Peter N. Belhumeur is a Professor in the Department of Computer Science at Columbia University and Director of the Laboratory for the Study of Visual Appearance (VAP LAB). He holds a Sc.B. from Brown University and a Ph.D. from Harvard University, followed by a postdoctoral fellowship at the University of Cambridge. His career includes roles at Yale University before joining Columbia in 2002. Education: Brown University (Sc.B., 1985), Harvard University (Ph.D., 1993) Postdoc: Isaac Newton Institute, University of Cambridge (1994) His research focuses on computer vision and machine learning, with applications in biodiversity and mobile technology. Notable projects include the Leafsnap, Birdsnap, and Dogsnap apps – pioneering species/breed identification tools using machine learning. He has received awards such as the PECASE, Helmholtz Prize, and EO Wilson Biodiversity Technology Pioneer Award. His work bridges academia and industry, demonstrated by collaborations with Dropbox and contributions to consumer-facing AI applications. The VAP LAB explores visual appearance modeling and computational photography.
Professor Dirk Bernhardt-Walther is an academic at the University of Toronto, serving as Program Director of the Cognitive Science Program and Department of Psychology . He investigates neural and computational mechanisms underlying high-level sensory perception, focusing on real-world scenes, mid-level vision, and visual aesthetics. Education: PhD in Computation and Neural Systems (Caltech, 2006), M.Phil (University of Cambridge) Research Focus: His lab employs fMRI, MEG, EEG , and GAN-generated stimuli to study scene categorization, perceptual organization, and aesthetic processing. Recent work explores curvature perception, emotion representation in scenes, and neural dissociations between computational and subjective visual metrics. Laboratory Members: The Bernhardt-Walther Lab includes PhD students like Gaeun Son (scene perception), Charlotte Leferink (scene representation), and Dela Farzanfar (aesthetic processing), alongside postdocs and collaborators. Advising: Supervises graduate students in projects combining computational modeling, psychophysics, and neuroimaging, particularly those with backgrounds in computer science or cognitive neuroscience.
Cristina Baus Marquez is a Research Fellow at the University of Barcelona's Faculty of Psychology, affiliated with the Department of Cognition, Development, and Educational Psychology. She holds a Ramon y Cajal Research Fellowship (2020–2025) and leads research in the Brain Dynamics and Structure of Human Cognition (BraCo) group. Her work focuses on cognitive neuroscience, bilingualism, and language processing, with a particular emphasis on electrophysiological and behavioral studies of language production, perception, and social cognition. Education: Bachelor's Degree (Llicenciatura) in Psychology, University of Barcelona (2003) PhD in Cognitive Neuroscience and Specific Educational Needs, Universidad de La Laguna (2010) Research Interests include the neural mechanisms underlying bilingual speech production, cross-modal language interactions, and how linguistic experience shapes perception of faces and voices. She employs EEG/ERP techniques to study self-monitoring processes in bilinguals and investigates the role of iconicity in sign language production. Key Projects: Ramón y Cajal Fellowship (2020–2025): Investigates verbal interactions and learning mechanisms Fundación BIAL Grant (2017–2019): Explored electrophysiology of bimodal bilingualism AGAUR Grant (2018–2020): Studied verbal interactions' cognitive mechanisms Labs/Teams: Active member of the BraCo research group, collaborating internationally on multilingualism and cognitive neuroscience projects.
Prof. Helen Blank is a Professor leading the Multisensory Perception Group and the Prediction in Communication Lab at the Institute for Systems Neuroscience, University Medical Center Hamburg-Eppendorf. Her work focuses on understanding how sensory information is integrated and predicted in contexts like speech perception and face recognition. She holds a Marie Curie Fellowship for her research on prior information's role in human communication. Fluent in German, English, and French, she contributes to experimental medicine and systems neuroscience. Her research spans predictive coding, neuroimaging, and clinical applications in Parkinson’s and developmental disorders. Education: Not explicitly stated in text, inferred as advanced degrees in neuroscience or related fields. Her research interests emphasize multisensory integration, predictive processing in speech and vision, and the neural bases of perception. Recent articles explore topics such as pupil responses to auditory surprise, face expectation hierarchies, and audio-visual speech processing. Awards include the Marie Curie Fellowship supporting her predictive communication work. She leads interdisciplinary teams within the Center for Experimental Medicine, advancing knowledge on perceptual mechanisms and their clinical implications.
