Find Academic Supervisors

Miriam HollarekView profile

Research Fellow

• Developmental Psychology
• Neuroscience
• Adolescent Development
• +3 more

Dr. Miriam Hollarek is a Visiting Fellow at Vrije Universiteit Amsterdam, affiliated with the Faculty of Behavioural and Movement Sciences, specifically in the Clinical Developmental Psychology department. She also holds visiting fellow positions at IBBA and LEARN!. Her research focuses on adolescent social-cognitive development and mental health, with a particular emphasis on neuroimaging studies and the impact of social contexts on psychological well-being. Her research interests include: Adolescent social-cognitive development Neuroimaging studies of trust and decision-making Developmental trajectories of mental health issues like social anxiety and depression The impact of social interactions and pandemic effects on adolescent psychology Her recent work explores the neurobiological foundations of trust in adolescents, the role of social contexts in mood variability, and the long-term effects of the pandemic on mental health. These studies combine neuroimaging techniques with longitudinal data analysis to understand developmental processes. No scientific awards mentioned. Advising and grants: No advising or grant information provided. Labs/teams: Affiliated with IBBA and LEARN! research groups.

Kevin HilbertView profile

Researcher

• Anxiety Disorders
• Mood Disorders
• Neuroimaging (fMRI)
• +3 more

Kevin Hilbert is affiliated with the Institute of Clinical Psychology and Psychotherapy at the Technische Universität Dresden, within the Faculty of Science's Department of Psychology. His research focuses on anxiety and mood disorders, particularly their neural substrates, with an emphasis on anticipation, emotional processing, and cognitive control strategies. He employs fMRI and psychophysiological methods to investigate these areas. Scientific Education: He earned a Diploma in Psychology from Technische Universität Dresden (2006–2012) with majors in Clinical Psychology and Work/Organizational Psychology, and a minor in Educational Psychology. His diploma thesis explored neural activation patterns in specific phobia subtypes. He completed internships at the University of Oxford’s Department of Experimental Psychology (2011) and TU Dresden’s Neuroimaging Center (2009). Professional Experience: Since 2012, he has been engaged in postgraduate psychotherapy training in adult cognitive behavioral therapy at the university’s Outpatient Treatment Center. Research Contributions: His work bridges clinical psychology and neuroscience, with publications on neurostructural correlates of phobias, generalized anxiety disorder pathophysiology, and fMRI applications in fear processing. His studies often integrate behavioral and neuroimaging data to advance understanding of anxiety disorders.

• Brain Network Connectivity
• Neuroimaging (fMRI/MEG/EEG)
• Neurodevelopmental Disorders
• +4 more

Peter Fransson is a Professor of Brain System Physiology at Karolinska Institutet's Department of Clinical Neuroscience. He holds a PhD from 1999 and became Associate Professor in 2006 before advancing to his current role since 2014. His research focuses on brain network connectivity, functional MRI (fMRI), magnetoencephalography (MEG), and EEG, with emphasis on neurodevelopmental disorders, chronic pain mechanisms, and neurological conditions like fibromyalgia and rheumatoid arthritis. Research Interests: Investigating large-scale brain network architecture, functional connectivity dynamics, and their implications in health and disease. Key areas include resting-state networks, pain modulation, neuroplasticity after stroke, and developmental neuroscience. Grants: Swedish Research Council grants (2024–2026, 2021–2024, etc.) for studies on neural plasticity, traumatic brain injury, and olfactory system development. Publications: Over 200 peer-reviewed articles, including work on fibromyalgia pain processing, neonatal brain connectivity, and computational modeling of brain networks. Recent studies focus on multimodal imaging and genetic influences on brain function. Labs/Teams: Leads the 'Large-scale Network Connectivity in the Human Brain' group, collaborating on projects like the Stockholm Sleepy Brain study and the RATSS twin study on neurodevelopmental disorders.

