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Mikail RubinovView profile

Assistant Professor

• Network Neuroscience
• Computational Neuroscience
• Brain Connectivity
• +4 more

Mikail Rubinov serves as Assistant Professor of Biomedical Engineering (primary appointment), Computer Science, Psychiatry, and Psychology at Vanderbilt University's School of Engineering. His interdisciplinary work bridges computational neuroscience, network science, and clinical applications. His research focuses on integrative statistical models of large-scale neural data , exploring brain network organization across species and scales. Key interests include evolutionary principles of brain networks, transcriptomic basis of neural individuality, information transfer in neural systems, and neuropsychiatric connectivity phenotypes. The Rubinov Lab develops computational frameworks for analyzing complex neural systems and integrates neuroscientific knowledge with multi-omics data. Recent publications reveal strong trends in network neuroscience methodology development (circular analysis frameworks, unbiased sampling techniques) and translational applications (epilepsy networks, autism spectrum connectomics, gut-brain axis interrogation). His work increasingly incorporates transcriptomic data with neuroimaging at biobank scale. NIH Grant Writing Workshop (June 2022) NIH Workshop Short Talks (April 2023) Rubinov actively mentors graduate and undergraduate students across Biomedical Engineering and Computer Science. His lab maintains collaborations with UCSF, HHMI Janelia Research Campus, Weizmann Institute, and international neuroscience consortia. Current projects include integrative models of large-scale neural data and transcriptomic basis of neural individuality. The Rubinov Lab operates within Vanderbilt's Department of Biomedical Engineering with extensive cross-school collaborations. Technical resources include GitHub repositories for constraint network models (cnm-code), volumetric segmentation (voluseg), and brain connectivity toolboxes.

Christopher John RozellView profile

Professor

• Computational Neuroengineering
• Artificial Intelligence
• Neuroscience
• +7 more

Christopher John Rozell is the Julian T. Hightower Chaired Professor in the School of Electrical and Computer Engineering at the Georgia Institute of Technology's College of Engineering. He serves as Executive Director of the Institute for Neuroscience, Neurotechnology & Society (INNS) and directs the Sensory Information Processing Lab (SIPLab). His research bridges computational neuroscience, machine learning, and neurotechnology, with clinical applications in treatment-resistant depression and neuromodulation therapies. Education: B.S.E. in Computer Engineering & B.F.A. in Music, University of Michigan (2000) M.S. and Ph.D. in Electrical Engineering, Rice University (2002, 2007) Postdoctoral Scholar, Redwood Center for Theoretical Neuroscience, UC Berkeley Research Focus: Dr. Rozell's interdisciplinary work spans computational neuroengineering, theoretical neuroscience, and artificial intelligence. He develops data analysis tools inspired by neural processing and creates therapeutic neurotechnologies. Key areas include: computational psychiatry (developing DBS therapies for depression), neural dynamics modeling, brain-computer interfaces, and societal impacts of neurotechnology. His lab focuses on high-dimensional data analysis, neural coding principles, and scalable neuromodulation approaches. Publication Trends (2023-2025): Recent works concentrate on deep brain stimulation mechanisms for depression, computational modeling of neural/autonomic dynamics, and machine learning applications in neuroscience. Dominant themes include biomarker discovery for treatment response, neural interoception modulation, probabilistic modeling of latent states, and brain-computer interface taxonomy. Clinical translation of neurotechnology is a consistent focus across publications. Awards & Honors: Elected AIMBE Fellow (2025) NIH BRAIN Initiative Photo/Video Award (2024) Congressional Panelist for BRAIN Initiative 10th Anniversary (2024) Sigma Xi Best Faculty Paper (2024) Neuro Open Science International Prize (2022) W. Howard Ector Outstanding Teacher Award (2019) McDonnell Foundation 21st Century Science Award (2014) NSF CAREER Award (2014) Leadership & Training: Dr. Rozell co-founded Neuromatch, Inc. to build global computational neuroscience communities. He advises Motif Neurotech and the Institute of Neuroethics. His mentees have received prestigious fellowships (Schmidt, Fulbright, NIH K99/R00) and hold leadership positions across academia and industry. Research is supported by NIH BRAIN Initiative, NSF, and private foundations. Labs & Initiatives: Directs the Sensory Information Processing Lab (theoretical neuroscience/neuroengineering) and the Institute for Neuroscience, Neurotechnology & Society (addressing ethical/societal implications). Neuromatch promotes open, accessible computational neuroscience training globally.

