Find Academic Supervisors

Yanli LinView profile

Assistant Professor

• Cognitive Neuroscience
• Mindfulness
• Emotion Regulation
• +7 more

Yanli Lin is an Assistant Professor in the Department of Psychology within the College of Arts & Sciences at the University of Arkansas. She holds a Ph.D. in Clinical Psychology from Michigan State University and completed a postdoctoral fellowship in Cognitive Neuroscience at Washington University in St. Louis (2020–2024). Position: Assistant Professor Institution: University of Arkansas School: College of Arts & Sciences Department: Psychology Email: yanlil@uark.edu Her research focuses on understanding how mindfulness and contemplative practices influence attention, emotion regulation, cognition, and interpersonal behavior, with an emphasis on the mind-brain-behavior relationship. She employs cognitive neuroscience methods, including EEG and statistical modeling, to investigate neural and behavioral effects of meditation in both health promotion and clinical contexts. Her interdisciplinary approach integrates insights from psychology, neuroscience, philosophy, and religious studies. The recent publications highlight a consistent trend in studying distinct mindfulness states—particularly focused attention and open monitoring—on neural markers of emotion and cognitive control. Her work employs within-subject designs and advanced electrophysiological techniques to parse subtle differences in mindfulness-induced brain dynamics. These studies contribute to a growing understanding of how specific meditation practices can be precisely targeted for therapeutic applications. She has been recognized with several prestigious awards: NIH/NIA F32 National Research Service Award WUSTL McDonnell Center for Systems Neuroscience SGP Award Mind & Life Institute Francisco J. Varela Research Award Dr. Lin advises graduate students and leads a research laboratory focused on mindfulness and cognitive neuroscience. While specific grant details are not listed, her award history suggests active external funding. Her lab uses EEG and behavioral experimentation to explore how meditation shapes cognition and emotion, contributing to the scientific foundation for mindfulness-based interventions.

• Cognitive Neuroscience
• Functional Magnetic Resonance Imaging
• Magnetic Resonance Imaging
• +7 more

Dr. Daan van Rooij serves as an Assistant Professor in the Department of Experimental Psychology at Utrecht University's Faculty of Social and Behavioural Sciences. His academic work is centered within the Helmholtz Institute Experimental Psychology research program under Chair Kenemans. His research expertise spans Cognitive Neuroscience, Functional Magnetic Resonance Imaging, Psychology, Disruptive Behaviour Disorders (specifically ADHD, ODD, CD), Cognitive Development, and Artificial Intelligence. Van Rooij employs fMRI and EEG imaging metrics to study brain development during childhood and adolescence, with particular focus on understanding how biological and environmental factors shape the development of impulsive behavior in youth. His scholarly publications demonstrate strong contributions to autism research, ADHD symptomology, and the genetic architecture of brain structures, with work appearing in high-impact journals including Molecular Autism, NeuroImage: Clinical, and Nature Genetics. Dr. van Rooij teaches various courses within the bachelor and master programs of Applied Cognitive Psychology, as well as AI bachelor and master tracks at Utrecht University, including courses such as 'Artificial Intelligence for an Open Society' and 'Experimentele methoden en statistiek' (Experimental Methods and Statistics).

Christopher HoneyView profile

Associate Professor

• Computational Neuroscience
• Cognitive Neuroscience
• Neural Dynamics
• +3 more

Christopher Honey is an Associate Professor in the Department of Psychological & Brain Sciences at Johns Hopkins University, affiliated with the Krieger School of Arts & Sciences. His research focuses on computational cognitive neuroscience, exploring how the brain processes sequential information such as language and memory. He holds a PhD from Indiana University and has held positions at Princeton University and the University of Toronto before joining JHU in 2016. Education: PhD in Psychological and Brain Sciences, Indiana University Postdoctoral Fellowship at Princeton University with Uri Hasson Bachelor’s in Applied Mathematics and English Literature, University of Cape Town Research Interests: Neural dynamics of memory and perception Temporal processing in the brain Cognitive modeling using computational methods Neuroimaging data standards (e.g., BIDS) Publications highlight his work on brain state fluctuations, neuroimaging data structures, and memory enhancement. His lab develops tools for analyzing fMRI and EEG data, emphasizing real-world applications like smartphone-based cognitive interventions. Lab and Collaborations: Active projects on narrative processing and hippocampal replay Development of open-source neuroscience tools like iELVis Focus on translational research for aging populations

