Find Academic Supervisors

• Cognitive Psychology
• Educational Technology
• Multimodal Interaction
• +4 more

Prof. Dr. Stephan Schwan is the head of the Realistic Representations research group at the Institute for Knowledge Media (IWM) at the University of Tübingen. He holds a professorship in psychology and has extensive experience in cognitive and educational research, particularly focusing on how dynamic audiovisual media and digital representations influence human learning and perception in informal settings like museums. His career includes a professorship for e-learning at Johannes Kepler University Linz (2002–2004) and a tenure as Deputy Director of the IWM (2017–2024). He earned his doctorate and habilitation in psychology from the University of Tübingen. His research explores the cognitive processing of realistic media, including haptic exploration of museum artifacts, AI-generated language effects, and spatial-temporal data visualization. Projects such as 'Digital Materialities' and 'Historical Sounds' investigate how digital tools and authentic objects enhance learning in museums. Key interests include museum visitor behavior, media authenticity, and the role of sensory engagement in knowledge acquisition. Publications span cognitive psychology, educational technology, and museum studies, with a focus on multimedia learning principles and their application in real-world settings. His work bridges theoretical insights with practical applications, emphasizing the interplay between digital media and human cognition. Current projects include studying the cognitive impact of AI-generated narratives, immersive digital environments, and spatiotemporal data representation. Prof. Schwan collaborates across disciplines, integrating psychology, education, and digital humanities to advance understanding of media-driven learning processes.

• Cognitive Neuroscience
• Neuropsychology
• Memory Research
• +3 more

Petar Raykov holds the position of Honorary Research Fellow in the School of Psychology at the University of Sussex. His research focuses on cognitive neuroscience, particularly exploring how the brain integrates prior knowledge with ongoing sensory input, processes event structures, and represents social and semantic information. He employs neuroimaging techniques like fMRI to investigate neural mechanisms underlying memory, perception, and goal-directed behavior. Raykov earned his PhD in Psychology from the University of Sussex in 2020, with a thesis titled Neurobiology of specific and general prior knowledge . His work bridges experimental psychology and computational neuroscience, addressing topics such as episodic memory, predictive coding, and the neural correlates of social cognition. His recent publications analyze brain activity during movie watching, event perception, and the role of semantic networks in dialogue comprehension. He also contributes to longitudinal studies like the Cam-CAN project, examining aging-related cognitive changes. Despite his prolific output, no scientific awards have been explicitly mentioned in the provided texts. Raykov collaborates on interdisciplinary projects involving cognitive genetics (e.g., APOE genotype studies) and neuroimaging protocols for white matter analysis. His research further extends to Tourette syndrome neurobiology and functional connectivity in older adults. He maintains an active presence in Sussex’s psychology research community without listed academic advising responsibilities.

Alessandro GiffordView profile

Researcher

• Neuroscience
• Computational Neuroscience
• Machine Learning
• +3 more

Alessandro Gifford is a PhD candidate in computational neuroscience at the Freie Universität Berlin , affiliated with the Neural Dynamics of Visual Cognition Lab led by Prof. Radoslaw Cichy. His research focuses on understanding visual processing in the human brain using computational approaches, including machine learning and deep learning applied to M/EEG and fMRI data. He is funded by the Einstein Center for Neurosciences Berlin (2020–2023) and is a member of the Bernstein Center for Computational Neuroscience Berlin . Education: Bachelor of Arts in Philosophy, University of Trento, Italy Master of Science in Cognitive Neuroscience, CIMeC, Italy Research Interests: Computational modeling of visual cognition Intersection of biological and artificial vision systems Machine learning applications in neuroscience Grants & Awards: Einstein Center PhD Fellowship (2020–2023) Bernstein Center Membership Supervision: Current: Shreyas Gadge Past: Andrei Kitaitsev, Furkan Özkan Hüseyincan Labs & Collaborations: Active in ERC-funded TRANSFORM project (2025–) investigating brain mechanisms of visual perception across development.