• Neuroscience
• Computational Modeling
• Meditation
• +5 more

Giuseppe PAGNONI is an Associate Professor at the Department of Biomedical, Metabolic and Neurosciences of Università di Modena e Reggio Emilia . His research spans neuroscience , computational modeling , meditation , and brain network analysis . He teaches courses such as Neural Systems Modeling for Bioengineering students and Human Physiology and Pathophysiology in Medicine programs, with a focus on predictive coding , default mode network , and emotional valence processing . Pagnoni has contributed to ENIGMA-Meditation , a global initiative exploring meditation's neuroscientific basis, and developed sparse Bayesian models for analyzing brain network individual differences. His work on Alzheimer's disease investigates anosognosia mechanisms through resting-state fMRI, while other studies examine ghrelin's role in obesity-related reward processing and oxytocin's effects on social anxiety . He employs dynamic causal modeling and predictive processing frameworks to study cognitive effort, mind wandering, and neuromorphic learning. His methodological expertise includes functional MRI , independent component analysis , and computational simulations .

Anne Böckler-RaettigView profile

Professor

• Social Cognition
• Empathy
• Theory of Mind
• +7 more

Prof. Dr. Anne Böckler-Raettig is a Professor for Research Methods & Social Cognition at the University of Würzburg's Faculty of Human Sciences. She leads an Emmy Noether Research Group and is involved in DFG projects like ContextualEYEze . Her roles include Deputy Chair of the local Ethics Committee, Co-Chair of the Diversity-AG, and Vertrauensdozentin of the Studienstiftung des deutschen Volkes. Primary Affiliation: Institute of Psychology, University of Würzburg Research Leadership: Emmy Noether Research Group (2018–2025) DFG Project: ContextualEYEze (2024–2025) Academic Roles: Professor (2021–present), Juniorprofessorin (2015–2020) Her research spans social cognition, empathy, theory of mind, prosocial behavior, gaze processing, and the psychological effects of meditation. Recent articles highlight gaze direction's role in attention capture, emotion perception, and prosociality, alongside neural correlates of mental training. She explores clinical and developmental contexts, including trauma responses and cross-cultural stigma studies. Scientific awards include the prestigious Emmy Noether Fellowship (DFG). Her work appears in journals like Neuroscience & Biobehavioral Reviews , Human Brain Mapping , and Emotion , reflecting interdisciplinary impact. Collaborations span institutions including Max-Planck Institutes and Princeton University.

Pernille HemmerView profile

Professor

• Cognitive Psychology
• Episodic Memory
• Semantic Memory
• +4 more

Pernille Hemmer is a Professor in the Department of Cognitive Psychology at Rutgers University. She joined the faculty in 2012 after completing a postdoctoral fellowship at Syracuse University and earning her Ph.D. from the University of California, Irvine's Department of Cognitive Science. Her research focuses on memory systems, decision-making in naturalistic environments, and Bayesian models of cognition. She leads the CCM Lab (https://sites.rutgers.edu/ccm-lab/), investigating how prior knowledge integrates with episodic memory and influences cognitive processes. Key research interests include: Episodic and semantic memory integration Optimal use of prior knowledge in cognitive tasks Bayesian analysis of individual differences in rational models Belief systems and agency perception Her work spans experimental psychology, computational modeling, and interdisciplinary approaches. Notable contributions include developing generalized Bayesian models of reconstructive memory and frameworks for understanding belief dynamics. Recent research explores socially cognizant robotics and counterintuitive concepts across domains. Awards: Higher-Level Cognition Modeling Prize (2008) Her National Science Foundation CAREER grant (2015) supports applications of Bayesian inference to memory and decision-making. Current projects examine temporal binding mechanisms and the memorability of supernatural concepts through novel methodological tools.

Ruben LaukkonenView profile

Senior Lecturer

• cognitive neuroscience
• meditation
• consciousness
• +2 more

Dr. Ruben Laukkonen is a Senior Lecturer (Associate Professor equivalent) in cognitive science and computational neuroscience at Southern Cross University, with honorary fellowships at Vrije Universiteit Amsterdam and The University of Queensland. His award-winning research integrates neural, psychological, and computational approaches to study meditation, insight, and consciousness. Research highlights: Bayesian models of advanced meditation states Mechanisms of true/false insight experiences Neural correlates of consciousness using EEG/Machine Learning Chief Investigator on Australia's largest psychedelic clinical trial ($4M funding) He publishes in leading journals, speaks internationally, and consults for the OECD on AI and education. His work explores rare states of consciousness across multiple explanatory levels, from neural dynamics to subjective phenomenology. Laukkonen received the 2024 Mid-Career Researcher Award for Research Excellence.