Jackson G. Lu is the General Motors Associate Professor of Management and an Associate Professor of Work and Organization Studies at the MIT Sloan School of Management. His scholarly work bridges cultural psychology with organizational behavior, examining how cultural differences manifest in AI adoption, creativity, and leadership dynamics. He serves as senior editor for Organization Science and Management and Organization Review , and associate editor for Journal of Personality and Social Psychology . Dr. Lu earned his PhD from Columbia Business School in 2018 and received tenure at MIT in 2023. His research has been published in top-tier journals across psychology, management, and general science domains, including Nature Human Behaviour , Psychological Bulletin , and Annual Review of Psychology . His work has garnered over 300 media mentions globally. Cross-Cultural Psychology AI Ethics and Creativity Leadership Emergence Stereotype Research Technological Adoption Workplace Diversity Recent research focuses on cultural tendencies in generative AI , AI's impact on creativity , and structural barriers faced by Asian professionals . He has received numerous accolades from professional societies including the Wegner Theoretical Innovation Prize and multiple Best Senior Editor Awards. 40 Best Business School Professors Under 40 Thinkers50 Radar Class of 2021 Academy of Management Award Outstanding Dissertation Award (2019) SAGE Early Career Award Dr. Lu teaches through MIT Sloan Executive Education's 5-day program Leading the AI-Driven Organization , and his findings have been featured in The New York Times , BBC , and The Economist . His editorial leadership spans multiple journals, reflecting his influence across academic networks.
Dr. Julie Markant is an Associate Professor in the Department of Psychology at Tulane University and a Faculty Associate in the Tulane Brain Institute. Her research focuses on the interplay between selective attention and learning in infants and young children, emphasizing developmental and neurobehavioral perspectives. She uses behavioral, eye-tracking, genetic, MRI, and fNIRS methods to explore how attention control influences learning efficacy and vice versa. Education: Ph.D., 2010, University of Minnesota Her research interests include developmental attention mechanisms, perceptual learning, and how biological and contextual factors shape cognitive outcomes. Key themes involve understanding how infants and children selectively attend to information and how this attention drives learning processes. Recent work explores caregiver influence on attention, prenatal factors affecting infant attention, and the role of competing information in school-aged learning. Dr. Markant leads the Learning and Brain Development Lab , which investigates cognitive and neural mechanisms underlying attention and learning. She is actively recruiting graduate students from Tulane’s Psychology and Neuroscience Ph.D. programs. Her publications reflect a focus on attention biases, developmental learning dynamics, and methodological innovations like remote infant studies. Awards and honors are not explicitly listed in the provided text.
Professor Sarah Bate is an academic at Bournemouth University, currently serving as Interim Associate Pro Vice-Chancellor (Research and Knowledge Exchange). She leads the Centre for Face Processing Disorders and authored the seminal book *Face Recognition and its Disorders*. Her work focuses on face-processing impairments in developmental and acquired prosopagnosia (face blindness), employing eye-movement technology to explore theoretical and remediation strategies. Education: Completed a BSc (2004), MSc (2005), and PhD (2009) in Psychology at the University of Exeter, followed by postdoctoral research before joining Bournemouth in 2010. Research Interests: Prosopagnosia sub-classification, face recognition disorders, neuropsychological assessment tools, and applications in forensic and clinical settings. Her studies span cognitive mechanisms, rehabilitation techniques, and individual differences in face perception. Recent articles emphasize taxometric analysis of prosopagnosia subtypes, familial transmission patterns, and the role of birthweight in face recognition. Collaborations include work on oxytocin’s effects and the development of diagnostic tools like the Oxford Face Matching Test. Grants and Affiliations: Active in grants such as the *Face Blindness Awareness Campaign* and affiliated with the British Psychological Society and Experimental Psychology Society. Supervises PhD students like Anna Bobak, focusing on neuropsychological and developmental aspects of face recognition.
