Dr. Aniket Bera is an Associate Professor in Computer Science at Purdue University and holds an Adjunct Associate Professor role at the University of Maryland at College Park (UMIACS). He directs the IDEAS Lab at Purdue and previously served as a Research Assistant Professor at UNC Chapel Hill. His research focuses on Affective Computing, Computer Graphics (AR/VR), AI & Robotics, Social Robotics, and medical AI applications for mental health diagnostics. Affiliations: Purdue University (Primary), University of Maryland (Adjunct), UMIACS Career: Joined Purdue in 2017, extensive industry collaborations with Disney Research, Intel, and C-DAC Research Interests: Affective Computing: Emotion perception via gait analysis, speech, and facial/body expressions AR/VR: Redirected walking, virtual environments, and human motion modeling Medical AI: AI-driven mental health detection systems (e.g., VidSole dataset) in collaboration with medical schools Key Contributions: Developed Project Dost (mental health initiative) Received 2020 Brain & Behavior Seed Grant ($X) for emotion-gait research Authored 65+ papers (1,800+ citations) with awards at IEEE VR 2021 Funding & Leadership: Serves as Senior Editor for IEEE RA-L (Planning/Simulation) Conference Chair for ACM SIGGRAPH MIG 2022 Labs/Teams: IDEAS Lab (Purdue), UMD GAMMA Group
Mark d'Inverno is a Professor in the Department of Computing at Goldsmiths, University of London, where he has established himself as a leading researcher at the intersection of artificial intelligence, multi-agent systems, and creative applications. His academic journey began with foundational work in formal methods and agent-based systems, culminating in his 1998 PhD thesis 'Agents, Agency and Autonomy: A Formal Computational Model' from University College London, and has evolved toward practical applications in music technology and ethical AI systems. Professor d'Inverno's research interests span multiple interconnected domains, with a particular focus on computational creativity, multi-agent systems, and the application of AI in musical contexts. His work explores how artificial intelligence can enhance creative processes, particularly in music composition and performance, while maintaining ethical considerations in social AI systems. He has made significant contributions to understanding how agents can interact meaningfully in social contexts, how ethical frameworks can be embedded in online systems, and how technology can support creative learning experiences. His recent scholarly output demonstrates a clear trajectory toward applied research with social impact, as evidenced by his 2021-2024 publications which increasingly address ethical considerations in AI, human-AI collaboration in creative domains, and educational applications of technology. These works reveal a researcher deeply engaged with both theoretical foundations and practical implementations, bridging the gap between abstract computational models and real-world creative and educational applications. Professor d'Inverno maintains an extensive collaborative network, frequently working with Matthew Yee-King on music technology applications, with Pablo Noriega on ethical AI frameworks, and with Jon McCormack on computational creativity. His research has been supported through various projects that connect theoretical computer science with practical creative applications, particularly in the development of systems that facilitate human-AI creative collaboration.
Institute for Bioengineering of Catalonia (IBEC)Spain
Prof. Raimon Jané Campos is a leading figure in biomedical signal processing at the Universitat Politècnica de Catalunya (UPC) and Universitat de Barcelona (UB). As co-director of UPC's Biomedical Signal and System Group (CREB) and coordinator of the Biomedical Engineering PhD Programme, he bridges engineering and clinical applications. His work focuses on respiratory and sleep disorder diagnostics, with significant contributions to COPD and sleep apnea monitoring through wearable devices and machine learning. PhD in Biomedical Engineering (UPC, 1989) Visiting researcher at Université de Nice-Sophia Antipolis Vice-president of Spanish Society of Biomedical Engineering Research spans respiratory mechanics , sleep-disordered breathing , acoustic biomarkers , bioimpedance , and machine learning in biomedical contexts . His 2025 work on microcalorimetric pathogen classification and 2024 spiking neural networks for apnea detection demonstrate cutting-edge integration of computational methods with physiological monitoring. Articles from 2017-2024 reveal consistent focus on non-invasive diagnostics , cardiorespiratory synchronization , and smartphone-based health solutions . Awarded the Barcelona City Technology Research Award (2005) and serving on the International Advisory Board for Physiological Measurement since 2010, his career combines academic leadership with real-world clinical translation through IBEC's technology transfer initiatives.
