Dr. Jane Garrison is a cognitive neuroscientist and Lecturer at the University of Cambridge, affiliated with Queens’ College. She serves as Director of Studies in both Psychological & Behavioural Sciences and Natural Sciences (Biological) for Part IA students, and as Admissions Tutor at Queens’ College. MA (Cantab), MSc (Hertfordshire), PhD (Warwick), PhD (Cantab) Focus on the neural basis of reality monitoring and hallucinations in schizophrenia and other conditions Current research explores paracingulate sulcus morphology, functional connectivity, and neurofeedback interventions Her recent publications emphasize neuroimaging methodologies, structural MRI analysis, and computational frameworks for understanding hallucination mechanisms. Contact: jrg60@cam.ac.uk
Carolyn Parkinson is an Associate Professor at the University of California, Los Angeles (UCLA), holding the Bernice Wenzel and Wendell Jeffrey Term Endowed Chair in Cognitive Neuroscience. Her research integrates social psychology with computational neuroscience to explore how the human brain represents, navigates, and shapes social environments. University: University of California, Los Angeles (UCLA) Academic Rank: Associate Professor Research Focus: Social and Affective Neuroscience, Social Network Analysis, Neural Mechanisms of Psychological Distance At the Computational Social Neuroscience Lab , Parkinson investigates: Neural encoding of social network structures Shared mechanisms for spatial, temporal, and social distance perception Computational modeling of social cognition Functional MRI analysis of social relationships Her work reveals that: Resting-state brain connectivity predicts social proximity Multivoxel patterns decode social knowledge representations Old cortical structures repurpose spatial processing for social cognition Neural population coding transcends historical phrenology-based approaches Notable awards include the Bernice Wenzel and Wendell Jeffrey Term Endowed Chair. She employs machine learning and social network theory to analyze distributed brain activity patterns, advancing understanding of human social behavior and cognition.
Dr. Matthias Gruber is a Reader (Associate Professor) in Cognitive Neuroscience at Cardiff University's School of Psychology. He leads the Cardiff University Motivation and Memory Lab at CUBRIC, where his research investigates the neuroscience of motivation and its effects on memory using multimodal neuroimaging techniques (structural/functional MRI, M/EEG). His work focuses on how intrinsic motivational states like curiosity enhance learning and memory consolidation. Education includes: PhD in Cognitive Neuroscience, University College London (2007-2011) Research Assistant position at University of Regensburg (2003-2006) Research explores: Neural mechanisms of curiosity and motivation Effects of reward anticipation on memory encoding Hippocampal-prefrontal interactions during learning Developmental aspects of curiosity from childhood to adulthood Real-world applications of motivation research His publications consistently demonstrate how motivational states modulate memory systems, with recent work focusing on spatial exploration dynamics and educational applications. Awards and honors: Sir Henry Dale Fellowship (Wellcome/Royal Society, 2019-2024) Laird Cermak Award (2016) Michael S. Gazzaniga Prize for Cognitive Neuroscience (2015) Elected to Memory Disorders Research Society (2017) Research funding includes major grants from Wellcome Trust, Royal Society, and European Commission. He leads the Motivation and Memory Lab at CUBRIC and is currently accepting expressions of interest from potential research trainees.