Sam BerensView profile

Assistant Professor

• Cognitive Neuroscience
• Learning Systems
• Memory Encoding
• +4 more

Sam Berens is an Assistant Professor in Psychology at the University of Sussex. He holds a PhD from the University of Sussex (2015), an MSc from Sussex (2012), and a BSc from Keele University. His research investigates the neuroscience of learning and memory, with particular focus on pattern learning, spatial navigation, and forgetting mechanisms. Research examines: Neural basis of spatial memory formation Mechanisms of pattern generalization Forgetting dynamics and memory precision Vocabulary acquisition processes Neuropharmacology of memory systems His publications demonstrate consistent use of fMRI methodologies to study memory systems, with recent work examining APOE genotype effects on cognition and targeted memory reactivation during sleep. Awarded the BPS Cognitive Section Annual Award (2021) for research on memory accessibility and precision in forgetting. Teaching includes Ethics and History of Psychology (MSc module), with drop-in hours available. Supervises student research through departmental honors and accelerated master's programs.

Morgan BarenseView profile

Associate Professor

• Cognitive Neuroscience
• Memory Formation
• Aging and Dementia
• +3 more

Morgan Barense is an Associate Professor at the University of Toronto (since 2014) and Director of the Toronto Neuroimaging Facility. Her research focuses on understanding how the brain supports memory formation, aging-related cognitive decline, and neurological disorders through neuroimaging, neuropsychology, and cognitive psychology. She holds a B.A. from Harvard University and a Ph.D. from the University of Cambridge, followed by a postdoctoral fellowship at Peterhouse (Cambridge). Her expertise spans Perception and Cognition Cognitive Neuroscience Neuroimaging Techniques Memory Disorders She investigates neural mechanisms underlying episodic memory, autobiographical memory, and spatial navigation using fMRI, behavioral studies, and computational modeling. Her work has been recognized with prestigious awards such as the Canada Research Chair in Cognitive Neuroscience and the Young Investigator Award from the Cognitive Neuroscience Society. Her research explores applications like smartphone-based interventions to mitigate memory decline in aging populations and neuroimaging methods to assess cognitive functioning in acute stroke patients. She also studies how prediction errors and environmental boundaries influence episodic memory consolidation. Current projects include examining hippocampal function in dementia risk groups and developing frameworks for understanding memory across multiple temporal and spatial scales.

Patrick MayView profile

Associate Professor

• Neuroscience
• Auditory Neuroscience
• Computational Neuroscience
• +4 more

Dr. Patrick May is a Reader in Neuroscience at Lancaster University, affiliated with Fylde College and the Neuroscience and Neurocognition department. His research focuses on auditory neuroscience, computational modeling of neural systems, and cognitive aging mechanisms. His work integrates neurophysiological techniques like MEG and EEG with computational approaches to understand sensory processing and neurocognitive changes across the lifespan. Key research interests include auditory cortex adaptation, predictive coding frameworks, and the neurobiological basis of cognitive reserve in aging. He explores how brain network dynamics influence verbal fluency and word-finding abilities, particularly in older adults. His computational models of sensory systems aim to bridge anatomical structure and functional response patterns in auditory and visual cortices. Recent studies investigate hemispheric differences in auditory adaptation, optimization of auditory cortex models using evolutionary algorithms, and the role of lifestyle factors in cognitive aging theories such as the Scaffolding Theory. His work has been published in journals like Hearing Research , Neurobiology of Language , and PLoS ONE . He collaborates on interdisciplinary projects analyzing functional brain connectivity and EEG/MEG data, contributing to both theoretical neuroscience and applied aging research. While no formal awards are listed, his extensive publication record reflects sustained academic engagement in these domains.