Jim Torresen is a Professor at the Norwegian University of Science and Technology (NTNU), specializing in Computer Science, Artificial Intelligence, and Robotics. He earned his M.Sc. and Dr.ing. (Ph.D.) in computer architecture and design from NTNU in 1991 and 1996 respectively, followed by industry experience in hardware design before transitioning to academia in 1999. Research Interests: His work spans Machine Learning, Evolvable Hardware, and Ethical AI, with notable contributions to music technology, facial expression recognition, and healthcare monitoring systems. He actively explores interdisciplinary applications of AI in creative domains and clinical environments. Publications & Editorial Roles: Torresen has published extensively in journals like Frontiers in Artificial Intelligence and Genetic Programming and Evolvable Machines . He serves as a Topic Editor for Frontiers in Explainable AI and has editorial roles in robotics and biomedical AI domains.
Dr. phil. André Fiebig is a Permanent Research Associate and PostDoc at the Institute of Fluid Mechanics and Technical Acoustics (ISTA) within Faculty V - Transportation and Mechanical Systems at Technical University of Berlin. From January 2019 to December 2024, he served as a Visiting Professor responsible for the field of psychoacoustics, funded by the HEAD Genuit Foundation. Since January 2025, he has been leading the 'Psychoacoustics and Noise Effects' working group at the Department of Technical Acoustics. His research spans multiple areas within psychoacoustics and soundscape studies, including fundamentals and modeling of psychoacoustic sensation variables, binaural psychoacoustics, assessment of ambient noise and soundscapes, and psychoacoustic evaluation of sound insulation measures. His work also addresses cognitive stimulus integration of auditory sensations, auditory recreation, acoustic quality of stay, characterization of quiet areas, and measuring sound-induced emotions. Analysis of his recent publications reveals a strong focus on urban soundscapes, noise-conscious behavior in transportation, and the development of methodological frameworks for soundscape assessment. His work often integrates psychoacoustic principles with environmental considerations, particularly examining the relationship between sound environments and human health. Recent research shows increasing emphasis on cross-cultural studies of noise perception and the development of standardized assessment methodologies. Dr. Fiebig is involved in the EARS (Education and Applied Research on Soundscapes) initiative and has contributed to numerous collaborative research projects examining the intersection of urban planning, environmental acoustics, and human perception. His work frequently appears in major acoustics conferences and journals, demonstrating his active role in advancing the field of psychoacoustics and soundscape research. His laboratory work focuses on psychoacoustic testing methodologies, soundscape assessment techniques, and the development of evaluation instruments for noise protection measures. The 'Psychoacoustics and Noise Effects' working group under his leadership conducts research on both theoretical aspects of sound perception and practical applications for urban noise management.
Victor Camillo Ottati is a Professor of Social Psychology at Loyola University Chicago, with a focus on political psychology, cross-cultural psychology, and communication. His research explores open-minded cognition, dogmatism, political judgment, and stereotyping. He has taught graduate courses in social psychology, social cognition, and political psychology, as well as undergraduate courses in introductory psychology, social psychology, and mass communication. Research Interests: Ottati's work addresses five key programs: (1) dogmatism and open-minded cognition, (2) cognitive processing styles in political judgment, (3) affect and nonverbal cues in political attitudes, (4) corrected vs. uncorrected social judgments, and (5) cross-cultural studies on subjective culture and stereotyping. He adopts an information-processing framework integrating affect and nonverbal cues. Recent Trends: His 2023 publications in Divided: Open-Mindedness and Dogmatism in a Polarized World emphasize group context, belief superiority, and situational factors in political cognition. Earlier works (2015-2020) investigate earned dogmatism, empathy in candidate evaluation, and Daoist thought's influence on leadership. Contact: Email vottati@luc.edu for inquiries.
Guy Dove is a Professor in the School of Arts & Sciences Humanities at the University of Louisville. His research bridges philosophy, cognitive science, neuroscience, linguistics, and artificial intelligence, focusing on the philosophy of psychology and abstract concept formation. PhD in Philosophy from the University of Chicago His work explores how language shapes cognition, advocating for a multimodal and flexible framework to understand abstract concepts. Recent publications address the implications of large language models for human cognition and the role of linguistic scaffolding in semantic memory. Key journals include Philosophical Transactions of the Royal Society B , Cognitive Neuropsychology , and Topics in Cognitive Science . He co-authored the book Consciousness and Physicalism: A Defense of a Research Program . Prior to his current role, Dove worked in the Developmental Neuropsychology and Electrophysiology Lab (2002-2003) and taught in the Department of Psychological and Brain Sciences (2004-2008).