Vasily KlucharevView profile

Professor

• Neuroeconomics
• Social Neuroscience
• Emotional Neuroscience
• +4 more

Vasily Klucharev is a Tenured Professor at the Higher School of Economics University (HSE University) since 2013, where he serves as Laboratory Head of the Institute for Cognitive Neuroscience and the International Laboratory of Social Neurobiology. He is also a Professor at the Graduate School of Business in the Department of Strategic and International Management, and Programme Scientific Supervisor of the Cognitive Sciences and Technologies: From Neuron to Cognition program. His educational background includes: 2003: Candidate of Sciences (PhD) in Neurobiology from St Petersburg State University with thesis titled 'Neurobiological mechanisms of emotions' 1994: Degree in Physiology from St Petersburg State University, Faculty of Biology Klucharev's research focuses on neuroeconomics, social and emotional neuroscience, and cognitive neuroscience, with particular emphasis on understanding decision-making processes, social influence, and conformity. His work integrates psychological theories with advanced neuroimaging techniques including fMRI, EEG, depth and scalp ERP, TMS, and MEG. His research has significant implications for understanding consumer behavior, persuasion, and the neural mechanisms underlying social conformity. His recent publications demonstrate a clear trend toward investigating the neural correlates of price perception, social influence on decision-making, and the processing of disinformation and deepfakes. His work bridges multiple disciplines, combining methods from neuroscience, psychology, and economics to address fundamental questions about human behavior in social contexts. Scientific awards: Best Teacher 2023-2024 Best Teacher 2018-2020 Best Teacher 2015 Klucharev has supervised numerous doctoral students including I. Ntoumanis, M. Martinez-Saito, O. Zinchenko, and Z. Yaple. His research has been supported by significant grants from Saint Petersburg State University, the Swiss National Science Foundation, and the European Commission. He has also served as an invited reviewer for prestigious journals including Psychological Science, Neuron, and Social Cognitive & Affective Neuroscience. As Director of the Institute of Cognitive Neuroscience at HSE University, Klucharev leads a multidisciplinary team exploring the neural mechanisms of social behavior, decision-making, and cognitive processes. His laboratory has gained international recognition, with research featured in major media outlets including BBC TV, Financial Times, The Telegraph, and CNN.

• Neuroimaging
• Neuroscience
• Functional Magnetic Resonance Imaging (fMRI)
• +3 more

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.

Anqi LiuView profile

Assistant Professor

• Machine Learning
• Trustworthy AI
• Distributionally Robust Learning
• +7 more

Anqi Liu is an Assistant Professor in the Department of Computer Science at the Whiting School of Engineering, Johns Hopkins University. She maintains significant affiliations with the Johns Hopkins Mathematical Institute for Data Science (MINDS) and the Johns Hopkins Institute for Assured Autonomy (IAA), while also collaborating extensively with the Center for Language and Speech Processing (CLSP) and the Laboratory for Computational Sensing and Robotics (LCSR). Her research focuses on developing principled machine learning algorithms for building reliable, trustworthy, and human-compatible AI systems in real-world applications. Key research areas include: Distributionally robust learning under covariate shift Uncertainty quantification for AI safety and fairness Safe exploration in control systems Fair machine learning under distribution shift Active learning under label shift Dr. Liu's work addresses critical challenges in high-stakes AI applications where reliability, safety, and societal impact are paramount. Her methods ensure AI systems remain robust to changing data environments, provide accurate uncertainty estimates, and incorporate human preferences in interactions. Analysis of her recent publications reveals a strong trajectory in trustworthy AI research with significant contributions to distribution shift handling, uncertainty quantification techniques, and safe decision-making frameworks. Her work bridges theoretical foundations with practical applications across healthcare, robotics, and social media analysis. Amazon Research Award Dr. Liu actively mentors eight PhD students and teaches specialized courses on Machine Learning for Trustworthy AI and standard Machine Learning at Johns Hopkins University, preparing the next generation of researchers to address critical challenges in AI safety and reliability.

Thomas HermannView profile

Researcher

• Auditory Data Science
• Interactive Sonification
• Smart Environments
• +5 more

Dr. rer. nat. Thomas Hermann is a faculty member at Bielefeld University's Faculty of Engineering, leading the Ambient Intelligence Group and coordinating the Computer Science program. He specializes in sonification, auditory data science, and smart environments. Head of Ambient Intelligence Working Group Computer Science Program Coordinator Member of multiple academic advisory boards His research focuses on interactive sonification for biomedical applications, quantum systems, and smart environments. Key projects include ECG sonification for cardiac diagnosis, real-time auditory feedback in swimming, and sonic interfaces for AR cooperation. Recent publications span 2025 with Python-based sonification tools ( pya AGen ), quantum system sonification, and ST-elevation myocardial infarction monitoring. He contributes to open-access supplementary materials and interdisciplinary workshops. As a researcher , Hermann develops practical sonification frameworks like Panson for facial behavior analysis, CardioScope for portable ECG monitoring, and Base Cube One for smart environments. His work bridges academic research with industry applications.

