Rosemarie Nagel is an ICREA Research Professor in the Department of Economics at Universitat Pompeu Fabra (UPF). She holds a PhD from the University of Bonn (1994) under Reinhard Selten. Her research bridges economic theory with behavioral insights, focusing on experimental economics, neuroeconomics, and game theory. She has pioneered the level-k reasoning model in Keynesian beauty-contest experiments and explored bounded rationality through lab and neuroscientific methods. Her work spans macroeconomic experiments, industrial organization, and strategic behavior analysis. She has been a full professor at UPF since 2006 and joined ICREA in 2007. Education: PhD in Economics, University of Bonn, 1994 (Advisor: Reinhard Selten) Postdoctoral work with Al Roth at University of Pittsburgh, 1994-1995 Research Interests: Experimental Economics (macro and micro), Neuro-Economics, Geno-Economics, Game Theory, Industrial Organization, Negotiation. Her methods integrate cognitive models, laboratory experiments, and neuroscience tools to study human decision-making. Key Contributions: Her work on strategic uncertainty in coordination games and neural correlates of strategic thinking has been published in top journals like American Economic Review , Econometrica , and Review of Economic Studies . She co-organizes macroeconomics and computational economics workshops. Professional Activities: Editor for Games and Economic Behavior , frequent speaker at international conferences, and advisor to policy institutions. Her lab focuses on experimental design and neuroeconomic applications.
David Jensen is a Professor in the College of Information and Computer Sciences (CICS) at the University of Massachusetts Amherst. He directs the Knowledge Discovery Laboratory and the Computational Social Science Institute. His research focuses on machine learning, causal modeling, and analyzing large social, technological, and computational systems. Jensen's work is supported by organizations like the National Science Foundation and DARPA. Education: DSc in Engineering and Policy, Washington University in St. Louis (1992) MS in Engineering and Policy, Washington University in St. Louis (1988) BS in Mechanical Engineering, University of Nebraska (1986) Research Interests: Causal inference in relational and dynamic systems Machine learning applications in security and privacy Computational social science Large-scale network analysis Achievements: Recipient of teaching awards from UMass College of Natural Sciences (2011) and CICS (2022) 2017 IEEE INFOCOM Test of Time Paper Award Leadership roles in conferences and journals, including action editor for the Journal of Machine Learning Research Labs and Affiliations: Founder of the Knowledge Discovery Laboratory (2000) Director of the Computational Social Science Institute (2018-2022) Member of the Computing Community Consortium (CCC) Council
Dr. Jing Zhang is an Assistant Professor in the Department of Computer Science at the University of California, Irvine (UCI), affiliated with the Donald Bren School of Information and Computer Sciences. She holds a Ph.D. in Electrical Engineering and Molecular/Computational Biology from the University of Southern California (2012) and completed postdoctoral training in Computational Biology at Yale University. Her research focuses on developing computational methods to unravel gene regulation mechanisms and link genetic variations to diseases, particularly in noncoding regions of the genome. She has contributed extensively to the ENCODE project, co-authoring pivotal studies in Nature and producing over 5,900 experimental datasets. Dr. Zhang’s work bridges engineering, mathematics, and biology, with applications in precision medicine for cancers and psychiatric disorders. She emphasizes the importance of noncoding DNA in disease causation and has pioneered tools like EN-TEx and scENCORE to analyze epigenomes and regulatory elements. Her lab actively seeks to recruit Ph.D. students, postdocs, and interns to advance genomic technologies. Key research areas include single-cell and spatial transcriptomics, gene regulatory networks, and computational methods for multi-omics data integration. Despite pandemic-related challenges, she maintains strong collaborations and teaches courses in bioinformatics. Her future goals include expanding lab interactions and applying computational models to predict disease susceptibility and treatment responses.
