & Affiliations: Affiliated with Aston University's School of Life & Health Sciences Member of CNRG and Health in Ageing Centre Research Interests: His work explores collaborative/antagonistic brain networks, lifespan changes in brain function, and the functional significance of negative BOLD responses. Techniques include fMRI, EEG, and advanced neuroimaging analysis methods like fractal dimension and laminar 7T MRI. Key Contributions: Published over 30 peer-reviewed articles on neuroimaging and brain networks Systematic reviews on neurovascular coupling and transcranial Doppler methods Labs & Teams: Active in CNRG and collaborates across disciplines in health sciences and bioengineering.

Tomaso A. Poggioمشاهده پروفایل

استاد

• Computational Neuroscience
• Machine Learning
• Computer Vision
• +۵ مورد دیگر

Tomaso A. Poggio is the Eugene McDermott Professor in the Department of Brain and Cognitive Sciences at the Massachusetts Institute of Technology , an investigator at the McGovern Institute for Brain Research , a member of the Computer Science and Artificial Intelligence Laboratory (CSAIL) , and the director of both the MIT Center for Biological and Computational Learning (CBCL) and the multi-institutional Center for Brains, Minds and Machines (CBMM) . Research Interests Poggio’s research is fundamentally interdisciplinary, sitting at the intersection of computational neuroscience , machine learning , and computer vision . His work is driven by the conviction that learning is the core gateway to both biological intelligence and artificial systems. Current themes include: Mathematical foundations of statistical learning theory Engineering applications in computer vision, graphics, bioinformatics, and intelligent search Computational neuroscience of visual object recognition and the ventral stream of the visual cortex Scientific Awards & Honors Eugene McDermott Professorship, MIT Advising & Grants Over three decades, Poggio has advised a large cohort of doctoral and master’s students whose theses span machine learning, computer vision, neuroscience, and bioinformatics. Representative graduates include H. Jhuang, Stanley Bileschi, Jacob Bouvrie, Jennifer Louie, M. Kouh, Sayan Mukherjee, Ryan Rifkin, Alexander Rakhlin, Thomas Serre, Gene Yeo, and many others. His research has been continuously supported by major federal and private funding initiatives, most recently through the multi-institutional Center for Brains, Minds and Machines (CBMM) headquartered at the McGovern Institute since 2013. Laboratories & Teams Poggio directs the Poggio Lab (CBCL) at MIT, an interdisciplinary group comprising neuroscientists, computer scientists, mathematicians, and engineers. The lab collaborates closely with experimental neuroscientists to develop predictive computational theories of visual cortex function and to translate those insights into practical algorithms for computer vision and machine learning.

Christian F. Doellerمشاهده پروفایل

استاد

• Cognitive Neuroscience
• Memory Psychology
• Spatial Navigation
• +۶ مورد دیگر

Professor Christian F. Doeller is a leading cognitive neuroscientist serving as Director of the Department of Psychology at the Max Planck Institute for Human Cognitive and Brain Sciences (MPI CBS) in Leipzig and Vice President of the Max Planck Society (since 2023). His roles include honorary professorships at the University of Leipzig (2019) and TU Dresden (Cognitive Neuroscience of Learning and Memory). He holds a PhD in Psychology from Saarland University (2005) and has held positions at institutions such as UCL (London), Radboud University (Nijmegen), and NTNU (Trondheim). His research focuses on spatial navigation, memory systems, and cognitive mapping in the human brain, leveraging neuroimaging (fMRI, EEG) and computational modeling. Key areas include hippocampal/entorhinal cortical function, grid cells, and the neural basis of spatial and conceptual representations. Recent work explores non-Euclidean spatial cognition, value-based decision making using grid-like maps, and hormonal influences on navigation. His lab combines experimental psychology, neuroimaging, and theoretical neuroscience to understand how brains build predictive models of environments and concepts. Publications emphasize cognitive maps, neural representations of space/value, and memory formation mechanisms. Over 100 journal articles span high-impact journals like Nature Neuroscience , Neuron , and Current Biology . His work bridges basic research and translational applications in neurodegenerative disorders and spatial cognition deficits.

Jonathan Cantمشاهده پروفایل

دانشیار

• Cognitive Neuroscience
• Visual Perception
• Object-Ensemble Perception
• +۶ مورد دیگر

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.

Burkhard Maessمشاهده پروفایل

استاد پژوهشی

• Neuroscience
• Auditory Processing
• Signal Analysis
• +۳ مورد دیگر

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.

Marlene Behrmannمشاهده پروفایل

استاد

• Cognitive Neuroscience
• Cognitive Science
• Visual Perception
• +۴ مورد دیگر

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.