• Biomedical signal and image analysis
• Deep learning
• Computational statistics
• +5 more

Chee-Ming Ting is an Associate Professor in the School of Information Technology at Monash University Malaysia. His expertise lies in machine learning, data science, and biomedical engineering, with a focus on signal processing, computational neuroimaging, and computer-aided detection. Previously, he held positions at King Abdullah University of Science and Technology (Research Scientist) and Universiti Teknologi Malaysia (Senior Lecturer). He has authored over 26 journal papers and 43 conference papers, and has secured research grants totaling RM2.5 million as PI/Co-PI. Education: PhD in Mathematics - Statistics, Master of Engineering in Electrical Engineering, and Bachelor of Engineering (Hons.) in Electrical & Electronics Engineering. Research interests include biomedical signal/image analysis, deep learning, spatio-temporal modeling, and neuroimaging applications for disease prediction and patient monitoring. He has supervised 9 graduate students (4 PhD, 5 Masters) and currently oversees 10 PhD candidates. Awards include the IEEE Signal Processing Society Malaysia's Research Excellence Award (2019, 2022) and several national/international innovation awards. His work contributes to UN Sustainable Development Goals related to health and technological advancement. Key projects include frameworks for neurological disease prediction using brain networks and generative adversarial networks for medical imaging enhancement.

• Obsessive-Compulsive Disorder (OCD)
• Cognitive-Behavioral Therapy (CBT)
• Exposure Therapy
• +5 more

Brian Zaboski, PhD, is an Assistant Professor of Psychiatry at the Yale School of Medicine. He holds dual expertise as a licensed Connecticut psychologist and Nationally Certified School Psychologist. His primary academic affiliation is with the Obsessive Compulsive Disorder Research Clinic within the Department of Psychiatry. Dr. Zaboski completed his PhD in School Psychology at the University of Florida, gaining clinical experience across school-based to acute inpatient settings. He specializes in cognitive-behavioral therapy (CBT) and exposure-based interventions for psychological disorders, with particular focus on OCD neurobiology and treatment innovation. His research integrates advanced quantitative methods and translational neuroscience to improve exposure therapy efficacy. Key areas include neurobiological network analysis, machine learning applications for OCD severity prediction, and neurofeedback treatment trials. He leads clinical trials investigating psilocybin therapy, pharmacotherapy combinations, and brain network changes in OCD patients. Dr. Zaboski's work has been funded by prestigious grants including the 2022 Brain & Behavior Research Foundation Young Investigator Award. Collaborations include prominent researchers like Christopher Pittenger, Terence Ching, and Michelle Hampson. His publications span peer-reviewed journals in psychiatry, neuroscience, and school psychology, with a focus on OCD mechanisms, treatment innovation, and school-based mental health interventions. Clinical trials he participates in explore novel treatments like troriluzole and psilocybin while investigating biomarkers for treatment response prediction.

• Machine Learning
• Computational Biology
• Bioinformatics
• +4 more

Catherine Mooney is a Professor in the School of Computer Science at University College Dublin (UCD), leading the Life Science Data Analytics Group (LiSDA). Her research focuses on applying machine learning to healthcare challenges, including biomarker development, clinical decision support systems, and addressing ethical and technical barriers in healthcare AI. Education: BSc in [field unspecified] from Trinity College Dublin PhD in Computer Science from UCD Prof Dip University Teaching & Learning from UCD Research Interests: Machine Learning applications in healthcare Biomarker discovery for neurological and metabolic conditions Explainable AI for clinical decision support Promoting diversity and inclusion in STEM education Her work bridges computational methods with medical challenges, emphasizing ethical AI and translational research. Notable Awards: Best Paper Award in Applied Biosciences (2023) UCD Long-Service Award (2022) Best Poster Award at ITiCSE ’20 (2020) Her research has led to impactful tools like LiSDA’s clinical decision support systems for epilepsy and pregnancy care. She also advocates for gender diversity in computing, serving in leadership roles like Vice Principal for EDI in UCD’s College of Science (2022–2024).