Dr. Benjamin de Haas is a vision scientist and faculty member at Justus Liebig University Giessen , Germany, within the Department of Psychology and Sports Science . He currently leads the ERC-funded Indivisual project and co-leads project C9 Factors influencing categorical face processing within the Collaborative Research Centre CRC/TRR 135. He is also a principal investigator in the NeurOscientific Workflow Assistance (NOWA) infrastructure project, dedicated to open, reproducible neuroscience. Research Focus Dr. de Haas pursues two intertwined questions: How do early and late stages of visual processing interact—from the initial registration of slanted edges to the recognition of faces? How and why do our perceptions differ from one person to the next? To answer these questions his group combines psychophysics, high-resolution eye-tracking, functional and quantitative MRI, and computational modelling, with a strong emphasis on face perception, individual differences, and naturalistic viewing conditions. Publications Overview Across more than 20 publications since 2016, Dr. de Haas has advanced understanding of individual differences in face processing, gaze control, and visual salience. His work repeatedly appears in Journal of Vision , Nature Communications , PNAS , and NeuroImage , highlighting a sustained focus on eye-movement behaviour, cortical representations of faces and scenes, and methodological best practices in neuroimaging. Current Supervision & Team Dr. de Haas currently supervises two PhD students: Elaheh Akbarifathkouhi Hilal Nizamoglu Together with Dr. Katharina Dobs (co-project leader) and affiliated post-docs and research technicians, the group forms the Indivisual laboratory at Giessen. Contact & Resources Email: Benjamin.de-Haas@psychol.uni-giessen.de Department of Psychology and Sports Science Otto-Behaghel-Str. 10F, 35394 Gießen, Germany
Olivia Cheung is an Assistant Professor of Psychology and Global Network Assistant Professor at New York University Abu Dhabi (NYUAD), affiliated with the Division of Science and the Department of Psychology. She leads the Objects and Knowledge Laboratory (OAK Lab), which is also associated with the Center for Brain and Health at NYUAD. Education: BSSc, Chinese University of Hong Kong PhD, Vanderbilt University Postdoctoral Training: Harvard Medical School, CIMeC (Trento, Italy), Harvard University Her research focuses on cognitive neuroscience and visual cognition, particularly how experience and learning shape perception. She investigates how visual and conceptual knowledge interact to influence representations of objects, faces, words, musical notations, and scenes. Her lab employs behavioral experiments, functional magnetic resonance imaging (fMRI), and computational modeling to explore perceptual expertise and category selectivity in the brain. Her recent publications (2022–2024) reveal a consistent focus on high-level vision, with studies on holistic face and word processing, neural and computational models of category recognition, ensemble perception of animacy, and social judgments from faces (e.g., election prediction). These works, presented at Vision Sciences Society (VSS), demonstrate interdisciplinary methods and collaborations with students and international researchers. Olivia Cheung teaches courses such as Capstone Projects in Computer Science and Psychology, and Concepts and Categories: How We Structure the World , reflecting her interdisciplinary approach. She mentors undergraduate researchers, many of whom have co-authored conference posters. Her lab, the OAK Lab, fosters research on the intersection of perception, knowledge, and expertise.
Andrew Todd is an Associate Professor in the Department of Psychology at the University of California, Davis, where he has been a faculty member since 2017. He is affiliated with the Social Inference Lab and conducts research in social and personality psychology, focusing on perspective taking, mental state reasoning, and intergroup bias. He serves as an associate editor for the Journal of Personality and Social Psychology . Education: Ph.D. in Social Psychology, Northwestern University, 2009 M.S. in Social Psychology, Northwestern University, 2006 B.A. in Psychology, Michigan State University, 2003 Dr. Todd's research investigates the cognitive and emotional processes underlying social inference, empathy, and stereotyping. His work explores how people understand others' mental states and how such reasoning is influenced by emotions, group membership, and situational factors. He is particularly interested in how these processes contribute to intergroup bias and diversity challenges. His recent publications reveal a strong focus on egocentric biases in social cognition, perspective taking, and the cognitive mechanisms of prejudice. These works span high-impact journals in psychology and cognition, demonstrating a consistent trajectory in understanding the subtle dynamics of social judgment and intergroup perception. Scientific Awards and Honors: SAGE Young Scholar Award, Foundation for Personality and Social Psychology Dissertation Award (2nd prize), Society for the Psychological Study of Social Issues Elected Fellow, Association for Psychological Science Elected Fellow, Society of Experimental Social Psychology Elected Fellow, Society for Personality and Social Psychology Dr. Todd has received research funding from the National Science Foundation and the UK Economic & Social Research Council. He mentors students through his Social Inference Lab and teaches courses in social cognition and attitudes. His prior teaching includes research methods and the unconscious mind. The Social Inference Lab at UC Davis, led by Dr. Todd, investigates perspective taking, mental-state reasoning, social categorization, and the roots of stereotyping and discrimination. The lab combines behavioral experiments, cognitive modeling, and theoretical analysis to understand how people form impressions of others and navigate socially diverse environments.