Rishidev Chaudhuri is an Associate Professor at the University of California, Davis in the Department of Neurobiology, Physiology and Behavior within the College of Biological Sciences. His research focuses on computational neuroscience and neural dynamics, employing mathematical models to investigate how neural circuits generate cognitive processes such as memory, perception, and decision-making. His work explores neural dynamics through models of memory systems, attentional mechanisms, and probabilistic inference. Recent publications highlight advances in understanding hippocampal memory scaffolds, parietal-frontal interactions, and neuromorphic computing inspired by brain architecture. Education: BA in Physics (Amherst College), PhD in Applied Mathematics (Yale University) Centers: Center for Neuroscience; affiliated with Applied Mathematics and Neuroscience Graduate Groups Scientific awards and honors are not explicitly mentioned in the provided materials.
Jeff Linderoth is the Harvey D. Spangler Professor in the Department of Industrial and Systems Engineering at the University of Wisconsin-Madison. His research focuses on large-scale numerical optimization, mixed-integer nonlinear programming, and stochastic programming, with applications in energy systems, global routing, and industrial processes. Education: BS in General Engineering (highest honors) from University of Illinois at Urbana-Champaign, MS in Operations Research from Georgia Institute of Technology, PhD in Industrial Engineering from Georgia Institute of Technology. Linderoth's work addresses theoretical and applied challenges in optimization, including developing algorithms for mixed-integer programming, analyzing knapsack polytopes, and creating tools like the Minotaur optimization toolkit. His recent publications explore integer programming techniques for subspace clustering, complementarity constraints, and customized coverage instrumentation. Selected trends in his research include advancements in stochastic programming, orbital branching for symmetric integer programs, and congestion analysis in power systems. His group contributes to optimization software and data-driven libraries like MIPLIB. Scientific Award: Harvey D. Spangler Professor.
Haipeng Shen is a Professor of Innovation and Information Management at HKU Business School, The University of Hong Kong, serving as Associate Dean (EMBA and IMBA) and holding the Patrick S C Poon Professorship in Analytics and Innovation. He chairs the Business Analytics and Innovation program and joined HKU in 2015 after previously holding a professorship at the University of North Carolina at Chapel Hill. His academic credentials include: PhD in Statistics, The Wharton School of Business, University of Pennsylvania, 2003 MA in Statistics, The Wharton School of Business, University of Pennsylvania, 2000 BS in Mathematics, School of Mathematical Sciences, Peking University, 1998 Professor Shen's research focuses on data-driven decision making under uncertainty, with expertise spanning big data analytics, business analytics, healthcare analytics, and service engineering. He develops advanced statistical and machine learning methodologies to solve complex operational problems in call centers, optimize stroke care protocols, and enhance financial risk modeling, emphasizing real-time applications in high-stakes environments. Analysis of his recent publications reveals a consistent interdisciplinary approach bridging operations research, statistics, and domain-specific knowledge. His work demonstrates strong methodological innovation in time-series forecasting for service systems, risk assessment frameworks for medical complications, and covariance structure analysis for financial markets, with direct translational impact on business operations and clinical outcomes. His scientific contributions have been recognized with prestigious awards including: Most Influential Publication Award from China Stroke Association (2018) Fellow of the American Statistical Association (2015) Best Advisor of the Year Award from Academy of Asian Business (2018) Elected Member of International Statistical Institute (2015) Cluster Chair for Big Data Analytics at INFORMS International (2015) As an academic leader, Professor Shen has secured significant research funding from organizations including The Xerox Foundation and National Institute on Drug Abuse. He serves as Associate Editor for Management Science, Journal of the American Statistical Association, and Technometrics, while mentoring graduate students in statistical methodology and applied analytics. His current initiatives position HKU Business School at the forefront of healthcare innovation through big data analytics, driving collaborations with medical institutions to transform stroke care and hospital operations in Asia.