Raymond H. Cuijpers is an Associate Professor at Eindhoven University of Technology in the Human Technology Interaction group. His research focuses on Cognitive Robotics , Human-Robot Interaction , and Artificial Intelligence for cognitive agents, with applications in healthcare robotics and aging population support. PhD in Physics of Man from Utrecht University (2000) Postdoctoral research at Erasmus MC Rotterdam and Radboud University Nijmegen Key research areas include: Developing socially intelligent robots with proper social cue interpretation Hybrid AI approaches for real-world complexity handling Visual-haptic perception integration in human motor control Service robots for COPD patient assistance (KSERA project) Rescue robotics and tele-operation applications Recent research output (2025) includes studies on: Personalization in human-robot communication Optimal lighting for elderly visual perception Human-robot bonding mechanisms Interactive sensorized platforms for homecare (GUARDIAN) Audiovisual temporal integration in virtual environments He coordinates large-scale European projects like GUARDIAN and previously KSERA, contributes to sustainable development goals through healthcare robotics, and serves on editorial boards of leading journals including International Journal of Social Robotics . His work spans both technical robotics development and human-centric interaction studies.
Minoru Koyama is an Assistant Professor in the Department of Cell & Systems Biology at the University of Toronto Scarborough (UTSC). His research focuses on understanding the neural circuit mechanisms underlying behavioral development, particularly in zebrafish models. He employs advanced techniques such as optogenetics, voltage imaging, and CRISPR-based methods to study circuit maturation in the hindbrain and spinal cord. Education: Koyama holds a Ph.D. (2006), M.Sc. (2002), and B.Sc. (2000) in Biological Sciences from the University of Tokyo. Research Interests: His work investigates how neural circuits mature post-birth and contribute to complex behaviors, with applications to developmental brain disorders. His lab uses zebrafish as a model system, combining optics, genetics, and machine learning for behavioral analysis. Key projects include studying motor coordination development and refining imaging techniques like multi-plane microscopy and voltage indicators. Publications Highlight: Koyama’s recent work includes innovations in microscopy (e.g., HiLo speckle illumination) and genetic tools (e.g., TEMPO lineage tracing). These advancements enable precise observation of neural circuits and cellular dynamics. Lab & Recruitment: The Koyama Lab actively recruits graduate students and postdoctoral researchers. No specific grants are detailed, but his work reflects broad interdisciplinary collaborations in neuroscience and biotechnology. Labs/Teams: His lab focuses on developmental neurobiology, leveraging cutting-edge imaging and genetic engineering to explore neural circuit function across vertebrate development.
Dr. Avniel Singh Ghuman is an Associate Professor in the Department of Neurological Surgery at the University of Pittsburgh School of Medicine. He serves as Director of the Cognitive Neurodynamics Lab and plays a key role in advancing MEG (Magnetoencephalography) Research at the university. His work bridges clinical neurosurgery with fundamental neuroscience research to understand visual perception mechanisms. Dr. Ghuman's educational background includes: BA in Math and Physics from The Johns Hopkins University (1998) PhD in Biophysics from Harvard University (2007) Postdoctoral training at the National Institute of Mental Health Dr. Ghuman's research focuses on how the brain transforms visual input into meaningful perception of objects, faces, words, and social images in real-world contexts. His laboratory employs both invasive (intracranial EEG) and non-invasive (MEG) techniques to examine the spatiotemporal dynamics of neural activity during visual processing. The lab integrates multivariate machine learning methods, network analysis, and direct neural stimulation to investigate information processing at both local brain regions and distributed network levels. Recent work has pioneered methods for studying brain activity during authentic social interactions and natural behavior. His publication record demonstrates significant contributions to understanding real-world face perception, neural dynamics during natural behavior, and the application of advanced analytical techniques to brain imaging data. His research has revealed how brain network dynamics form a 'punctuated equilibrium' of stable states with transitory bursts between them, coinciding with behavioral shifts in everyday activities. Dr. Ghuman has received notable recognition for his work: Young Investigator Award from NARSAD (2012) Award for Innovative New Scientists from the National Institute of Mental Health (2015) His research has been featured in prominent media outlets including MIT Technology Review, The Wall Street Journal, and Carnegie Mellon University publications. As Director of the Cognitive Neurodynamics Lab, Dr. Ghuman leads a research program that has advanced our understanding of how the brain processes visual information in real-world environments, with implications for both fundamental neuroscience and clinical applications.