• Visual Perception
• Cognitive Psychology
• Developmental Science
• +۶ مورد دیگر

Prof. Anna Franklin is a Professor of Visual Perception and Cognition at the University of Sussex's School of Psychology. She leads the Sussex Colour Group and Sussex Baby Lab , focusing on human color perception, development, and neural representation. Her research combines cognitive psychology, developmental science, and neuroscience to explore how color perception develops, influences aesthetics, and relates to conditions like autism. Key projects include ERC-funded initiatives studying environmental impact on color perception and developing the ColourSpot diagnostic app for childhood color vision deficiency. She also serves as Deputy Director of Research and Knowledge Exchange for the School of Psychology. Education includes a BA from the University of Nottingham and a PhD from the University of Surrey, followed by a postdoctoral fellowship. Her work spans 107+ publications, emphasizing interdisciplinary methods like hyperspectral imaging and fMRI. Collaborations include industry partnerships with ETTA LOVES and COSATTO to apply infant visual preference research in product design. Research grants include European Research Council awards (Starting Grant 2012-2017, Consolidator Grant 2018-2025) and a Proof of Concept grant for ColourSpot . Her labs investigate cross-cultural color categorization, infant aesthetics, and neural correlates of color processing. Future work focuses on calibrating visual systems to environmental statistics and improving early childhood color vision screening.

Richard Bornمشاهده پروفایل

استاد

• Systems & Integrative Neuroscience
• Visual Perception
• Cortical Circuitry
• +۴ مورد دیگر

Richard Born is a Professor of Neurobiology at Harvard Medical School , focusing on the circuitry of the mammalian cerebral cortex and its role in visual perception. His lab employs multi-species approaches, combining primate psychophysics and electrophysiology rodent 2-photon imaging and optogenetics hierarchical Bayesian modeling of perceptual inference to investigate cortico-cortical feedback, neural variability, and context-dependent visual processing. Research Interests span visual systems neuroscience, with emphasis on top-down modulation of sensory processing binocular rivalry and perceptual states gamma oscillations and neural synchrony input-gain control in V1/V2/V3 Bayesian brain frameworks neuroanatomical connectomics Recent work explores layer 1 dendritic interactions with somatostatin interneurons and collaborations with institutions like Boston University and the University of Rochester. Advising includes mentoring postdoctoral fellows (Ariana Sherdil, Camille Gómez-Laberge, Abhinav Grama) and students at Harvard Medical School. The lab utilizes advanced techniques including multi-electrode arrays laminar probes optogenetic perturbation DTI tractography validation for circuit analysis.

George Alvarezمشاهده پروفایل

استاد

• Visual Cognition
• Attentional Selection
• Visual Memory
• +۱۲ مورد دیگر

George Alvarez is a Professor of Psychology in the Faculty of Arts and Sciences at Harvard University, where he leads the Vision Sciences Laboratory. His research lies at the intersection of cognitive science, neuroscience, and computational modeling, focusing on how the human visual system efficiently encodes and processes information through mechanisms such as attention, memory, and statistical learning. His research interests center on the cognitive and computational foundations of visual intelligence. Specifically, he investigates attentional selection , visual and working memory storage , fluid resource allocation , and ensemble coding . A key focus is understanding how the brain extracts regularities from visual input to form efficient representations. He explores whether detailed visual memory recall involves reactivation in the primary visual cortex, how learning statistical covariances alters object representations in the ventral visual stream, and where in the visual hierarchy ensemble statistics first emerge. His lab combines behavioral studies , fMRI , neurostimulation , and deep neural network models to probe these questions and bridge human and machine vision. Alvarez is affiliated with Harvard’s Mind, Brain, and Behavior (MBB) consortium and actively contributes to interdisciplinary research. He mentors students and researchers in the Vision Sciences Laboratory, fostering innovation in cognitive and computational neuroscience. While no specific awards or grants are listed in the provided text, his work is supported through institutional and research funding mechanisms at Harvard. His lab collaborates across disciplines, leveraging AI advances to refine models of human visual cognition. The lab maintains active participation in public science through platforms like TestMyBrain.org and MechanicalTurk.com, enabling large-scale behavioral data collection. Future work aims to deepen the integration between artificial and biological vision systems, uncovering fundamental principles of perception and cognition.

Leila Wehbeمشاهده پروفایل

دانشیار

• Machine Learning
• Cognitive Neuroscience
• Neuroscience
• +۴ مورد دیگر

Leila Wehbe is an Associate Professor in the Machine Learning Department and Neuroscience Institute at Carnegie Mellon University (CMU), with affiliations in Psychology and Computational Biology. She leads a research group focused on understanding high-level brain representations of language and vision using machine learning techniques. Her work combines neuroimaging (fMRI/MEG) with computational models to investigate how the brain processes meaning and visual stimuli. Education : PhD in Machine Learning from CMU, advised by Tom Mitchell BE in Electrical and Computer Engineering from the American University of Beirut Postdoc at UC Berkeley's Helen Wills Neuroscience Institute with Jack Gallant Research Interests : Her research bridges cognitive neuroscience and AI, focusing on: Decoding language and visual processing from brain activity Developing machine learning models aligned with brain representations Investigating semantic composition in language Exploring visual cortex selectivity for objects/food Improving neural decoding with advanced methods (e.g., transformers, generative models) Awards & Recognition : NSF CAREER Award (2022) NIH R21/R01 Awards Human Frontier Science Program Award Google Faculty Research Award Grants & Labs : Leads the Wehbe Lab, part of brAIn at CMU. Active in grant programs including NSF and NIH, focusing on language-brain alignment and visual cortex studies. Co-organized workshops at ICLR and CVPR on brain-inspired AI.