Zohreh Sharafi is an Assistant Professor of Software Engineering in the Department of Computer and Software Engineering (GIGL) at Polytechnique Montréal. Previously, she served as a Senior Research Fellow in the Department of Electrical and Computer Engineering at the University of Michigan, Ann Arbor, where she worked with Dr. Westley Weimer and was awarded the prestigious NSERC Postdoctoral Fellowship. Prior to her academic career, she worked as a software engineer at Morgan Stanley, contributing to the firm's electronic trading platform and serving as principal architect of SURF, a market data simulator. Her educational background includes a Ph.D. in Computer Engineering from École polytechnique de Montréal under the supervision of Dr. Giuliano Antoniol and Dr. Yann-Gaël Guéhéneuc, a Master of Applied Science in Software Engineering from Concordia University, and a Bachelor of Computer Engineering from the University of Tehran. Dr. Sharafi leads the SENSE Lab, a multidisciplinary software engineering research laboratory focused on understanding problem-solving strategies developers use during software development, with particular attention to human factors such as gender and native language. Her research combines human-centric design with experimental methodologies, investigating cognitive processes involved in software development using biometric measures including eye tracking and neuroimaging. Current active projects include evaluating trustworthiness perceptions of software artifacts and studying the role of creativity in software engineering tasks. She has made significant contributions to understanding how gender influences program comprehension and code review processes. Her publication record demonstrates a strong focus on empirical methods in software engineering, particularly eye tracking and neuroimaging techniques to study developer cognition. Her work spans program comprehension, code review, requirements engineering, and the impact of human factors on software development processes. She has developed methodological frameworks for conducting eye tracking studies in software engineering and has made notable contributions to understanding how visualization techniques affect software development tasks. NSERC Postdoctoral Fellowship NSERC Discovery Grant Program and Launch Supplements (Sep 2024-Sep 2029) IVADO Startup & Operation Fund (Jan 2022-Jan 2023) Scholarship for Doctoral Studies from Fonds de Recherche du Quebec Distinguished Reviewer Awards from IEEE ICPC 2020 and ACM FSE 2024 Dr. Sharafi actively mentors students including Mahta Amini (PhD Candidate, IVADO Scientifique en résidence 2024 Laureate), Cameron Cherif (PhD Candidate), Sara Yabesi (Master's Student), and Anthonia Njoku (Graduate research intern). She serves on numerous conference organizing committees including as Local Arrangement Chair for SANER 2025, Program Co-chair for SEMLA 2024, and as a reviewer for top-tier journals including IEEE Transactions on Software Engineering and ACM Computing Surveys. Her research is supported by multiple grants focused on understanding human factors in software engineering through empirical methods. At Polytechnique Montréal, Dr. Sharafi directs the SENSE Lab which brings together computer scientists, cognitive scientists, and software engineering researchers to investigate the cognitive aspects of software development. The lab employs advanced methodologies including eye tracking, functional near-infrared spectroscopy (fNIRS), and functional magnetic resonance imaging (fMRI) to study how developers comprehend, navigate, and modify software systems. Current projects examine trustworthiness perceptions in code review, the role of creativity in software engineering tasks, and gender differences in software development processes.
Jon Brennan is an Assistant Professor in the Department of Linguistics at the University of Michigan, affiliated with the College of Literature, Science, and the Arts (LSA). His research focuses on neurolinguistics, computational linguistics, and psycholinguistics, particularly investigating how the brain processes language structure and meaning. He leads the Computational Neurolinguistics Lab, which develops neurocomputational models to study language comprehension mechanisms. Brennan received an NSF Grant for collaborative research with Christophe Pallier (Paris) on neurocomputational models of natural language processing. His work integrates EEG, fMRI, and MEG techniques to decode linguistic features in neural signals. Key research areas include syntax-semantics interfaces, multilingual processing, and developmental disorders like dyslexia. Notable contributions include studies on hierarchical syntactic structure, minimal pairs in language models, and neural correlates of theory of mind in children. Brennan collaborates internationally, exemplified by the US-French NSF-CRCNS grant. He has published extensively on topics like neural decoding of grammatical features, LLM internal representations, and bilingual processing mechanisms. Scientific awards include the NSF Collaborative Research in Computational Neuroscience (CRCNS) Grant (2016). His research bridges computational modeling and experimental neuroscience, aiming to reveal how language mechanisms are implemented in neural systems.