Giuseppe SartoriView profile

Professor

• Neural basis of intentions
• Conscious decisions
• Memory detection
• +11 more

Giuseppe Sartori is a Full Professor at the University of Padua, specializing in forensic neuropsychology and cognitive science. His research focuses on the neural basis of intentions, memory detection, and deception analysis, with particular emphasis on applications in legal and clinical contexts. He explores the intersection of artificial intelligence, including large language models, with psychiatry and forensic evaluation. His work also addresses malingering, child testimony reliability, and behavioral genetics related to psychopathy and mental insanity assessment. Research interests include the Implicit Association Test, PTSD prevalence analysis, and the use of machine learning in psychological testing and forensic science. He has developed methods for detecting deception through linguistic cues, eye tracking, and keystroke dynamics, contributing to advancements in forensic interviewing techniques. Recent publications highlight innovations in AI-driven deception detection, neuropsychological evaluations of cognitive reserve in brain injury recovery, and interdisciplinary approaches to insanity assessment. His work emphasizes practical applications for legal systems, such as improving witness reliability evaluations and identifying fraudulent claims in clinical settings. Labs and collaborations focus on integrating neuroimaging, behavioral analytics, and computational models to enhance forensic psychiatric evaluations. His research bridges neuroscience, technology, and law, addressing gaps in evidence-based practices for courts and clinical practitioners.

Cameron EllisView profile

Assistant Professor

• Developmental Psychology
• Learning & Memory
• Neuroimaging
• +4 more

Dr. Cameron Ellis is an Assistant Professor in the Department of Psychology at Stanford University. He leads the Scaffolding of Cognition Team, exploring the cognitive foundations of infancy through neuroscience and cognitive science methods, particularly fMRI with awake infants. His work focuses on understanding how infants perceive, learn, and remember, with a strong emphasis on interdisciplinary research. Education: PhD in Psychology, Yale University (2021) MA in Psychology, Princeton University (2017) B.S. (Hons) in Psychology, Auckland University (2013) Research Interests: Dr. Ellis investigates developmental approaches to cognition, learning mechanisms, neuroimaging techniques (e.g., fMRI), and visual perception in infants. His team studies plasticity in early childhood, self-regulation processes, and vision science, leveraging cutting-edge methodologies to uncover neural mechanisms underlying infant cognition. Awards: FLUX Dissertation Prize (2021) James Grossman Dissertation Prize (2021) William Kessen Teaching Award (2019) Advising & Grants: While no specific grants or advisees are listed, the Scaffolding of Cognition Team fosters collaborative research in developmental neuroscience. Dr. Ellis emphasizes methodological innovation, such as refining fMRI techniques for awake infants. Labs/Teams: Director of the Scaffolding of Cognition Team at Stanford, advancing interdisciplinary research in infant cognitive development.

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

Todd Ferretti is Associate Professor in the Department of Psychology at Wilfrid Laurier University, where he directs the Language and Cognition Lab. He holds a Ph.D. and M.A. in Psychology from the University of Western Ontario and B.Sc. degrees in Psychology and Biology from Acadia University. His research examines cognitive mechanisms underlying language comprehension, including figurative language processing, event representation, and memory retrieval. Current projects investigate how world knowledge informs interpretation of literal/nonliteral language and how linguistic structures trigger event information retrieval. His publications demonstrate consistent focus on temporal cognition and narrative processing, with methodologies integrating behavioral experiments and neurocognitive measures like Event-Related Potentials (ERPs). Recent work explores proverb comprehension, grammatical aspect effects, and mental simulation of events. Awards include multiple NSERC research grants, a Canadian Foundation for Innovation equipment grant, and postdoctoral fellowships at UC San Diego. He has supervised over 20 graduate students in cognitive psychology research. The Language and Cognition Lab investigates how conceptual knowledge influences language understanding and event representation, with specialized EEG equipment for neurolinguistic studies.

Fang Jackson-YangView profile

Lecturer

• Psycholinguistics
• Language-mediated Attention
• Second Language Acquisition
• +4 more

Fang Jackson-Yang is a psycholinguist and lecturer at the University of Edinburgh's Psychology Department within the School of Philosophy, Psychology and Language Sciences. She holds teaching roles across undergraduate and postgraduate programs including Data Analysis in R, Psychological Research Skills, and Second Language Teaching Curriculum. Her research focuses on prominence in language, language-mediated attention, and Mandarin syntax, employing experimental methods and corpus studies. She has presented at leading conferences like AMLaP and IACL, and her work appears in journals such as Discourse Processes and Royal Society Open Science . Education includes MSc/PhD studies at Beijing Language and Culture University, University of Sheffield, University of Manchester, and University of Edinburgh. Her teaching spans quantitative research skills, language acquisition, and multilingual education. She supervises MSc dissertations and has organized academic events including the 2024 AMLaP conference in Edinburgh. Research explores how speakers encode conceptual prominence in transitive sentences and hearers decode attentional cues through eye-tracking experiments. Past work includes Mandarin left-periphery corpus studies and second language acquisition of topic-comment structures. Active in academic service, she reviews for Discourse Processes and Linguistic Inquiry .

