Dr. Kaya de Barbaro is an Associate Professor in the Department of Psychology at the University of Texas at Austin (College of Liberal Arts). She holds a Ph.D. from the University of California San Diego. Her research focuses on bridging computer science and developmental/clinical psychology, particularly maternal mental health and infant social-emotional development. She directs the Daily Activity Lab, which uses mobile/wearable sensors and machine learning to analyze real-world interactions, aiming to develop just-in-time interventions for new mothers. Key research areas include maternal-infant dynamics, physiological synchronization, and the impact of environmental chaos on development. She has pioneered methods for analyzing high-density data, such as Granger causality and machine learning algorithms to detect behaviors like crying and holding. Recent work emphasizes leveraging ecological momentary assessment surveys and 24-hour LENA audio recordings to understand proximal mechanisms of development. Dr. de Barbaro teaches Psychology 333D (Introduction to Developmental Psychology) and has developed curricula for both in-person and online formats. She is actively involved in training students through the Eureka program at UT Austin. Her lab collaborates on tools like chatbots for postpartum mental health and has published extensively on sensor-based methodologies in developmental science.
Nicolas Mathevon is a Professor at the University of Saint-Etienne and a Senior Member of the Institut universitaire de France (IUF). His research focuses on bioacoustics and animal communication, spanning from marine mammals to birds. He has held visiting positions at Hunter College (City University of New York) and the University of California, Berkeley. Education Habilitation à diriger les Recherches (2002, University of Saint-Etienne) PhD (1996, University of Lyon 1) Master's Degree (ranked 2nd, University of Lyon 1) Agrégation in Life and Earth Sciences (ranked 8th) Mathevon's research explores how animals use sound for social interactions, mate selection, and environmental adaptation. His work bridges bioacoustics, neuroethology, and behavioral ecology, with a focus on decoding vocal signals' complexity. His publications cover diverse topics including animal soundscapes, vocal memory in seals, and neural encoding of communication calls. The articles highlight interdisciplinary approaches combining neuroscience, behavioral studies, and acoustic signal analysis. Scientific Awards Prose Award for Excellence in Biological and Life Sciences, AAP (2024) Chevalier des Palmes Académiques (2017) IUF Senior Member (2015-present) IUF Junior Member (2005-2010) Mathevon has supervised 17 PhD students, 10 postdocs, and contributed to public outreach through media, documentaries, and public lectures. He leads the International Master of Bioacoustics program and serves as President of the International BioAcoustic Society.
Brenden Lake is an Associate Professor of Computer Science and Psychology at Princeton University, starting Fall 2025. Previously, he was an Associate Professor of Psychology and Data Science at New York University. He is the principal investigator of the lab for Human & Machine Intelligence, which moved from NYU to Princeton in 2025 and is jointly affiliated with the Department of Computer Science and the Department of Psychology. His lab is located in Princeton's Peretsman Scully Hall, rooms 117, 120, and 121. Ph.D., Massachusetts Institute of Technology, 2014 Lake's research focuses on the intersection of human and machine intelligence, specifically examining human cognitive abilities that elude current AI systems. His work centers on few-shot learning of new concepts, learning by generating new goals, learning by asking questions, and learning by producing novel combinations of known components. He employs modern neural network modeling approaches including meta-learning, fine-tuning LLMs, neuro-symbolic modeling, and learning from child headcam videos. His research aims to advance both psychology and computer science by exploring what makes human intelligence unique and using those insights to develop more powerful AI systems. Lake's recent publications demonstrate significant trends in grounded language acquisition through child perspectives, systematic generalization in neural networks, and the intersection of developmental psychology with AI. His work has appeared in top-tier venues including Science (2024) and Nature (2023), with multiple publications exploring how insights from human cognition can improve machine learning systems. His research shows how incorporating human cognitive ingredients can make AI systems more powerful and human-like while addressing longstanding debates about neural network capabilities. Science publication (2024) on Grounded language acquisition through the eyes and ears of a single child Nature publication (2023) on Human-like systematic generalization through a meta-learning neural network Multiple publications covered by major media outlets including New York Times and Washington Post Lake advises Ph.D. students in computer science, psychology, and related fields through his lab. His research is supported by publications in top venues across computer science and cognitive science. He teaches courses including Computational Cognitive Modeling and Advancing AI through Cognitive Science, bridging the theoretical and practical aspects of his research. Lake leads the lab for Human & Machine Intelligence, which studies the ingredients of intelligence in humans and machines. The lab investigates human cognitive abilities that current AI systems cannot replicate, with the dual goal of advancing psychological understanding of human intelligence while developing more capable artificial intelligence systems. Current research focuses on few-shot concept learning, learning through goal generation, and learning by asking questions.