Lauren M. Lipner, Ph.D., is an Assistant Professor in the Clinical Psychology Doctoral Program at Long Island University (LIU) Post, within the College of Liberal Arts and Sciences. She holds a B.A. from Pennsylvania State University and earned her M.A. and Ph.D. in Clinical Psychology from Adelphi University in 2020. Her academic and clinical training includes an APA-accredited pre-doctoral internship at Pennsylvania Hospital/University of Pennsylvania Health System, a clinical postdoctoral fellowship at Mount Sinai Beth Israel, and a research and teaching postdoctoral fellowship at Adelphi University. Her research focuses on psychotherapy process and outcome, with an emphasis on the development and repair of the therapeutic alliance. Key areas include alliance rupture resolution, factors contributing to premature treatment termination, and methodological approaches to measuring therapeutic dynamics. She has contributed extensively to the literature through peer-reviewed journal articles, book chapters, and conference presentations. The most recent publications reflect a strong trend in advancing methodological rigor in studying alliance ruptures, utilizing control chart methods, single-case designs, and multi-method approaches. Her work bridges clinical practice with empirical research, particularly in cognitive-behavioral and integrative therapies for personality and anxiety disorders. Scientific awards and grants highlight her recognition in the field: Small Research Grant, Society for Psychotherapy Research (2021) Charles J. Gelso, Ph.D. Psychotherapy Research Grant, Society for the Advancement of Psychotherapy (APA Division 29, 2023) Dr. Lipner has served as Principal Investigator on funded projects including 'The relationship between therapist flexibility, alliance rupture resolution, and premature treatment termination' and 'Reasons for dropout measure: Development and validation.' She is actively involved in professional organizations such as the American Psychological Association (Divisions 12 and 29), the Society for Psychotherapy Research, and the Society for the Exploration of Psychotherapy Integration. She regularly presents her research at national and international conferences, contributing to training and supervision literature, particularly in CBT and alliance-focused models. While no specific lab or research team is explicitly named in the text, her collaborative work with prominent researchers like Jeremy D. Safran, J. Christopher Muran, and Jacqueline P. Barber suggests active participation in a research network focused on psychotherapy process and integration. Her contributions to handbooks and case studies further indicate a strong commitment to clinical education and training.
Matt Nassar is an Associate Professor of Neuroscience and Assistant Professor of Cognitive and Psychological Sciences at Brown University. He leads the Learning, Memory and Decision Lab, which is part of the Department of Neuroscience and the Robert J. & Nancy D. Carney Institute for Brain Science. His research focuses on understanding how the brain flexibly processes information to achieve complex and adaptive behaviors through computational approaches that bridge cognitive psychology and neuroscience. Education: PhD, University of Pennsylvania (2012) BA, Colgate University (2004) Nassar's research examines how different cognitive systems—learning, memory, and perception—leverage common computational principles to optimize decision-making. His work particularly focuses on how the brain balances stability and flexibility in processing information, how uncertainty is represented and utilized in learning, and how neural computations underlie complex behaviors. Through computational modeling and empirical research, he investigates how modular information-processing systems impact decisions and complex behavior in dynamic environments. His research integrates methods from cognitive psychology, neuroscience, and computational modeling to address fundamental questions about human cognition. Analysis of Nassar's recent publications (2020-2024) reveals a strong focus on computational neuroscience applied to decision-making, learning, and psychiatric conditions. His work frequently employs Bayesian modeling approaches to understand belief updating, uncertainty processing, and structure learning. Key themes include the neural basis of flexibility in learning, computational mechanisms underlying psychiatric symptoms, and age-related changes in cognitive processing. His research bridges cognitive psychology, neuroscience, and computational modeling to provide insights into both healthy cognition and disorders such as depression and schizophrenia. Scientific Contributions: Developed computational models of belief updating and learning under uncertainty Investigated neural mechanisms of stability-flexibility tradeoffs in cognition Examined age-related differences in learning and memory processes Explored computational mechanisms underlying psychiatric conditions Studied the role of noise correlations in neural learning systems Investigated how prefrontal cortex representations shape decision processes Nassar actively mentors researchers in his lab, with recent announcements highlighting postdocs joining from prestigious institutions like Max Planck UCL and Freie Universität Berlin. His lab appears to receive significant research funding, supporting multiple postdoctoral positions and research projects. Collaborations span multiple departments at Brown University, particularly with researchers in Cognitive and Psychological Sciences, Neurology, and Psychiatry. The lab has produced numerous high-impact publications in top journals including Nature Human Behaviour, Brain, and eLife. The Learning, Memory and Decision Lab, led by Nassar, is an active research group that uses computational models to understand how the brain represents and stores information for effective decision making. Recent lab announcements (as of February 2025) indicate the lab is expanding with new postdoctoral researchers joining from Harvard, Max Planck UCL, and Freie Universität Berlin, suggesting strong research momentum and funding support. The lab appears to be well-integrated within Brown's neuroscience community, with collaborations spanning multiple departments and research centers.