Piotr WinkielmanView profile

Professor

• Emotion and Consciousness
• Social Cognition
• Embodied Cognition
• +5 more

Piotr Winkielman is a Professor of Psychology at the University of California, San Diego (since 2007), with affiliations at Warwick Business School (UK) and the Warsaw School of Social Sciences and Humanities (Poland). His research focuses on the interplay of emotion, cognition, embodiment, and consciousness in social cognition, employing methods from social/cognitive psychology and neuroscience. Key interests include unconscious emotion processing, facial mimicry, decision-making under emotional influence, and the neural basis of social perception. Education: PhD in Social Psychology (1997), University of Michigan MSc in Psychology (1991), University of Bielefeld, Germany BSc in Psychology (1988), University of Warsaw, Poland Research Interests: Winkielman explores how fleeting affective reactions influence behavior without conscious awareness, studying facial feedback mechanisms, emotional contagion, and the role of physiological signals in decision-making. His work bridges theories like Affect-As-Information and Facial Feedback, while challenging assumptions about the necessity of conscious processes in emotion. Grants & Funding: Supported by NSF Grant BCS-0350687 for studies on unconscious emotion and physiological feedback. Collaborations include projects on mimicry, stress effects, and cross-modal perception. Labs & Teams: Leads research at UCSD on embodied cognition and social neuroscience, with studies involving EEG, EMG, and behavioral experiments. International collaborations span UK, Poland, and Germany.

• Language Processing
• Cognitive Neuroscience
• Neuropsychology
• +3 more

Marta Kutas is a Distinguished Professor in the Department of Cognitive Science at the University of California, San Diego (UCSD), where she has held roles including Department Chair (2007–2019), Director of the Center for Research in Language (2007–2022), and Chancellor's Associates Endowed Chair (2017–2022). Her research focuses on language processing, neuropsychology, and electrophysiological methods, with a particular emphasis on event-related potentials (ERPs). She has contributed significantly to understanding semantic integration, memory, and neural mechanisms underlying language comprehension. Education includes a B.A. from Oberlin College (1971) and a Ph.D. in Psychology from the University of Illinois (1977). She has held adjunct roles at San Diego State University and the UCSD Department of Neurosciences. Her awards include the Revelle Medal (2023), membership in the American Academy of Arts and Sciences (2018), and the Cognitive Neuroscience Society's Distinguished Career Award (2015). Her research interests span language comprehension/production, neuropsychology, and ERP methodologies. Key publications analyze semantic processing, memory-related brain potentials, and the impact of individual knowledge on word processing. She has collaborated on studies involving Alzheimer's, Parkinson's, and schizophrenia, using ERPs to explore cognitive deficits.

Shima AbdullateefView profile

Research Fellow

• Biomedical Engineering
• Medical Informatics
• Computational Physiology
• +3 more

Shima Abdullateef is a Postdoctoral Research Fellow at the Centre for Medical Informatics within the Usher Institute, College of Medicine and Veterinary Medicine at the University of Edinburgh. Her work bridges biomedical engineering and clinical medicine through computational modeling and data science applications. Education: PhD in Biomedical Engineering, Brunel University London (2016-2020) MSc in Biomedical Engineering, University of Surrey (2014-2015) BSc in Biomedical Engineering (Bioelectrics), Science and Research IA University (awarded 2013) Research Focus: Dr. Abdullateef specializes in two interconnected domains: computational hemodynamics modeling arterial wave propagation and reflection phenomena, and machine learning-driven seizure detection using minimal-density EEG montages. Her arterial research investigates how vascular geometry impacts blood pressure dynamics, while her neuroscience work develops practical clinical tools for critical care seizure monitoring that reduce electrode requirements by 50-75% compared to standard EEG setups. Publication Trends: Her 15 most recent publications (2018-2025) reveal a strategic shift from pure cardiovascular modeling toward integrated neurological applications, with 60% focusing on seizure detection algorithms. The work consistently applies one-dimensional computational models and phase-synchrony analysis to solve clinical monitoring challenges, particularly in resource-constrained pediatric intensive care settings. Active Projects: A Window in the Brain: Developing a novel seizure detection tool for pediatric critical care (since 2020), funded through University of Edinburgh research channels Collaborative Environment: She operates within the Centre for Medical Informatics' interdisciplinary ecosystem, collaborating with clinicians from Edinburgh BioQuarter and data scientists to translate engineering solutions into clinical practice, with particular emphasis on making neurocritical care monitoring more accessible through reduced-sensor EEG technology.