Mohit Singhal is an Assistant Teaching Professor at Northeastern University in Boston specializing in Cybersecurity and Privacy within the Teaching Faculty. His work bridges computational systems and social dynamics in digital environments. His primary research interests include: Cybersecurity Privacy Social Media Analysis Content Moderation Fairness in AI Malware Analysis He investigates algorithmic fairness in business ranking systems, censorship circumvention technologies, causal effects of content moderation policies, and cybersecurity misinformation propagation across platforms like Yelp, Parler, and Twitter. Publication trends from 2019-2025 reveal an evolution from malware analysis toward social-media-centric research, with increasing focus on fairness evaluation frameworks, toxicity measurement in online conversations, and adversarial robustness of privacy tools. Recent work integrates causal inference methods with computational social science approaches. No scientific awards were mentioned in available sources. As a Teaching Professor, Singhal focuses on pedagogy and curriculum development in cybersecurity education. While specific grant details and student mentorship information are not publicly documented in the provided materials, his role involves training students in emerging challenges at the intersection of technology and society.
Looi van Kessel serves as Assistant Professor in Literary Studies and Gender Studies at Leiden University, affiliated with the Leiden University Centre for the Arts in Society (LUCAS) and the Department of Film and Literary Studies. He coordinates the minor program 'Gender and Sexuality in Society and Culture' and chairs both the Curriculum Committee and the Leiden University LGBT+ Network, where he advocates for equal treatment of LGBTQIA+ staff and students. Van Kessel completed his PhD in 2019 with a dissertation examining melodrama and sexual identity in the works of American author James Purdy. His academic trajectory demonstrates a commitment to exploring literature's role in shaping and challenging societal understandings of gender and sexuality across different historical periods. His research spans three interconnected domains: LGBTQIA+ literary analysis focusing on authors James Purdy and Louis Couperus; AIDS epidemic literature examining how writing from this period functions as pedagogy for future generations; and contemporary drag culture analysis, particularly in response to rising anti-drag sentiment across Europe. His work consistently explores how literature creates space for alternative sexual identities and challenges rigid categorizations of gender and sexuality. As an educator committed to inclusive practices, Van Kessel researches democratizing pedagogies that recognize diverse student backgrounds and learning needs. He co-leads a project assessing the Film and Literary Studies curriculum at Leiden University to develop more inclusive teaching approaches that address not just course materials but also workload, teaching methods, and assessment formats. Van Kessel holds significant editorial positions as co-chief editor for Tijdschrift voor Genderstudies (Dutch Journal for Gender Studies) and editorial board member for Arabesken, the journal of the Louis Couperus Society. His public engagement includes regular contributions to media discussions on LGBTQIA+ issues, addressing topics from substance abuse in queer communities to the political challenges facing drag performers. His recent work demonstrates how academic research can directly inform contemporary social debates and policy discussions regarding LGBTQIA+ rights and representation.
Aleksandra Slavković is a Professor of Statistics and Associate Dean for Graduate Education at Pennsylvania State University's Eberly College of Science. She holds a PhD in Statistics from Carnegie Mellon University (2004) and has held academic roles since 2004, including appointments at the Institute for Computational and Data Sciences and Penn State College of Medicine. Her research focuses on statistical data privacy, differential privacy, algebraic statistics, and applications in social and health sciences. She has authored over 50 peer-reviewed publications and serves on editorial boards of top journals like Journal of Privacy and Confidentiality and Annals of Applied Statistics . Slavković has received major honors including Fellowships from the Institute of Mathematical Statistics (2021) and American Statistical Association (2018). She leads initiatives to enhance graduate education, including the Science Achievement Graduate Fellows Program, and actively promotes diversity in STEM through her leadership roles. Her recent work emphasizes privacy-preserving techniques for genomic, healthcare, and network data, with contributions to synthetic data generation and secure multiparty computation protocols. Her academic service includes chairing ASA committees and advising at the National Academy of Sciences. She maintains collaborative ties with institutions like Cornell University and UC Berkeley through visiting scholar programs, and her research bridges statistics, computer science, and applied mathematics.