• Pain Research
• Embodied Cognition
• Clinical Neuroscience
• +3 more

Dr. Abby Tabor is a researcher within the Faculty of Health and Applied Sciences (HAS) at the University of the West of England (UWE Bristol). Her work focuses on the theoretical understanding of aversive bodily symptoms, particularly pain, with an emphasis on embodied perspectives and active inference frameworks. She investigates how body-world interactions shape perception and action, especially in contexts such as limb fracture, amputation, and pediatric prosthetics collaboration with the NHS. Her research bridges clinical practice, neuroscience, and rehabilitation, aiming to improve treatment outcomes and patient well-being. Abby’s research interests include the interplay between perception and action in pain contexts, the role of environment in bodily experiences, and the application of advanced technologies to enhance prosthetics and pain management. Her work often involves interdisciplinary collaborations, combining insights from neuroscience, psychology, and clinical medicine. Her recent publications explore biomechanical and psychological pathways in pain, the efficacy of aerobic exercise in pain reduction, and methodological innovations in pain research. While no specific awards are listed, her contributions to prosthetics and chronic pain studies highlight her impactful work. No student advising or grant details are provided in the text. Abby is affiliated with UWE’s HAS faculty and is actively involved in NHS partnerships for translational research.

Henrik EhrssonView profile

Professor

• Cognitive Neuroscience
• Neuroscience
• Psychology
• +5 more

Henrik Ehrsson is a Professor of Cognitive Neuroscience at Karolinska Institutet's Department of Neuroscience, Sweden. He holds a PhD and MD from Karolinska Institutet and has been a faculty member since 2008. His research focuses on understanding the neural mechanisms underlying body ownership, multisensory integration, and self-awareness, with implications for neuroprosthetics and virtual reality applications. He leads the Cognitive Neuroscience of Bodily Awareness and Self-Cognition Group and the Brain, Body, and Self Lab . Education: MD and PhD, Karolinska Institutet (2003, 2001) Postdoctoral Fellowship, Wellcome Trust Centre for Neuroimaging, UCL (2008) Research Interests: Dr. Ehrsson investigates how the brain integrates sensory signals to form a coherent body representation, with applications to neuropsychiatric disorders, neuroprosthetics, and virtual reality. His work explores the neural basis of self-location, memory encoding, and interoception (e.g., heartbeat awareness in blind individuals). Key themes include: Body ownership illusions and their neural substrates Cross-modal plasticity in sensory-deprived populations Techniques like fMRI, EEG, and virtual/augmented reality Awards: ERC Advanced Grant (SELF-UNITY project) Swedish Research Council Distinguished Professorship Göran Gustafson Prize in Medicine Grants & Labs: Funded by Swedish Research Council, ERC, and Hjärnfonden. His labs feature advanced VR setups, EEG, TMS, and neuroimaging collaborations. Collaborations include NYU, Utrecht University, and clinical teams for translational research. Students: Supervises PhD/MA students like Xiaole Luan (Body Ownership) and August Hägerdal (Rubber Hand Illusion EEG studies).

Daniele MarinazzoView profile

Professor

• Computational Neuroscience
• Complex Systems
• Neurophysics
• +4 more

Daniele Marinazzo is a Full Professor in the Department of Data Analysis at Ghent University (Belgium), with a background in statistical physics and a focus on computational neuroscience and complex systems. He serves as Deputy Editor at PLOS Computational Biology , Co-Editor-in-Chief at Neurons, Behavior, Data Analysis, and Theory , and academic editor at Network Neuroscience and Imaging Neuroscience. His work spans theoretical physics, neuroscience methodology, and experimental neurophysiology. Academic Affiliation: Ghent University (Belgium) Editorial Roles: 3+ journals Research Initiatives: EBRAINS representative Research Interests combine computational neuroscience, complexity science, and network analysis. He investigates higher-order interactions in brain networks, synergistic information processing, and methodological advancements in neuroimaging. Recent work includes MEG/EEG analysis, gene expression modeling, and developing open-source tools like SPM-Python. Scientific Contributions include 15+ recent publications on topics ranging from individual brain fingerprinting to multisensory integration models. His work appears in venues like Nature Communications , Physics of Life Reviews , and Entropy , with methodological innovations in hidden factor localization and network synchronization analysis. Current projects include PhD/postdoc recruitment for fast-sampled fMRI analysis and organizing the Erice workshop Higher-Order Interactions: Mechanisms, Behaviors, and Networks (August 2025).