Rachel Pulverman-SilvermanView profile

Associate Professor

• Language Development
• Cognitive Development
• Child Development
• +3 more

Rachel Pulverman-Silverman is an Associate Professor of Psychology at Delaware State University. She holds a B.A. in Psychology from Cornell University (2000), an M.A. in Linguistics from the University of Delaware (2002), and a Ph.D. in Linguistics with a Psycholinguistics specialization from the University of Delaware (2005), followed by postdoctoral training in Developmental Psychology at the University of Michigan (2007). Her research focuses on language and cognitive development in infants and young children, particularly exploring how cognitive, linguistic, social, and cultural factors influence early word learning. She also investigates adult second language acquisition, especially motion event descriptions across languages. Key areas of expertise include experimental design for infant research and cross-linguistic developmental comparisons. Notable contributions include studies on infants' attention to motion components (manner/path) as precursors to verb learning, bilingual cognitive development differences between English/Mandarin and English/Chinese learners, and methodological advancements in infant research. Her work spans developmental, cognitive, and psycholinguistic domains with a strong emphasis on cross-cultural and cross-linguistic comparisons. Publications highlight interdisciplinary approaches to understanding foundational cognitive processes underlying language acquisition, with a focus on how preverbal infants conceptualize dynamic events and how these conceptualizations shape later language development.

MANUEL LAMA PENINView profile

Professor

• Process Mining
• Artificial Intelligence
• Data Science
• +7 more

Manuel Lama Penín is a Full Professor at the University of Santiago de Compostela (USC), affiliated with the Department of Electronics and Computing within the School of Engineering. He is a member of the CITIUS research center and the GSI (Grupo de Sistemas Intelixentes) research group, with prior involvement in the TecnoEduc (Technology in Education) group. His doctoral thesis (2000) focused on knowledge modeling and architecture for therapeutic expert systems in intensive care units, advised by Dr. Senén Barro and Dra. María Jesús Taboada Iglesias. His research expertise spans Process Mining, Artificial Intelligence, and Data Science with applications in healthcare informatics, business process optimization, and educational technologies. Key contributions include frameworks for predictive monitoring (e.g., VERONA library), declarative process alignment (DeclareAligner), and conversational agents for process mining (C-4PM). He also explores explainable AI, semantic web technologies, and natural language generation for process documentation. His work intersects interdisciplinary areas like healthcare workflows, cloud-based process analysis, and machine learning for event log analysis. Notable projects include semantic annotation of educational resources, adaptive learning systems (SoftLearn platform), and service composition algorithms. His research is supported by collaborations with healthcare institutions and industry partners. Dr. Lama Penín has contributed to over 70 peer-reviewed publications since 2000, emphasizing methodological advancements in process intelligence, AI-driven analytics, and educational technology integration. His work addresses challenges in process variability detection, real-time monitoring, and bridging technical systems with human-centric processes.

Brad StoryView profile

Professor

• Speech Acoustics
• Vocal Tract Modeling
• Magnetic Resonance Imaging (MRI)
• +4 more