Ulrich Schroeders is a Professor of Psychological Diagnostics at the University of Kassel, where he has been employed since October 2017. His work focuses on developing and validating psychological assessment tools, with particular expertise in cognitive diagnostics and educational measurement. He teaches various programs for approximately 500 students annually and serves as a supervisor for teacher training students preparing for their oral state examinations in Pedagogy/Psychology. Dr. Schroeders earned his PhD from Humboldt University of Berlin in 2010 with a dissertation titled "Measurement of Cognitive Abilities Using Modern Technologies: Artifacts, Equivalence, and New Constructs." Prior to that, he completed his Diploma in Psychology at Julius-Maximilians-University Würzburg in 2004 with a thesis on diagnosing dyscalculia in first-grade students. His research spans several key areas in psychological assessment. He specializes in technology-based competency diagnostics, developing innovative methods for measuring cognitive abilities and school competencies. A significant portion of his work involves applying Machine Learning and metaheuristics to psychometric problems, particularly in structural equation modeling. His methodological expertise includes advancing techniques in Local Structural Equation Modeling (LSEM) and Meta-Analytic Structural Equation Modeling (MASEM), with applications across educational and clinical psychology contexts. Analysis of Dr. Schroeders' recent publications reveals a strong focus on computational approaches to psychological assessment. His work frequently employs optimization algorithms like Ant Colony Optimization and Bee Swarm Optimization to address challenges in test construction and validation. There's a clear trajectory toward game-based and technology-enhanced assessment methods, as seen in studies using Mastermind and Wordle as assessment tools. His research also demonstrates growing interest in applying machine learning to predict behavioral outcomes, including juvenile delinquency, suicide risk, and psychotherapy outcomes. Dr. Schroeders has secured significant research funding, including projects funded by the German Research Foundation (DFG) and the Hector Foundation. His current projects include "Facing the Replication Crisis in Machine Learning Modeling" (2025-2027) and "PINGUIN: Potenzialidentifikation IN der GrUndschule" (2024-2027), which focuses on identifying elementary students' initial competencies. He leads the development of the BEFKI assessment system (Berliner Test zur Erfassung fluider und kristalliner Intelligenz), which includes versions for different age groups (5-7, 8-10, and 11+). His methodological toolbox includes specialized approaches for test construction and validation, particularly focusing on optimization algorithms applied to psychological measurement problems.
Professor Keiko Honda is a distinguished faculty member at Waseda University's Faculty of Education and Integrated Arts and Sciences, School of Education. With a Doctorate in Education from Teachers College, Columbia University, she has established herself as a leading expert in educational psychology, particularly focusing on developmental disorders, anger management, crisis intervention, and school counseling. Her educational background includes: Graduate School, Division of Psychology, Counseling Psychology at Teachers College, Columbia University (1994) Faculty of Liberal Arts, Social Study at International Christian University Professor Honda's research focuses on understanding and addressing the challenges faced by children with developmental disorders, particularly in emotional regulation and social interaction. Her work has led to the development of specialized intervention programs including anger management techniques for children with borderline intelligence and social skills training for children with special needs. She has pioneered approaches that combine clinical psychology with educational practices to create effective support systems in school environments. Her research has identified key developmental stages in children's needs and self-control, resulting in categorized intervention strategies. Her work has been particularly influential in developing practical tools for educators and counselors working with children who have difficulties in social interaction and emotional regulation, including VRICS (Violence Risk Check Sheet) and specialized anger management programs implemented in schools and correctional facilities. Professor Honda is actively involved in professional organizations including: Japan Psychological Association Japan School Psychologist Association Japanese Association of Criminal Psychology Japanese Association of Correction Education Japanese Association of Educational Psychology Japanese Association of Learning Disorder She supervises graduate students across multiple departments including the Graduate School of Education and the Graduate School of Letters, Arts and Sciences, teaching diverse courses related to school psychology, educational psychology, and brain-based learning in inclusive classrooms. Her current research projects focus on developing comprehensive systems for inclusive education and prosocial problem-solving strategies for children with developmental disabilities.