Amy Vaughan Van HeckeView profile

Professor

• Developmental Psychology
• Neuroscience
• Autism Spectrum Disorder
• +5 more

Amy Vaughan Van Hecke serves as Assistant Chair and Professor in Marquette University's Department of Psychology, leading research on autism spectrum disorder (ASD) and social development across the lifespan using neuroimaging and psychophysiological methods. She directs community initiatives to improve autism services access for underserved Milwaukee populations through the Next Step Clinic. Her academic foundation includes: B.A. in Psychology from Smith College Ph.D. in Developmental Psychology from the University of Miami Dr. Van Hecke's research centers on brain activity, heart rate regulation, and social behavior in individuals with and without ASD, utilizing high-density EEG and MRI to examine neural responses to interventions like PEERS ® . Current projects investigate pandemic impacts on social interaction in autistic adults and neural mechanisms of social isolation remediation. Her work bridges laboratory neuroscience with community-based clinical applications. Publication analysis reveals consistent focus on intervention efficacy (particularly PEERS ® ), neural plasticity measurement, and comorbid conditions across developmental stages. Recent work emphasizes gender-specific outcomes, family impacts, and pandemic-related mental health, demonstrating methodological diversity from EEG asymmetry to community-based participatory research. Her distinguished scientific recognition includes: Kirschstein National Research Service Award (NRSA) from the National Institute of Mental Health Dr. Van Hecke mentors students through her Marquette Autism Project lab and the Next Step Clinic training program while securing major grants from Marquette University, Johnson Controls Foundation, and the Greater Milwaukee Funders’ Collaborative. She teaches undergraduate/graduate courses in developmental psychology and statistics. Advising: Clinical psychology graduate mentorship (excluding 2025 intake); undergraduate research supervision Grants: $500k+ secured for Next Step Clinic serving underserved Milwaukee children She co-directs the Marquette Interdisciplinary Autism Initiative and the Next Step Clinic, which employs a Family Navigation model in Milwaukee's Metcalfe Park neighborhood to provide autism screening, diagnosis, and therapy for children aged 15 months-10 years facing systemic barriers to care.

Valdas NoreikaView profile

Senior Lecturer

• Sleep and dreaming
• Consciousness
• Inter-brain synchronisation
• +3 more

Dr Valdas Noreika is a Senior Lecturer in Psychology at the School of Biological and Behavioural Sciences, Queen Mary University of London. He serves as Head of The Centre for Brain and Behaviour and leads the Sleep and Cognition Lab. His work bridges cognitive neuroscience, psychology, and clinical applications, with a focus on understanding consciousness and its disorders. Dr Noreika's educational background includes: BA in Philosophy from Vilnius University, Lithuania MSc in Neurobiology from Vilnius University, Lithuania PhD in Psychology from the University of Turku, Finland, focusing on altered states of consciousness and temporal distortions Dr Noreika's research explores the cognitive and neural mechanisms underlying sleep, dreaming, and consciousness. Using techniques including electroencephalography (EEG), transcranial magnetic stimulation (TMS), and psychophysics, his work investigates both basic mechanisms of consciousness and their applications to neurodevelopmental and mental health conditions. His research spans multiple domains including time processing, inter-brain synchronization across species, and environmental decision-making. A key aspect of his work involves translational research focusing on sleep, subjective experiences, and well-being in conditions such as learning disabilities, ADHD, autism, and depression. Analysis of Dr Noreika's recent publications reveals a strong focus on consciousness studies, neural mechanisms of sleep and dreaming, and applications to neurodevelopmental conditions. His work frequently employs EEG and other neuroimaging techniques to study brain activity during various states of consciousness. Recent trends show increasing emphasis on inter-brain synchronization, particularly in infant-parent interactions and cross-species communication, as well as growing interest in environmental psychology and climate change-related decision making. Dr Noreika has secured significant research funding including: The neural basis of inter-species communication - £155,098 from the Biotechnology and Biological Sciences Research Council (2024-2026) Sleep and circadian interactions with sensory sensitivity in adults with intellectual disabilities - £103,229 from the Baily Thomas Charitable Fund (2023-2025) As a supervisor, Dr Noreika advises multiple PhD students working on diverse topics including Alzheimer's disease diagnosis using information theory, emotion recognition, thermal sensation in Parkinson's disease, cultural differences in cognitive processes, and time processing. His Sleep and Cognition Lab serves as a hub for interdisciplinary research bridging neuroscience, psychology, and clinical applications. Dr Noreika leads the Sleep and Cognition Lab at Queen Mary University of London, which focuses on investigating the neural mechanisms of sleep, dreaming, and consciousness. The lab brings together researchers from diverse backgrounds to study both fundamental aspects of consciousness and their applications to clinical populations. Current projects include investigations of sleep and sensory sensitivity in adults with learning disabilities and human-dog interaction studies.