Qiongshi Lu is an Associate Professor at the University of Wisconsin–Madison, affiliated with the Department of Biostatistics and Medical Informatics within the School of Medicine and Public Health. He also holds affiliate faculty positions in the Department of Statistics, Computer, Data & Information Sciences at the College of Letters and Science. His research focuses on developing statistical methods for human genetics, including genome-wide association studies (GWAS), gene-environment interactions, and genetic risk prediction. Lu’s work bridges computational biology, epidemiology, and clinical genetics, with a particular emphasis on understanding complex trait variability and resilience mechanisms in neurodegenerative diseases like Alzheimer’s. His lab (qlu-lab.org) explores innovative statistical frameworks such as PIGEON for gene-environment interaction analysis and has contributed to tools like the R package 'ipd' for predictive data inference. Recent studies highlight his interdisciplinary approach, addressing topics from congenital heart disease genetics to socioeconomic health gradients using large-scale genomic datasets. While no formal advisees are listed, his research collaborations span multiple institutions and disciplines.
Mandana Arbab is the Lodish Family Assistant Professor of Neurology at Harvard Medical School and faculty member of the Rosamund Stone Zander Translational Neuroscience Center at Boston Children's Hospital. Her research program focuses on developing precision gene editing therapies for neurodegenerative disorders. Current work employs CRISPR-based technologies to correct genetic mutations underlying conditions like spinal muscular atrophy and telomere biology disorders. Recent publications demonstrate innovations in base editing systems, including engineering novel editors with reduced off-target effects. Her 2023 Science paper established preclinical proof-of-concept for base editing in spinal muscular atrophy. Dr. Arbab's lab combines high-throughput screening, machine learning, and molecular biology to optimize therapeutic genome editing. She was awarded the NIH Pathway to Independence Award for her work advancing neurological gene therapies.
Dr. Jeroan Allison is Chair and Professor at UMass Chan Medical School's Department of Population and Quantitative Health Sciences. Trained as a primary care physician and epidemiologist (Harvard SPH), he leads research in narrative interventions for health behavior change, with continuous funding from NIH, AHRQ, and RWJF. His work spans hypertension control in Vietnam, AI-driven health communication, and implementation science for non-communicable diseases. Harvard School of Public Health: Master of Science in Epidemiology University of Alabama at Birmingham: MD Samford University: BS in Chemistry Research interests include narrative medicine , health disparities , mHealth , and health services research . He has published extensively on hypertension interventions in Vietnam, digital health tools, and tobacco cessation strategies using peer engagement. Recent publications focus on AI applications , global implementation science , and social determinants of health . His team has developed culturally adapted interventions for HPV vaccination and hypertension management using community storytelling methods. Scientific contributions include: Co-Editor-in-Chief of Medical Care Developing simulation-based training for research assistants Designing peer recruitment models for smoking cessation Dr. Allison holds multiple grants and leads the UMMS-Vietnam research collaboration , focusing on late-stage translation research in low-resource settings.
Line Katrine Harder Clemmensen is an Associate Professor at the Department of Applied Mathematics and Computer Science, Technical University of Denmark (DTU), affiliated with the DTU Microbes Initiative. She holds a Ph.D. from DTU's IMM (2006–2009) and previously served as Principal Data Scientist at the Maersk Group (2016–2017). Her research focuses on machine learning, statistical modeling, deep learning, and sparse methods, applied to environmental, biological, industrial, and financial domains. Notable projects include hydroacoustic modeling in aquaculture systems, AI-driven sea safety, and bio-based sustainability modeling. Her recent work addresses topics like parent-child interaction patterns in OCD, Alzheimer’s treatment via spectral flicker, and genomic studies on social trust. She supervises multiple PhD students, including those exploring Raman spectroscopy applications and contamination detection in drug products. Language skills include Danish, English, Spanish, French, and Portuguese.