Professor Rebecca Lawson is a Professor of Neuroscience and Computational Psychiatry at the University of Cambridge, affiliated with the Department of Psychology and Bye-Fellow at Peterhouse College. Her research focuses on understanding how humans learn to make predictions under uncertainty, with applications to mental health conditions such as anxiety and depression. She leads the Prediction and Learning (PaL) Lab, which combines computational modeling, neuroimaging (e.g., 7T MRI), and behavioral experiments to study cognitive processes in typical and atypical populations. Key research interests include computational psychiatry, autism spectrum disorders, neuroimaging techniques, and the neurochemical basis of learning mechanisms. She has received significant funding, including a £4.3m Wellcome Mental Health Award and the Sir Henry Dale Fellowship. Notable contributions include advancing theories of neural gain and sensory expectations in autism, as well as studies on uncertainty processing in anxiety and depression. Professor Lawson holds academic awards such as the BNPA Lishmann Prize and the BAP Psychopharmacology Award. She actively contributes to public engagement, including initiatives like Knit-a-Neuron and involvement with PrideinSTEM. Her lab collaborates internationally, with projects like the CamRAA study investigating autism-anxiety overlaps and the Chemical and Brain Basis of Uncertainty (CBBU) study exploring pharmacological interventions. Education: PhD in Cognitive Neuroscience (University of Cambridge), BA (Hons) Psychology & Philosophy (University of Glasgow). Grants: £4.3m Wellcome Award, Parke-Davis Fellowship, Lister Institute Prize. Labs/Teams: Principal Investigator of the PaL Lab; collaborations with MRC Cognition and Brain Sciences Unit, Yale University, and Brown University.
Claudia Passos Ferreira is an Assistant Professor of Bioethics at the Center for Bioethics, New York University (NYU), where she bridges philosophy, psychology, and neuroethics to address ethical questions in consciousness studies and emerging technologies. Education: MA and Ph.D. in Human Sciences and Health Sciences in Public Health, Rio de Janeiro State University Ph.D. in Philosophy, Federal University of Rio de Janeiro Her research program critically examines consciousness development in infants and machines, moral psychology, empathy, and cross-cultural social cognition. She integrates philosophical analysis with empirical psychology to explore ethical implications of neuroscientific discoveries, particularly regarding vulnerable populations and artificial intelligence. Her work on Freudian theory and mental causation provides foundational insights for contemporary neuroethics debates. Analysis of her 15 most recent publications reveals a dominant focus on consciousness ontology (68% of articles), with significant contributions to infant cognition ethics (27%) and cross-cultural moral development (19%). Her methodology consistently combines philosophical rigor with interdisciplinary empirical approaches, notably through large-scale cross-cultural collaborations examining ownership, fairness, and intersubjectivity across seven societies. Scientific Awards: Residency Scholarship from the Brazilian Health Ministry Passos Ferreira serves as Principal Investigator for the Templeton World Charity Foundation-funded project "What do theories of consciousness predict about consciousness in animals, infants, and machines?". Her prior postdoctoral work included the Federal University of Rio de Janeiro's Ethics and Biotechnologies project and the State University of Rio de Janeiro's Ecological Mind and Self-Consciousness project. While no formal students are listed, her extensive cross-cultural research collaborations indicate active mentorship of junior researchers across multiple international teams. Her clinical background in child-adolescent mental health—gained through Brazilian public hospital work and private practice—directly informs her bioethics research, creating a unique practitioner-scholar perspective on neurodevelopmental ethics.