Frank E. Garcea, Ph.D., is a Research Assistant Professor in the Department of Neurosurgery and Neuroscience at the University of Rochester School of Medicine and Dentistry. His research focuses on the cognitive and neural mechanisms underlying tool use, apraxia, and stroke recovery. He employs neuropsychological testing, fMRI, and lesion-symptom mapping to study brain injury effects on functional connectivity and action knowledge. Education: Bachelor of Science in Psychology, St. John Fisher College (2006–2010) PhD in Brain and Cognitive Sciences, University of Rochester (2012–2017) Research Interests: Dr. Garcea investigates how brain regions like the parietal cortex and dorsal/ventral streams mediate object manipulation and tool use. His work explores stroke-related disconnection syndromes, motor speech coordination networks, and translational brain mapping to preserve neural function during surgery. He collaborates on projects involving epilepsy patients undergoing electrocorticography to study action-related neural pathways. Labs & Affiliations: Principal Investigator of the Garcea Lab at URMC, focusing on tool use deficits in brain tumor/stroke survivors. Affiliated with the Del Monte Institute for Neuroscience and the Neurobiology & Anatomy Program. His lab integrates neuroimaging, lesion analysis, and clinical care to advance personalized brain mapping strategies.
Dr. James Ashton-Miller is a prominent faculty member in the Department of Mechanical Engineering at the University of Michigan, where he directs the Biomechanics Research Laboratory. He serves as a Center Member of the University of Michigan Injury Prevention Center and maintains affiliations with the Institute of Gerontology. His interdisciplinary work bridges engineering principles with medical applications, focusing on injury prevention across sports medicine, obstetrics, and geriatrics. Dr. Ashton-Miller's educational background includes: PhD from the University of Oslo, Oslo, Norway (1978-1983) MSME from M.I.T., Cambridge, MA, U.S.A (1972-1974) B.SC. (Hons) from the University of Newcastle-upon-Tyne, Newcastle-upon-Tyne, England (1967-1972) His research focuses on the biomechanics of injury prevention across multiple critical domains. In sports medicine, he has demonstrated that some ACL injuries are overuse injuries resulting from too many sub-maximal loading cycles that prevent healing of collagen damage. In women's health, his work on childbirth injuries addresses conditions that affect more women than breast cancer. His research on fall-related injuries in older adults reveals the dual threat of physical and cognitive factors. He also investigates sciatica, disc degeneration, and develops new medical devices for screening, diagnosis and treatment. Dr. Ashton-Miller's recent publications show a strong trend toward developing practical clinical applications from fundamental biomechanical research, with emphasis on advanced imaging methods, wearable sensors, and computational modeling for pelvic floor function assessment. His work consistently aims to translate engineering insights into clinical solutions for injury prevention. His research insights have earned him numerous national and international research awards, though specific awards aren't detailed in the available information. His work involves close collaboration with clinicians and surgeons who meet weekly to discuss progress and next steps. Dr. Ashton-Miller is deeply committed to mentoring, working with NIH K-series fellows along with 1-2 post-doctoral fellows, 3-5 PhD students, 2-4 M.S. students, 4-5 undergraduate students, and 2-4 young clinicians. His research is generously supported by the National Institutes of Health, National Science Foundation, National Basketball Association, Fortune 500 companies, and startup companies including Procter & Gamble and Hologic, Inc. He directs the Biomechanics Research Laboratory and co-leads the Pelvic Floor Research Group, where his teams develop new medical devices to improve screening, diagnosis, and treatment of various biomechanical conditions. These laboratories maintain strong clinical connections, ensuring research remains grounded in real-world medical challenges.
Niko Troje is a Professor at York University, affiliated with the Departments of Psychology, Biology, and Electrical Engineering & Computer Science. He holds cross-appointments and leadership roles, including Director of the BioMotion Lab. His research focuses on perceptual representations, biological motion, and vision science. Education: Ph.D. in Biology (1994) - Albert-Ludwigs Universität B.Sc. in Biology (1990), Physics & Mathematics (1987) - Albert-Ludwigs Universität Research Interests: Troje investigates how the brain processes biological motion, perception of human and animal movement, and applications in virtual reality. His work bridges neuroscience, psychology, and computer science. Key Contributions: Pioneered point-light displays for motion perception, explored gait analysis in mental health, and developed tools for motion capture and analysis (e.g., bmlTUX). Awards: Humboldt Research Prize (2014) NSERC Steacie Fellowship (2008-2009) Canada Research Chair (2003-2013) Grants & Labs: Led funded projects on movement perception, collaborated with institutions like the Max Planck Institute, and directs the BioMotion Lab at York University.