Michelle CraskeView profile

Professor

• Fear
• Anxiety Disorders
• Translational Research
• +6 more

Michelle Craske is a Distinguished Professor and the Kevin Love Fund Centennial Chair at the University of California, Los Angeles (UCLA), specializing in Clinical Psychology. Her research focuses on fear, anxiety disorders, etiological models, risk factors, and translational research bridging fear learning and exposure treatments. She also emphasizes disseminating evidence-based cognitive behavioral therapies into clinical practice. Research Interests: Fear and anxiety mechanisms Exposure therapy techniques Translational research linking neuroscience and clinical applications Digital mental health interventions Neuroimaging and reward processing Scientific Awards: Distinguished Professor Kevin Love Fund Centennial Chair Publication Trends: Recent work explores digital interventions for anxiety and depression, neuroimaging in fear extinction, reward processing in therapy outcomes, and personalized treatment using AI. Subfields include virtual reality , neuroreinforcement , peer mentor systems , and multimodal assessment .

Iva BarisicView profile

Lecturer

• Human-Computer Interaction
• Cognitive Science
• Wayfinding Usability
• +3 more

Dr. Iva Barisic is a Lecturer at the Department of Humanities, Social and Political Sciences at ETH Zürich, affiliated with the Chair of Cognitive Science. Her work focuses on interdisciplinary research at the intersection of cognitive science, human-computer interaction, and spatial behavior. Her research interests encompass wayfinding usability in complex environments, social dynamics in navigation, and the application of neuroimaging techniques such as fMRI and eye-tracking to study joint attention mechanisms in autism spectrum disorder. She teaches courses like Human-Computer Interaction: Cognition and Usability, emphasizing the integration of cognitive principles into technology design. Dr. Barisic’s recent publications explore topics such as digital assistant delegation expectations, spatial learning with mobile maps, and the neural underpinnings of social interactions. Her work bridges theoretical cognitive science with practical applications in urban design, user experience research, and assistive technology development. Her research has been published in top-tier journals, with a focus on understanding human spatial cognition and social behavior through both experimental and computational methods. She collaborates with interdisciplinary teams to advance knowledge in human-centered design and neurocognitive mechanisms.

• Bayesian Statistics
• Machine Learning
• Neuroimaging
• +3 more

Bingjing Tang is a Research Fellow in the Department of Statistics at Stanford University, advised by Professor Julia Palacios. Their research focuses on Bayesian methods, generative models, and neuroimaging analysis, with applications in computational statistics and machine learning. Contact: bingjing@stanford.edu . Research interests include nonparametric Bayesian inference, Gaussian processes, spatial statistics, and functional network estimation from neuroimaging data. Recent work emphasizes marginal constraints in generative models and group-representative analysis of multi-subject fMRI datasets using Markov Random Fields. No scientific awards or grants are explicitly listed. Advising records are not provided in available texts.

• Neuroimaging Standards
• Functional MRI
• Schizophrenia Research
• +3 more

Christopher Markiewicz is a Senior Research Scholar in the Department of Psychology at Stanford University. His work focuses on neuroimaging standards, particularly the Brain Imaging Data Structure (BIDS), and advancing reproducible research practices in neuroscience. He contributes to large-scale initiatives like the Accelerating Medicines Partnership for Schizophrenia (AMP SCZ), developing neuroimaging protocols and multi-site data standards. His research integrates computational methods, open science frameworks, and collaborative projects to improve the reliability and interoperability of neuroimaging data. Position: Sr Research Scholar, Department of Psychology, Stanford University Key Projects: BIDS extensions (NIRS-BIDS, Motion-BIDS), fMRIPrep, AMP SCZ neuroimaging protocols Research interests include: Standardization of neuroimaging data (BIDS) fMRI preprocessing pipelines (fMRIPrep) Schizophrenia neuroimaging and clinical high-risk cohorts Open science practices and reproducible workflows Publications highlight contributions to neuroimaging protocols, data standardization, and computational tools for reproducibility. His work bridges technical innovations with clinical applications in mental health research.