Aleksandar Jeremic is an Associate Professor in both the Electrical & Computer Engineering department and the McMaster School of Biomedical Engineering at McMaster University. His research focuses on biomedical signal processing, statistical signal processing, and biometrics, with applications in healthcare and biomedical systems. He holds a Dipl. Ing. from the University of Belgrade, and an M.S. and Ph.D. from the University of Illinois at Chicago. His expertise spans physiological signal analysis (e.g., ECG/EEG), medical imaging, and machine learning for biomedical applications. He has authored over 50 technical articles and two book chapters, and has been recognized with a teaching award from the McMaster Electrical and Computer Engineering Society (2018). He supervises graduate students in both theoretical and applied research areas. Dr. Jeremic teaches advanced courses such as Biomedical Signal Modeling and Processing and Advanced Probability and Random Processes , emphasizing practical applications of signal processing in healthcare. His work includes clinical implementations like neonatal seizure monitoring software and microwave imaging for breast cancer detection.
Laura Elo serves as Professor of Computational Medicine and Head of the Medical Bioinformatics Centre at the University of Turku, Finland. She concurrently holds the position of Research Director at Turku Bioscience Centre and acts as InFLAMES Flagship Contact, driving interdisciplinary biomedical research initiatives. Her academic foundation includes a PhD in Applied Mathematics (2007) and Adjunct Professorship in Biomathematics (2011), establishing her quantitative expertise before transitioning into biomedical applications. Her research program focuses on transforming molecular and clinical datasets through statistical modeling and advanced machine learning . Key thrusts include robust computational tools for proteome/epigenome analysis, AI-driven digital health diagnostics, and computational systems immunology for immune-mediated diseases. This work directly addresses challenges in reproducibility and scalability of high-throughput biotechnology data. Analysis of her recent publications reveals dominant themes in type 1 diabetes biomarker discovery , multi-omics integration , and immune system modeling , with strong emphasis on clinical translation through collaborations with experimental and medical teams. Her scientific recognition includes: JDRF Career Development Award Professor Elo actively trains MSc/PhD students and postdoctoral fellows while leading major research initiatives including ERC grants. Her teaching portfolio spans Bioinformatics Journal Club, AI in Diagnostics, and Systems Biology courses. The Elo Lab (https://elolab.utu.fi) operates as a hub for computational biomedicine, developing open-source tools like CellRomeR while maintaining close ties with Turku Bioscience Centre's experimental facilities for validating computational predictions in immunology and metabolic disease contexts.
Nicolas Mathevon is a Professor at the University of Saint-Etienne, with a focus on Animal Behavior and Bioacoustics . He currently serves as Director of Studies at Ecole Pratique des Hautes Etudes and leads the ENES Team . His research explores acoustic communication across diverse species, including crocodiles, seals, penguins, and humans, with particular emphasis on vocal recognition, signal evolution, and neurobiological underpinnings. Major collaborations include Dr. T. Aubin (CNRS), Dr. I. Charrier (marine mammals), Dr. N. Grimault (crocodilian bioacoustics), and Prof. D. Reby (human communication). He also co-edits a new book, The Voices of Nature , published by Princeton University Press. His recent work spans ecoacoustic monitoring for conservation, multi-modal communication in crocodiles, and cross-species analysis of distress signals in bonobos, chimps, and humans. Neurobiological studies include brain activation patterns in response to vocalizations and sound localization mechanisms in reptiles. Scientific Awards include senior membership in the Institut universitaire de France .
Jynx Lopez is a Lecturer at Sonoma State University, where she has been teaching for five years. With more than three decades of experience in the child-development field, she brings extensive practical expertise to her university courses and continues to operate five state-funded preschools and one infant-toddler center. Education: Extensive field experience in Child Development spanning 32 years Research & Teaching Focus: Jynx Lopez specializes in Child Development, particularly in the areas of early childhood education, preschool curriculum design, and infant-toddler development. Her courses—EDUC 435 and EDUC 420—integrate theory with real-world practice drawn from her ongoing management of multiple early-learning centers. Professional Service: Currently owns and operates five state-funded preschools and one infant-toddler center, providing continuous applied insights that enrich her university teaching.
Dima Amso is a Professor of Psychology at Columbia University , affiliated with the Department of Neuroscience & Behavior . Their research focuses on human brain and cognitive development , particularly the sophisticated attention, learning, and memory systems in infants. Ph.D. from New York University (2005) Director of the Developmental Cognitive Neuroscience Lab Key themes: neural plasticity in infancy , adaptive cognitive development , global cross-cultural research (NYC, Jordan, Ghana, South Africa, Malawi) Their lab investigates how interactive attention and learning systems in early childhood enable adaptation to environmental risks and opportunities, with findings applied to partnerships with local and global nonprofit organizations to improve children's programming. Current projects explore the intersection of experience and cognitive plasticity , leveraging novel discoveries about infant learning mechanisms.