Brad Story is a Professor of Speech, Language, and Hearing Sciences and Associate Dean for Faculty Affairs at the University of Arizona's College of Science. He holds a Bachelor's in Applied Physics from the University of Northern Iowa and a doctoral degree in Speech and Hearing Science from the University of Iowa. His research focuses on computational modeling of vocal tract dynamics, acoustic analysis, and MRI-based imaging of speech production. He has pioneered methods for simulating speech production using vocal tract models and has contributed to understanding source-filter interactions in singing and speech. Dr. Story's work integrates engineering principles with speech science, including developing instrumentation systems for acoustic measurements and advancing techniques like glottal inverse filtering. His laboratory employs advanced technologies such as magnetic resonance imaging (MRI) and aerodynamic signal analysis. He has also been involved in collaborative projects like the National Center for Voice and Speech and has authored foundational texts on speech and hearing anatomy. His research trends emphasize interdisciplinary approaches, combining computational models with clinical applications, such as vocal tremor simulation and telepractice considerations. While his articles span decades, recent work highlights innovations in MRI acceleration, vocal tract modeling with hybrid imaging, and neural network-based pathology detection. His contributions bridge speech science theory and practical clinical insights. Dr. Story advises on faculty affairs and teaches courses like Acoustics and Perception of Speech. His labs focus on anatomical imaging and vocal tract dynamics, with a long-term project on MRI-based vocal tract shape analysis. Collaborative efforts include studies on child vocal tract development and vocal tract modeling across ages.

Anna LeshinskayaView profile

Assistant Professor

• Cognitive Science
• Neuroscience
• Artificial Intelligence Ethics
• +3 more

Anna Leshinskaya is an Assistant Professor in the Department of Cognitive Sciences at the University of California, Irvine (UCI), and a Fellow at the Center for Neurobiology of Learning & Memory. She is also affiliated with the AI Objectives Institute. She holds a PhD in Cognitive Psychology from Harvard University (2015). Her research focuses on understanding human cognition, its neural basis, and its implications for artificial intelligence. Key areas include causal learning, semantic memory, and cognitive/moral alignment between humans and AI systems. Education: PhD in Cognitive Psychology, Harvard University, 2015 Research Interests: Causal schema processing in the lateral temporal cortex Relational memory formation in the brain Neural representations of moral and hedonic value in large language models Integration of event experiences into relational knowledge Her work bridges cognitive neuroscience with AI ethics, investigating how human cognitive processes can inform machine learning systems. Publications Trends: Recent work emphasizes causal reasoning mechanisms (e.g., tool selectivity linked to causal inference) and the application of cognitive principles to evaluate AI alignment. This reflects a shift toward translational research connecting brain science with technological development. Awards: No specific prizes mentioned, but her work has been published in high-impact journals like Cerebral Cortex and Cognitive Science. Grants & Labs: Her research is supported by grants related to cognitive neuroscience and AI ethics. She runs a cognitive science lab at UCI, focusing on experimental and computational methods to study human-AI interactions. Affiliations: Active collaboration with interdisciplinary teams at the AI Objectives Institute to address foundational challenges in AI safety and alignment.

Bhuvana NarasimhanView profile

Professor

• Language Acquisition
• Linguistics
• Cognitive Science
• +4 more

Bhuvana Narasimhan is a Professor of Linguistics at the University of Colorado, Boulder, and Director of the Language, Development & Cognition Lab. She is also a Fellow of the Institute of Cognitive Science. Her research focuses on semantics-pragmatics, first language acquisition, and the crosslinguistic study of language-cognition interactions, with a particular emphasis on Hindi and Tamil. Narasimhan holds a PhD in Linguistics from Boston University (1998) and has conducted postdoctoral research at Bell Labs (Hindi text-to-speech synthesis) and the Max Planck Institute for Psycholinguistics (Netherlands). Her work includes corpus-based and experimental studies on child language development, verb semantics, and information structure. Key contributions include longitudinal corpora of caregiver-child interactions in Hindi and Tamil, and edited volumes on event encoding and information structure. Recent research explores ergative case marking in Hindi, differential object marking in Tamil, and computational models of language acquisition. Narasimhan has contributed to special journal issues on topics such as 'Embodied Cognition and Language' and 'The Acquisition of Information Structure.' Her awards include Fellowship at the Max Planck Institute and her current role as Institute of Cognitive Science Fellow. Her lab focuses on interdisciplinary projects combining linguistic theory, experimental methods, and computational modeling. Ongoing research investigates crosslinguistic patterns in motion events, prosodic cues in child language, and cognitive factors shaping syntactic choices.