• Neuroimaging
• Sensory Processing
• Autism Spectrum Disorders
• +6 more

Dr. Shulamite Green is an Associate Professor in the Department of Psychiatry and Biobehavioral Sciences at the UCLA David Geffen School of Medicine. She holds the Friends of the Semel Institute Chair and is a licensed clinical psychologist specializing in autism. Her work spans multiple institutions including UCLA's TIES for Families program and collaborations through the Intellectual and Developmental Disabilities Research Center (IDDRC). Dr. Green's research focuses on sensory processing in autism spectrum disorders (ASD), utilizing neuroimaging (particularly fMRI), psychophysiological, and behavioral methods to investigate how sensory processing difficulties affect higher-level cognition such as attention, social functioning, and executive functioning. Her work spans from infancy through young adulthood, and she also studies other populations at risk for sensory processing difficulties, including children with anxiety disorders and those with early life trauma. Her research has identified neural mechanisms underlying sensory over-responsivity and how these relate to broader cognitive and social functioning. Her publication trend shows consistent high-impact research in autism neuroscience, with a focus on sensory processing mechanisms across development. Recent work emphasizes early biomarkers in infants, cross-species neural mechanisms, and the intersection of sensory processing with social cognition. Her research has increasingly incorporated multi-site collaborations and translational approaches to bridge basic science with clinical applications. Dr. Green has received significant NIH funding for her research, including multiple principal investigator roles on major grants investigating neural mechanisms of sensory reactivity in autism across development, mechanisms underlying sensory over-responsivity, and gene-brain-environment interactions in ASD. As a clinical psychologist, she works with UCLA's TIES for Families program for families adopting children from foster care, bringing her research expertise to clinical practice. She also collaborates with animal researchers to identify cross-species neural mechanisms of sensory over-responsivity, demonstrating the translational nature of her work.

Meredith RayView profile

Associate Professor

• Bayesian methods
• Semi-parametric modeling
• fMRI brain imaging analysis
• +3 more

Meredith Ray, PhD, MPH, is an Associate Professor in the Division of Epidemiology, Biostatistics, and Environmental Health at the University of Memphis School of Public Health (SPH). She also serves as Program Coordinator for Biostatistics. Her research focuses on Bayesian methods, semi-parametric modeling, fMRI brain imaging analysis, and bioinformatics (epigenetics). Her work includes identifying brain activation regions using fMRI meta-data and DNA methylation associations with health outcomes. Education: PhD in Biostatistics from the University of South Carolina (2014) MPH in Biostatistics from the University of Georgia (2009) BS in Mathematics from Piedmont College (Demorest, Georgia) Research interests emphasize statistical methodologies applied to public health challenges, including HIV prevention strategies, lung cancer care quality, and substance use epidemiology. She collaborates on studies involving multidisciplinary healthcare systems and population-based cohorts. Recent work examines PrEP discontinuation patterns in sexual/gender minority populations and surgeon quality metrics in lung cancer resections. Her articles analyze topics ranging from epidermal growth factor receptor testing in lung cancer to interventions improving pathological staging accuracy. She has contributed to developing matrix-variate Dirichlet processes for earthquake hypocenter modeling, showcasing interdisciplinary methodological expertise. Laboratory and team affiliations include the Division of Epidemiology, Biostatistics, and Environmental Health at UofM SPH. She advises on biostatistical methodologies for clinical and population health studies.

Jacob YeungView profile

Researcher

• Neural Computation
• Machine Learning
• Computer Vision
• +3 more

Jacob Yeung is a Ph.D. student in the Neural Computation & Machine Learning joint program at Carnegie Mellon University , supported by an NSF Graduate Research Fellowship . He is advised by Prof. Michael J. Tarr and Prof. Deva Ramanan. Current Institution: Carnegie Mellon University Prior Education: B.S. in Electrical Engineering and Computer Science (EECS) from University of California, Berkeley His primary research focuses on understanding human visual processing of dynamic stimuli and enhancing machine visual reasoning through fMRI decoding and video diffusion models . Key contributions include developing BrainNRDS for motion decoding from neural activity and eDCA for dimensionality reduction in neural-behavioral data. Recent publications highlight advancements in dynamic visual stimuli reanimation (CVPR 2025 Oral) and cortical semantic mapping with Vision Transformers (ICLR 2025). He has also contributed to datasets like Hangul Fonts and analytical methods such as eDCA . Scientific Awards: NSF Graduate Research Fellowship He has served as a teaching assistant for Advanced Machine Learning (10716) at CMU (Spring 2025) and Introduction to Network Communications (EE 122) at Berkeley (Spring 2022). Additionally, he tutored foundational computer science courses at Berkeley in 2021.