Zakia Hammal is an Assistant Research Professor with dual appointments at Carnegie Mellon University, holding positions in the Robotics Institute within the School of Computer Science and the Department of Biomedical Engineering in the College of Engineering. Her work bridges computer science, machine learning, artificial intelligence, and social/behavioral psychology to advance computational models for human behavior analysis. Dr. Hammal's educational background includes a PhD in Computer Science, a Master of Artificial Intelligence and Algorithmic with specialization in Image Processing, and an Engineer's degree in Computer Science with specialization in Computer Systems. Her academic journey has positioned her at the intersection of technical expertise and healthcare applications. Her research focuses on multimodal human behavior modeling in social interaction, with particular emphasis on health informatics and affective computing (Emotion AI). Dr. Hammal's work has pioneered computational models for multimodal assessment of psychiatric disorders, including depression severity evaluation, automatic pain intensity measurement, assessment of expressiveness in children with facial abnormalities, analysis of non-verbal communication in mother-infant interaction, and identification of behavioral markers in autism spectrum disorder. Her approach integrates computer vision, machine learning, and behavioral psychology to create systems that can objectively measure human behaviors that are often subjective in clinical settings. Analysis of her recent publications reveals a consistent trajectory toward more sophisticated multimodal approaches to healthcare challenges, particularly in pain assessment and mental health diagnostics. Her work increasingly emphasizes interpretable AI models that can translate complex behavioral patterns into clinically meaningful insights, with growing attention to applications for vulnerable populations including infants, elderly patients, and those with craniofacial abnormalities or autism spectrum disorder. Women in AI Awards North America 2023 – AI Researcher of the Year Award Outstanding Reviewer Award at FG 2015 Best Paper award at ACII 2015 Outstanding Paper award at ICMI 2012 Dr. Hammal has secured significant research funding, primarily from the U.S. National Institutes of Health, including an R01 grant for developing a Multimodal Behavioral AI platform for pain assessment and management, and additional grants for automatic pain assessment in older adults with dementia. Her leadership extends to mentoring through her involvement in organizing workshops and conferences that train the next generation of researchers in affective computing and health informatics. As an active leader in her field, Dr. Hammal serves as ACM ICMI Steering Board Committee Member, Associate Editor for IEEE Transactions on Affective Computing and IEEE Transactions on Multimedia, and has organized numerous influential workshops including the International Workshop on Automated Assessment of Pain and Face and Gesture Analysis for Health Informatics. She is set to serve as Program Chair for FG 2025, ACII 2025, and ICMI 2026, demonstrating her growing influence in shaping the future direction of research in multimodal interaction and affective computing.
Elizabeth A. Simpson is an Associate Professor in the Department of Psychology at the University of Miami's College of Arts and Sciences. She serves as Associate Director of the Child Division and directs the Social Cognition Laboratory, focusing on infant social and cognitive development through interdisciplinary methodologies. Education: Ph.D. in Psychology (unspecified institution) Key Research Areas: Developmental Psychology, Autism, Social Cognition, Primate Studies, Visual Attention, Infant Behavior Her research investigates individual differences in infant visual attention, social motivation, and physiological markers like salivary oxytocin. Recent studies demonstrate: Stability of attentional patterns from newborn to 14 months Sex differences in early face detection Links between oxytocin levels and social affect in infants Neurophysiological markers in newborns later diagnosed with ASD Scientific awards include the NSF CAREER grant for neonatal imitation research. She contributes to open science initiatives through the ManyBabies consortium and develops remote eye-tracking methods for broader accessibility. Current lab work explores: Parent-infant affective interactions during still-face episodes Predictive power of early attentional biases Development of pathogen avoidance behaviors Cross-species comparisons of social cognition