Yize Zhao is an Associate Professor in the Department of Biostatistics at Yale School of Public Health and an Associate Professor in the Department of Biomedical Informatics & Data Science at Yale University. She holds affiliations with multiple Yale research centers including the Yale Center for Analytical Sciences, Yale Alzheimer's Disease Research Center, Yale Wu Tsai Institute, Yale Center for Brain and Mind Health, and Yale Computational Biology and Bioinformatics. Dr. Zhao's research focuses on developing statistical and AI methods to analyze large-scale complex biomedical data including medical imaging, genomics, and electronic health records. Her methodological expertise spans Bayesian statistics, feature selection, predictive modeling, data integration, missing data analysis, and network analysis. Her research interests span multiple biomedical domains with a strong focus on mental health, psychiatry, neurodegenerative diseases, and aging. Her recent work includes brain-to-behavior modeling, multi-layer biomedical networks, imaging genetics and genomics, and the integration of multi-modal biomedical data with real-world data. Dr. Zhao's work has resulted in numerous high-impact publications, with recent research focusing on Alzheimer's disease, brain network analysis, and advanced statistical methods for neuroimaging. Her publications show a strong trend toward integrating multi-modal data sources and developing sophisticated statistical approaches to address complex biomedical questions. Thelma and Marvin Zelen Emerging Women Leaders in Data Science Award from the Institute of Mathematical Statistics (IMS) COPSS Emerging Leader Award from the Committee of Presidents of Statistical Societies (COPSS) YSPH Investigator Research Award Yale Alzheimer's Disease Research Center Research Scholar Award Elected member of the International Statistical Institute Dr. Zhao serves as an Associate Editor for Biometrics and is a standing member of the NIH Biodata Management and Analysis (BDMA) study section. Her research is supported by multiple NIH grants, highlighting the significance and impact of her work in biostatistics and biomedical data science.
Xenophon Papademetris is a Professor of Biomedical Informatics & Data Science and Radiology & Biomedical Imaging at Yale School of Medicine. He serves as Associate Director of Biomedical Imaging Data Sciences at Yale Biomedical Imaging Institute and directs the Medical Software and Medical Artificial Intelligence Certificate Program. PhD in Electrical and Information Sciences from Yale University (2000) BA from Cambridge University (1994) Postdoctoral Fellowship at Yale University (2002) His research focuses on medical image analysis, machine learning, and biomedical software development. He has developed tools like BioImage Suite Web and contributed to standards committees at the Association for the Advancement of Medical Instrumentation (AAMI). His work spans modalities including MRI, CT, PET, and optical imaging. Recent publications emphasize neuroimaging analysis, explainable AI in healthcare, and multimodal data integration across species. He leads NIH-funded research under the BRAIN Initiative (R24 MH114805) and has authored a textbook on Medical Software published by Cambridge University Press. IEEE Senior Member Yale Brown-Coxe Postdoctoral Fellowship Harding Bliss Prize for Excellence in Engineering He directs the BioImage Suite Project, creating web-based image analysis tools using JavaScript and WebAssembly. His teaching includes both academic courses and a Coursera program on Medical Software with over 14,000 enrollments.
Kay James is an Associate Professor of Neuroscience and Education at Teachers College, Columbia University, and serves as Director of the Graduate Program in Neuroscience and Education and the Neurocognition of Language Lab. Their work focuses on neural mechanisms underlying language disorders, second language acquisition, and cognitive processes in schizophrenia. Key affiliations include Biobehavioral Sciences, Neuroscience and Education, Human Development, and Cognitive Science in Education. Research interests emphasize the neural basis of language processing in pathological contexts such as developmental speech disorders and schizophrenia, alongside second language acquisition in adults. Their interdisciplinary approach bridges cognitive neuroscience with clinical and educational interventions. Publications span studies on mismatch negativity in speech disorders, syntactic development in Arabic diglossia, and brain-behavior asymmetry in schizophrenia. Ongoing work explores voice-related cortical potentials and emotional face processing through electrophysiological methods. Labs and teams include the Neurocognition of Language Lab, focusing on language neurobiology and clinical applications. Grants and advising roles are not explicitly detailed in the provided materials.