Donald S. Sakaguchi is the Morrill Professor in the Department of Genetics, Development and Cell Biology at Iowa State University (ISU), and serves as Director of the Biology and Genetics Undergraduate Programs. He holds an adjunct professorship at the ISU College of Veterinary Medicine. His research focuses on regenerative and repair strategies for the nervous system, particularly using stem cells and biomaterials for neuroprotection and tissue repair. Dr. Sakaguchi earned his B.S. and Ph.D. in Biology/Neurobiology from SUNY Albany and completed postdoctoral training at UC San Diego. Education: B.S. Biology (SUNY Albany, 1979), Ph.D. Neurobiology (SUNY Albany, 1984), Postdoctoral Fellow (UC San Diego). Research Interests: Developing cell-based therapies for neurodegenerative diseases and injuries using mesenchymal stem cells (MSCs) and neural progenitor cells (NPCs). Key areas include: 1) Stem cell engineering for neurotrophic factor delivery, 2) Biomaterials for neural regeneration (e.g., 3D-printed conduits), 3) Peripheral nerve repair via transdifferentiation, and 4) In vitro models of traumatic brain injury. Collaborations span neuroscience, bioengineering, and veterinary medicine. Labs/Teams: Sakaguchi Lab at ISU, part of the Nanovaccine Institute and interdisciplinary programs in Neuroscience, MCDB, and Bioinformatics. The lab emphasizes diversity and inclusion, fostering training for undergraduate and graduate researchers.
Dr. Franziska Pannach is an Assistant Professor at the Faculty of Arts of the Rijksuniversiteit Groningen (Netherlands), affiliated with the Centre for Language and Cognition (CLCG) . She specializes in Computational Linguistics , Digital Humanities , and Semantic Web Technology , focusing on modeling narratives and mythological texts using NLP and ontologies. Her work emphasizes Open Science and cross-cultural comparisons of folktales and myths. Education : Dr. rer. nat. (PhD) in Applied Computer Science (Digital Humanities/Computational Linguistics), University of Göttingen, Germany (2024) MSc in Applied Computer Science (Digital Humanities), University of Göttingen (2019) BSc in Applied Computer Science (Computational Neuroscience), University of Göttingen (2013) Research Interests include computational approaches to mythological and folkloristic analysis, shallow ontologies for narrative comparison, and semantic web applications in cross-cultural studies. She leads the GOLEM (Graph Ontologies for Literary Evolution Models) project and contributed to the STRATA (Stratification Analyses for Mythic Narrative Materials) project. Teaching : Semantic Web Technology (MSc), Database-driven Web Technology (BSc), Digital Humanities: Tools and Methods (MSc), Analysing Data (MSc) Supervision : PhD students Pritha Majumdar (RUG) and Kristina Schneider (RUG/University of Mainz) Publications focus on narrative ontologies, mythological event annotation, and NLP for under-resourced languages. Her recent work includes the GOLEM Triple Store and shallow ontologies for myth comparison. Networks & Memberships : Member, Digital Humanities Association of Southern Africa (DHASA) since 2019 Co-founder and editor of the Journal of Digital Humanities Association of Southern Africa (JDHASA) Collaborations with institutions in Germany, South Africa, and Denmark
Dr. Lauren Robinson is a researcher affiliated with King's College London and the NIHR Maudsley Biomedical Research Centre (BRC) , focusing on Psychological Medicine . Her work spans Eating Disorders , Neuroscience , and Mental Health , with a particular emphasis on personality profiles, diagnostic markers, and comorbidity in eating disorders. Her research integrates longitudinal studies and neuroimaging to explore developmental trajectories in adolescents. Recent work includes machine learning applications for risk prediction in psychiatric conditions and immune ageing in COVID-19 severity. She leads projects like First Episode Eating Disorders and Markers of Bone Health (2019–2021), funded by collaborations with institutions such as the Berlin Institute of Health and NUI Galway . Key trends in her 2024 publications include personality traits as diagnostic markers for eating disorders, immune system dynamics in viral diseases, and bone fracture risks in anorexia nervosa patients. Her interdisciplinary approach bridges psychiatry , genetics , and machine learning . Lauren Robinson collaborates extensively across Europe, with affiliations at Technische Universitat Dresden , University of Toronto , and Fudan University . Her work contributes to UN Sustainable Development Goals, particularly Good Health and Well-being (SDG 3).