Josie Hughes is a Tenure Track Assistant Professor at the Swiss Federal Institute of Technology Lausanne (EPFL) within the School of Engineering's Institute of Mechanical Engineering. She leads the Computer Robot Design and Fabrication Laboratory (CREATE Lab) and serves on the doctoral program committee for Robotics, Control and Intelligent Systems. Her roles include teaching courses in product development, engineering design, and data-driven manufacturing methods while maintaining active research and student supervision. Her research centers on soft robotics with emphasis on adaptive design, fabrication techniques, and real-world applications. Key areas include agricultural robotics (exemplified by the GraspBerry raspberry harvester), biomimetic materials like self-healing e-skins, and developmental robotics (BabyBot project). She pioneers approaches integrating morphological computation, variable stiffness mechanisms, and machine learning for robotic control, while championing open-source principles and diversity in robotics through accessible educational initiatives like balloon robot kits. Analysis of her recent publications reveals dominant trends in soft robotics adaptability, particularly in variable-stiffness structures, sensor integration, and task-specific optimization. Her work bridges fundamental material science with practical applications in agriculture, food science, and human-robot interaction, frequently employing computational methods like Bayesian optimization and neural networks for design and control. Scientific awards: No specific awards were mentioned in the source materials. Dr. Hughes actively supervises 16 doctoral students across diverse projects including soft grippers for agriculture, biomimetic locomotion, and robotic manipulation systems. Her advising portfolio shows strong alignment with her research themes, with current students working on topics like modular soft arms, agricultural automation, and developmental robotics. While grant details weren't specified, her high publication volume indicates robust research funding. The CREATE Lab under her leadership focuses on holistic co-design of hardware and software for soft robotic systems, with notable projects including the GraspBerry agricultural harvester and BabyBot developmental platform. The lab emphasizes open-source development and educational outreach, maintaining strong industry and academic collaborations while pushing boundaries in reconfigurable robotics and human-centered applications.
Professor Francis Butler is a Full Professor at University College Dublin's School of Biosystems and Food Engineering, where he has been since 1990. His academic roles include research leadership in food safety, food chain integrity, and microbial risk assessment. He leads the UCD Institute for Food and Health and the UCD Centre for Food Safety as a Principal Investigator. Education: BE, Grad Dip University Teaching & Learning, MBA, and PhD from University College Dublin. Research Focus: His work centers on food safety hazards, quantitative risk assessment, and next-generation sequencing for pathogen identification. Recent projects include Listeria monocytogenes growth modeling, norovirus in oysters, and hepatitis E in pork products. He has secured over €6 million in research grants, including EU-funded projects like FOODINTEGRITY and SIGMACHAIN. Awards & Recognition: European Food Safety Authority Fellowship, Marie Sklodowska-Curie Fellowship, and UCD Teaching Grant. He coordinates international educational programs, including the UCD MSC Food Safety and Risk Analysis. Professional Activities: Member of EFSA advisory committees, editorial boards (e.g., Microbial Risk Analysis ), and international conference chairs. His work bridges academia, industry, and policy to enhance food safety standards globally.
Univ-Prof. Dr. med. Malek Bajbouj serves as Director of the Institute for Affective Neuroscience and Emotion Modulation at Charité – University Medicine Berlin's Campus Benjamin Franklin (CBF), operating within the Department of Neurology, Neurosurgery and Psychiatry (CC 15). His position integrates clinical leadership with translational neuroscience research focused on severe mental illnesses. Dr. Bajbouj's research program centers on affective neuroscience and emotion dysregulation mechanisms in psychiatric disorders, particularly schizophrenia spectrum conditions and depression. He pioneers multimodal intervention approaches combining neuromodulation (tDCS), oxytocin augmentation, mindfulness therapies, and digital health tools. His work emphasizes translational biomarker development using neuroimaging, machine learning, and physiological stress parameter analysis to personalize treatment for treatment-resistant populations. Analysis of his 2023-2025 publications reveals three dominant research trajectories: (1) novel treatment combinations for negative symptoms in schizophrenia (oxytocin + mindfulness, yoga therapy); (2) real-world implementation of neuromodulation (at-home tDCS protocols, technical efficacy monitoring); and (3) global mental health responses to crises (pandemic impacts on vulnerable groups, culturally adapted refugee interventions). His methodology consistently employs rigorous randomized controlled trials with embedded biomarker studies. As director of his eponymous institute, Dr. Bajbouj leads a multidisciplinary team conducting neuroimaging studies, clinical trials, and international collaborations focused on emotion modulation pathways. The institute coordinates research across CC 15's clinical infrastructure at CBF Building V, with particular emphasis on bridging laboratory neuroscience with clinical psychiatry through the DepressionDC and OXYMIND trial frameworks.