Jessica CantlonView profile

Professor

• Cognitive Neuroscience
• Developmental Psychology
• Quantitative Reasoning
• +3 more

Jessica Cantlon is the Ronald J. and Mary Ann Zdrojkowski Professor of Developmental Neuroscience/Psychology at Carnegie Mellon University's Dietrich College of Humanities and Social Sciences. She leads the Concepts, Actions, and Objects Lab and the Kid Neuro Lab, focusing on the neural and cognitive foundations of quantitative reasoning in humans and non-human primates. Her research employs behavioral and neuroimaging techniques to explore how numerical and spatial concepts develop in children and how these relate to evolutionary processes. Key research themes include cross-species comparisons of numerical processing (e.g., studies on rhesus monkeys and olive baboons), the role of the intraparietal sulcus (IPS) in numerical cognition, and the impact of environmental and gender factors on mathematical development. She has contributed to debates on core knowledge theories, semantic frameworks, and the evolution of human intelligence. Her work bridges developmental psychology, cognitive neuroscience, and comparative psychology, with implications for education and public health policy. Her labs emphasize interdisciplinary approaches, combining fMRI studies with behavioral experiments to understand how abstract concepts emerge from neural systems. Current projects investigate recursive pattern processing, hierarchical reasoning, and the neural basis of mathematical learning from naturalistic environments like educational videos.

• Sleep Disorders
• Cognitive Neuroscience
• Aging and Neurodegeneration
• +3 more

Nathan Cross is a researcher at the University of Sydney's Brain and Mind Centre, specializing in sleep neurobiology, aging, and cognitive neuroscience. His work explores how sleep impacts memory consolidation, dementia risk factors, and neurological conditions like obstructive sleep apnea. He collaborates on large-scale studies such as the Canadian Longitudinal Study on Aging, investigating links between sleep disorders and cognitive decline. Affiliations: Brain and Mind Centre (University of Sydney) Key Research Areas: Sleep physiology, neurodegenerative biomarkers, and translational sleep medicine His research focuses on identifying sleep-related mechanisms underlying cognitive aging, including EEG and fMRI studies of sleep oscillations, and developing interventions for sleep disorders in older adults. Current projects include analyzing sleep state misperception in insomnia and evaluating CPAP effects on brain integrity in mild cognitive impairment. Recent work highlights the stability of NREM sleep phase-amplitude coupling and its role in memory retention, as well as the association between insomnia and subjective memory decline in middle-aged populations. Grants: 'Using functional MRI to decode sequential memory replay' (2024), 'Evaluating the effect of CPAP on brain integrity' (2013) Advising: Supervises research students Clara Tan Cheri Yi (dementia risk factors) and Tian Yang (multimodal health systems) Labs/Teams: Active contributor to the Centre for Integrated Research and Understanding of Sleep (CIRUS), focusing on clinical-neuroscience interfaces in sleep medicine.