Hedy Kober is an Adjunct Associate Professor in Psychiatry at Yale School of Medicine and an Adjunct Associate Professor of Law. She serves as Director of the Clinical and Affective Neuroscience Laboratory at Yale. Her work bridges psychology, neuroscience, and clinical interventions, with a focus on emotion regulation, mindfulness, and addiction. Education PhD in Clinical Psychology (Respecialization), Fielding Graduate University (2021) PhD, Columbia University (2009) MPhil, Columbia University (2008) MA, Columbia University (2007) Research Interests Dr. Kober's research focuses on the cognitive and neural mechanisms underlying emotion regulation, with particular emphasis on mindfulness-based interventions for various conditions including addiction, eating disorders, and depression. Her work explores how individuals regulate cravings, manage negative emotions, and develop healthier behavioral patterns through cognitive strategies and mindfulness practices. She employs a range of methodologies including fMRI, ecological momentary assessment, and clinical trials to investigate these processes in both healthy individuals and those with clinical conditions. Her recent work has increasingly focused on digital interventions that make evidence-based therapies more accessible, particularly for substance use disorders and eating disorders. She examines how brief, scalable interventions can effectively target core mechanisms of behavior change. Research Trends Dr. Kober's recent publications demonstrate a strong focus on the intersection of emotion regulation, mindfulness, and clinical applications. Her work connects basic cognitive neuroscience with clinical interventions, particularly examining how individuals regulate cravings and negative emotions. Recent studies have expanded to include digital delivery of interventions, network approaches to understanding emotional processes, and the development of neuromarkers for addiction. Her research increasingly incorporates longitudinal and ecological momentary assessment methods to capture real-world emotional dynamics. Scientific Awards Outstanding Mentor Award (2019) from American Academy of Child and Adolescent Psychiatry Early Career Investigator Award (2018) from NIDA and NIAAA Teaching Excellence at Yale (2017) from Yale Center for Teaching and Learning Helmsley Fellowship in Cross Disciplinary Science (2016) from Helmsley Charitable Trust Scholar Award (2011) from Yale Center for Clinical Investigation Advising and Grants Dr. Kober has received significant grant funding for her research on emotion regulation and addiction. She serves as Principal Investigator on clinical trials examining brief training for alcohol craving regulation and the role of reward learning and decision making in addiction. Her work has been supported by organizations including NIDA and NIAAA. As a mentor, she has guided numerous students and early-career researchers, recognized by her Outstanding Mentor Award from the American Academy of Child and Adolescent Psychiatry. Laboratory Dr. Kober directs the Clinical and Affective Neuroscience Laboratory at Yale, which investigates the neural and cognitive mechanisms of emotion regulation and their application to clinical problems. The lab employs a multi-method approach including neuroimaging, behavioral experiments, and clinical interventions to understand how people regulate emotions and cravings, with the goal of developing more effective treatments for conditions like addiction and eating disorders.
Colin Conrad is an Associate Professor of Digital Innovation at Dalhousie University’s Faculty of Management. He also serves as Co-Director of the College of Digital Transformation and Principal of the Cognition and Organizations Research Group. His research focuses on interdisciplinary projects spanning information systems, computer science, and cognitive neuroscience, with particular emphasis on human factors in educational technology and artificial intelligence. His work is supported by NSERC, CFI, and Mitacs. Research interests include mind wandering measurement via EEG, AI ethics, human-AI interaction, and neurophysiological impacts of digital technologies. He explores topics such as virtual teacher perception, privacy calculus in AI systems, and cognitive state awareness in human-AI collaboration. His recent studies address challenges in remote work ergonomics, digital transformation during crises, and legal/ethical aspects of brain-computer interfaces. His publications analyze behavioral responses to cybersecurity notifications, virtual influencer trust dynamics, and adaptive online learning systems. Current projects investigate the cognitive effects of AI-generated media and the neurophysiological foundations of attention in digital environments. Colin’s research is funded through grants emphasizing interdisciplinary innovation and societal impact. He collaborates with industry partners to translate neuroscientific insights into practical applications in education and workplace design.