Christopher Conway serves as Associate Professor of Psychology at Fordham University's College of Arts and Sciences, where he directs the Bronx Personality (B-PER) Lab. His research investigates borderline personality disorder, anxiety, depression, and distress tolerance using experience sampling methods and longitudinal designs. The lab examines personality development across key transitions such as romantic breakups and financial strain. 2007 BS in Psychology and Spanish, Duke University 2009 MA in Clinical Psychology, University of California, Los Angeles 2013 PhD in Clinical Psychology, University of California, Los Angeles Conway's work centers on distress tolerance as a protective factor against self-injurious behaviors, momentary personality processes using ecological assessment, and the HiTOP consortium 's dimensional classification of psychopathology. His lab develops quantitative models linking personality dimensions to clinical outcomes, with emphasis on how stressors trigger symptom changes. Recent publications reveal neuroticism's specific association with broadband internalizing symptoms rather than narrowband anxiety or anhedonia. His publications demonstrate consistent focus on transdiagnostic mechanisms and dimensional classification systems . Key trends include validating the HiTOP framework across cultures, examining distress tolerance in substance use contexts across four continents, and developing within-person models of self-injury using registered report methodology. Professional affiliations include: Society for Research on Psychopathology Association for Psychological Science Association for Behavioral and Cognitive Therapies Association for Research in Personality Conway advises multiple graduate students in the B-PER Lab and leads several active studies including MOMENT (Measuring Our Momentary Emotions and Negative Thoughts), DENEM (Daily Experiences of Negative Emotions), and READI (Responses to Emotions And Daily Interactions). His lab participates in the multinational Cross-cultural Addictive Behaviors Study examining distress tolerance across seven countries. All research materials follow open science principles through his OSF repository. The B-PER Lab maintains active research programs examining personality development through: 3-year longitudinal Multiyear Adult Personality Project (MAPP) Cross-cultural Addictive Behaviors Study (CABS) Daily emotion regulation projects using smartphone-based assessments
Smita Ghosh is an Assistant Professor in the Department of Mathematics and Computer Science at Santa Clara University, part of the College of Arts and Sciences. Her research focuses on social network analysis, algorithms for information diffusion, and applications in cybersecurity, disaster management, and machine learning. She holds a B.Tech. from the West Bengal University of Technology, India, and an M.S. and Ph.D. from the University of Texas, Dallas. Her work addresses challenges in rumor containment, clickbait detection, and optimizing network models for social media content analysis. Recent publications include studies on hypergraph-based solutions for rumor blocking and stochastic models for emergency response in social networks. She also explores cross-modal topic modeling for enhancing content detection algorithms. Notable contributions include developing data-driven strategies for identifying hate speech spreaders and improving wildfire severity predictions using environmental features. Her research bridges theoretical computer science with real-world applications in public health, education, and disaster management. Her academic contributions include organizing conference proceedings like the 18th International Conference on Algorithmic Aspects in Information and Management (AAIM 2024). She actively contributes to educational initiatives such as the Classroute project, creating multilingual educational content for Punjabi and Urdu speakers.
Ingo Bojak is a Professor at the School of Psychology and Clinical Language Sciences , University of Reading. His research focuses on computational neuroscience, neurodynamics, and neural population models. He explores topics such as biological mistake-making, EEG analysis, and the effects of anesthesia on brain activity. Bojak serves as an associate editor for Neurocomputing and related journals. His work bridges theoretical frameworks with experimental data, emphasizing cross-scale biological phenomena and neural network dynamics. Bojak’s research interests include understanding spontaneous neural oscillations, cortical activity modeling, and the integration of EEG/fMRI data. He has contributed to advancements in neural field theory and Bayesian uncertainty quantification. His studies on biological mistakes highlight adaptive mechanisms across biological systems. Related affiliations include collaborations with the School of Biological Sciences at the University of Reading. Recent publications emphasize theoretical biology, computational neuroscience, and interdisciplinary approaches to understanding neural systems. His work often addresses functional adaptation through error-driven mechanisms and explores the interplay between neural excitability and inhibition.
Chandan J Vaidya is a Professor in the Department of Psychology at Georgetown University, directing the Developmental Cognitive Neuroscience Laboratory (DCNL). His research focuses on cognitive neuroscience mechanisms underlying adaptive behaviors, particularly implicit learning, executive control, and their dysfunction in ADHD, ASD, and other developmental disorders. Using multidisciplinary methods including fMRI, behavioral testing, and genetic analysis, he investigates how dopamine systems, brain connectivity, and environmental factors influence cognitive processes. Primary appointment: Professor, College of Arts and Sciences - Department of Psychology Education: Ph.D. from Syracuse University Research interests include neurodevelopmental disorders, neuroimaging of cognitive control, and translational neuroscience. Recent work examines striatal connectivity changes in ADHD due to stimulant use, executive dysfunction subtypes in autism, and brain correlates of reward processing in obesity. Key findings highlight hyperconnectivity in ASD, dopamine genotype influences on executive function, and age-related changes in default mode networks. Ongoing studies explore transdiagnostic models of psychopathology and precision medicine approaches in neurodevelopmental disorders. Lab activities focus on translational research bridging basic neuroscience with clinical applications. Collaborations involve pediatric neurology, psychiatry, and computational modeling.