Indranath ChatterjeeView profile

Assistant Professor

• Computational Neuroscience
• Medical Imaging
• Schizophrenia
• +7 more

Dr. Indranath Chatterjee is an Assistant Professor at Manchester Metropolitan University's Department of Computer and Mathematics, with adjunct roles at Woxsen University and the International Center for Neuroscience Research. He specializes in Computational Neuroscience, Schizophrenia, and Medical Imaging, focusing on fMRI analysis and machine learning applications. His research spans over 12 authored/edited books and numerous peer-reviewed publications, including works on neuroimaging, AI in healthcare, and blockchain solutions. He leads the Chatterjee's NeuroImaging and AI Lab at Tongmyong University, collaborating globally on projects like 'Uncovering Neuroscience History in South Korea' (FENS grant) and 'Green Neuromarketing'. Awards include the 2021 Best Young Neuroscientist Award and multiple paper accolades. Education: PhD in Computational Neuroscience from University of Delhi. Previous roles include Assistant Professorships at Tongmyong University (2019–2024) and JK Lakshmipat University. He serves as Chief Section Editor of international journals and holds leadership roles in organizations like ACM, FENS, and INCF. Active in conferences worldwide, delivering over 26 keynotes. Research interests include Schizophrenia neurobiology, AI-driven medical diagnostics, and neuromarketing strategies. Current projects address chronic pain in osteoarthritis, green neuromarketing via EEG, and historical neuroscience studies. His lab employs 8 researchers focusing on neuroimaging, machine learning, and interdisciplinary AI applications. Awards highlight his contributions to neuroscience and computational methods, including FENS-funded research and editorial recognition. Grants include government/non-profit collaborations for societal impact through medical imaging and machine learning.

• Neuroimaging in Psychiatry
• Psychiatric Disorders Pathophysiology
• Neurocognitive Profiles
• +4 more

Marcella Bellani is an Associate Professor at the University of Verona's Department of Neuroscience, Biomedicine and Movement Sciences, Section of Psychiatry and Clinical Psychology. She chairs the Neuroimaging Section of the European Psychiatric Association and directs the Brain Imaging and Neuropsychology Research Unit. Her research focuses on applying neuroimaging techniques (MRI, fMRI) to study psychiatric disorders, with emphasis on biomarkers for early diagnosis and intervention. She investigates psychiatric disorders like bipolar disorder, schizophrenia, and depression using translational approaches combining neuroimaging, neuropsychology, and rehabilitation strategies. Her teaching roles include contributing to medical and psychiatric rehabilitation programs, covering topics like psychiatry fundamentals and cognitive therapy principles. She actively participates in postgraduate psychiatry specialization courses, overseeing clinical case discussions and literature updates. Bellani's work integrates computational neuroscience methods to analyze brain structure/function relationships, with recent projects exploring machine learning applications in mental health diagnostics. Her research unit collaborates internationally through initiatives like the ECNP neuroimaging network, emphasizing data harmonization for large-scale studies. Key areas include the impact of inflammation on brain microstructure in psychosis, cognitive remediation therapies, and digital interventions for social isolation. She advocates for ethical considerations in psychiatric care, such as opposing assisted suicide for severe depression cases.

Joanne Jao KeehnView profile

Research Professor

• Autism
• Sensory Processing
• Multisensory Integration
• +3 more

Dr. Joanne Jao Keehn is a Research Professor of Psychology at San Diego State University (SDSU), affiliated with the College of Sciences and the Department of Psychology. She is part of the SDSU/UC San Diego Joint Doctoral Program in Clinical Psychology. Her research focuses on neural and behavioral mechanisms of sensory processing, multisensory integration, and sensorimotor development in children with and without autism, utilizing advanced neuroimaging techniques like fMRI and MEG. Her work explores links between sensory abnormalities, stress responsivity, and autism symptomatology. Dr. Keehn’s expertise spans autism, sensory processing, functional neuroimaging, and developmental neuroscience. She leads the BDIL Lab, conducting studies on sensory and multisensory integration in clinical populations. Her research emphasizes understanding atypical neural connectivity and its implications for behavioral symptoms in autism. She has contributed to collaborative efforts like the Autism Brain Imaging Data Exchange (ABIDE) to enhance connectome studies in autism. Her academic contributions include over 25 peer-reviewed publications since 2009, with recent work focusing on functional connectivity patterns, sensory network interactions, and neuroimaging methodological advancements. Though specific awards are listed under placeholders, her work is recognized for advancing understanding of autism’s neurobiological underpinnings. She collaborates across institutions and mentors students in clinical and developmental psychology.