• Probabilistic Programming
• Deep Learning
• Artificial Intelligence
• +7 more

Jan-Willem van de Meent is an Associate Professor at the University of Amsterdam where he co-directs the AMLab with Max Welling. He also maintains an Assistant Professor position at Northeastern University, though currently on leave while continuing to advise students and collaborate. His research develops AI models by combining probabilistic programming and deep learning, focusing on understanding inductive biases that enable models to generalize from limited data. His research spans multiple domains: Probabilistic programming frameworks and inference methods Inductive biases for generalization from limited data Physical system simulators incorporating domain knowledge Causal structure and symmetries in AI models Applications in robotics, NLP, healthcare, and physical sciences Van de Meent is one of the creators of Anglican, a probabilistic programming language based on Clojure, and currently develops Probabilistic Torch, a library for deep generative models extending PyTorch. He is writing a book on probabilistic programming (draft available on arXiv) and serves as co-chair of the international conference on probabilistic programming (PROBPROG). His recent publications show a strong trend toward developing more efficient inference methods for probabilistic models, exploring disentangled representations across vision and language domains, and applying these techniques to healthcare, robotics, and neuroscience. His work on nested variational inference, energy-based models, and state abstraction in reinforcement learning has been particularly influential. Awards and Recognition NSF CAREER award (2021) Van de Meent actively advises multiple PhD students and postdocs across interdisciplinary projects. His lab maintains strong collaborations with researchers in robotics, healthcare, neuroscience, and other scientific domains, applying advanced probabilistic modeling to challenging real-world problems. He also develops practical tools for the research community, making advanced inference techniques more accessible to practitioners.

• Consciousness Studies
• Cognitive Neuroscience
• Sleep Deprivation Effects
• +3 more

Anikó Kusztor is a Postdoctoral Research Fellow at Monash University, Australia, specializing in consciousness studies. She holds a PhD from Monash University and prior degrees from Eötvös Loránd University and the University of Oslo. Her research focuses on understanding how subjective experience transforms under conditions like sleep deprivation, dissociation, and dreaming, employing EEG and neuroimaging techniques. She is affiliated with Tlab (Qualia Structure Research) and M3CS (Monash Mind Modelling and Computational Systems), contributing to interdisciplinary projects on consciousness and open science. Education: BSc Psychology (Eötvös Loránd University), MSc Cognitive Neuroscience (University of Oslo), PhD (Monash University) Her work bridges cognitive neuroscience, clinical research, and computational modelling. Recent studies include investigations into color perception, arousal mechanisms, and the neural basis of dissociative disorders. She actively participates in journal clubs and conferences, promoting collaborative research in consciousness science. Articles highlight her contributions to understanding color qualia structures, the role of cardiac activity in age-related neural signals, and the neurobiology of grief. Her work emphasizes interdisciplinary approaches, integrating experimental and computational methods.

Lina SkoraView profile

Researcher

• Consciousness
• Bayesian Brain Models
• Reward Learning
• +3 more

Lina Skora is a Visiting Researcher in the School of Psychology and the Sackler Centre for Consciousness Science at the University of Sussex. She holds a BSc in Psychology from St Mary's University and an MSc in Social Cognition with Neuroscience from University College London. Her doctoral research focuses on the role of interoceptive signals in conscious/unconscious associative learning under the supervision of Dr Ryan Scott, Dr Daniel Campbell-Meiklejohn, and Prof Anil Seth. Her research interests span consciousness studies, Bayesian brain models, adaptive behavior, emotion theory, and interoceptive inference. She explores how sensorimotor predictions and bodily signals influence perception and learning processes. Lina has contributed to studies on instrumental learning, autonomic performance monitoring, and facial expression analysis using interdisciplinary methods combining neuroscience and cognitive psychology. Her recent publications address topics like cardiac activity's role in learning, machine validation of facial expression databases, and the feasibility of unconscious conditioning. While no specific awards are listed, her work demonstrates contributions to understanding embodied cognition and consciousness mechanisms. Lina's doctoral thesis (2020) investigated the integration of body, action, and consciousness in adaptive interactions with the environment through instrumental learning paradigms. She collaborates with leading figures in consciousness science and employs experimental psychology, neurophysiological measures, and computational modeling in her research.