Yevgeni Berzak is an Assistant Professor at the Technion and a Research Affiliate at Mit BCS . He directs the Technion Language, Computation and Cognition (LaCC) Lab and leads the Cognitive Science Track in the Data Science and Engineering degree at the Technion. His academic background includes: PhD in Computer Science at Infolab, MIT CSAIL Postdoctoral research with Roger Levy at MIT CPL Lab Masters in Computational Linguistics at Universities of Saarland and Nancy Bachelors in Cognitive Science and Amirim Honors Program at Hebrew University of Jerusalem His research focuses on the intersection of Cognitive Science and Natural Language Processing (NLP) , studying human language acquisition and processing through computational modeling, linguistic theory, and neuroimaging. He develops datasets like OneStopQA and CELER , and explores how human gaze patterns can improve machine language understanding. Recent publications address topics such as: Eyetracking for language proficiency assessment Repetition effects in reading behavior Readability prediction via scrolling interactions Structured annotation schemes for reading comprehension The LaCC Lab under his leadership combines theoretical linguistics with machine learning to bridge human and artificial language processing.
Adam de la Zerda is an Associate Professor at Stanford University's Department of Structural Biology (School of Medicine) and Electrical Engineering (by courtesy). He develops advanced optical molecular imaging technologies combining nanoparticle contrast agents and adaptive OCT systems for cancer and ophthalmic disease research. Technion-Israel Institute of Technology (BSc, 2005) Stanford University (PhD, 2011) UC Berkeley (Postdoctoral Fellowship) Research Themes : Virtual biopsy using machine learning-enhanced OCT Gold nanorod-based molecular contrast agents Speckle noise reduction for cellular resolution Needle beam optical coherence tomography angiography His 15 most recent publications demonstrate technical innovations in: Metasurface optics for extended depth-of-field Spectral deconvolution of multiple contrast agents Speckle modulation for improved diagnostic clarity Noninvasive lymphatic system mapping Scientific Honors : Pew-Stewart Scholar for Cancer Research AFOSR Young Investigator NIH Early Independence Award Forbes 30 Under 30 (x2) Chan Zuckerberg BioHub Investigator His lab team has developed clinical prototypes including OcuBell Inc. 's ophthalmic imaging systems and Visby Medical 's diagnostic platforms. Current research spans from in vivo glycoprotein imaging to de novo biosensor development for real-time disease monitoring in awake animal models.
Gunnar Blohm is an Assistant Professor in the Department of Biomedical and Molecular Sciences at Queen's University, affiliated with the School of Medicine and Faculty of Health Sciences. His research focuses on sensorimotor neuroscience, particularly 3D sensorimotor control, eye-hand coordination, and computational modeling of neural processes. He holds a Ph.D. from Université Catholique de Louvain and has held postdoctoral positions at York University and his alma mater. Cross-appointed to the School of Computing, Department of Psychology, and Department of Mathematics and Statistics, he is also Vice-Director of the Connected Minds initiative. His research integrates behavioral experiments, brain imaging (MEG/EEG), and patient studies to understand how sensory information is transformed into goal-directed actions. Key areas include visuomotor transformations, multisensory integration, and Bayesian processes in neural computations. Blohm leads the Computational Sensorimotor Neuroscience Lab, emphasizing collaborative projects like Neuromatch Academy and contributions to open science initiatives. Affiliated with Queen's Centre for Neuroscience Studies and Ingenuity Labs, his work bridges computational approaches with clinical applications, aiming to develop frameworks for understanding brain dysfunction and clinical tools. His recent articles explore topics like saccade dynamics, pupil responses, and generative adversarial collaborations in scientific discourse.