• Social Psychology
• Cognitive Neuroscience
• Action Processing
• +3 more

Dr. Bartosz Majchrowicz serves as a Lecturer in the Department of Social Psychology within the Faculty of Philosophy at Jagiellonian University, Krakow. Based at the Institute of Psychology (Ingardena 6), he maintains active research and teaching roles with contact details publicly listed including email bartosz.majchrowicz@uj.edu.pl and phone 12 663 24 69. His research spans Social Psychology and Cognitive Neuroscience with specialized focus on action processing mechanisms, sense of agency phenomena, decision-making under uncertainty, and neurophysiological correlates of volition. Key investigations examine how uncontrollability influences effort allocation, interoception-action interactions, sensory attenuation effects, and temporal aspects of agency perception through experimental paradigms including probabilistic reversal learning and Libet-style tasks. Analysis of his 15 publications (2016-2025) reveals consistent exploration of agency phenomenology using neuroscientific methods. His work demonstrates how factors like action spontaneity, outcome valence, cardiac feedback, and learning from losses modulate agency experiences, with recurring themes in temporal binding, error processing, and embodied cognition. This research bridges psychological theory with neural mechanisms underlying human volition. As part of Jagiellonian University's Institute of Psychology, Dr. Majchrowicz contributes to academic initiatives including Scientific Thursdays and Clinical Tuesdays, operating within a research ecosystem featuring specialized laboratories and interdisciplinary teams advancing psychological science through the Excellence Initiative and international collaborations.

Kelsey PerrykkadView profile

Research Fellow

• Perinatal Mental Health
• Autism Spectrum Disorders
• Predictive Processing
• +5 more

Kelsey Perrykkad is a Postdoctoral Research Fellow at Monash University’s Faculty of Medicine, Nursing and Health Sciences, based at the Monash Medical Centre. She investigates perinatal mental health and child developmental outcomes using longitudinal datasets. Her interdisciplinary research bridges cognitive science, philosophy, and education, focusing on mental health-cognitive process interactions, the nature of self, environmental uncertainty processing, and action-consequence dynamics. Perrykkad holds a PhD in Cognitive Science (2021) and a BA in Cognitive Science and Philosophy (2014), both from Monash University. Education: PhD in Cognitive Science: Monash University (2017-2021) Bachelor of Arts in Cognitive Science & Philosophy: Monash University (2010-2014) Her research interests span predictive processing frameworks applied to autism spectrum conditions, agency perception, and the interplay between neuroscience and education. Notable contributions include work on classroom acoustics for autistic children and fidgeting behaviors through predictive coding. Perrykkad has lectured in critical thinking and philosophy of mind at Monash, earning a Dean’s Teaching Commendation (2020). Awards: Australasian Cognitive Neuroscience Society Emerging Researcher Award (2022) Vice-Chancellor’s Thesis Excellence Commendation (2021) Dean’s Sessional Teaching Commendation (2020) Her recent publications explore agency in schizophrenia/autism, acoustic classroom interventions, and self-prioritisation in cognitive domains. Perrykkad collaborates internationally on projects addressing mental health, neurodiversity, and educational neuroscience.

• Philosophy of Cognitive Science
• Embodied Cognition
• Extended Mind Theory
• +6 more

Andy Clark is a Professor of Cognitive Philosophy at the University of Sussex's School of Media, Arts and Humanities. His work bridges philosophy, cognitive science, and technology, focusing on embodied and extended cognition, predictive processing, and the impact of cultural artifacts on human cognition. He leads the ERC Synergy Grant XScape, exploring interactions between predictive brains, cultural tools, and visual search. Clark's research integrates robotics, computational neuroscience, and AI ethics, emphasizing how technology extends human cognitive capacities. His recent publications examine generative AI's role in extending minds, the role of predictive processing in consciousness, and the ethical implications of ambient technologies. Clark holds grants including the EU-funded XScape (2021-2027) and previous ERC Advanced Grant Expecting Ourselves (2017-2021). He has authored influential books like Surfing Uncertainty (2016) and Supersizing the Mind (2008). His research themes include robotic embodiment, computational psychiatry, and socio-technological systems. Current projects explore predictive processing's role in mental health, creativity, and human-AI collaboration. Key research directions: predictive processing as a unifying framework for consciousness, the extended mind hypothesis in AI contexts, and the philosophical implications of large language models. His work challenges traditional boundaries between mind, body, and environment, advocating for a 'metamorphic' view of cognition shaped by technological and cultural evolution.