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Arlene BjugstadView profile

Assistant Professor

• School-based mental health
• Community-engaged research
• Community organizing
• +4 more

Arlene Bjugstad is an Assistant Professor in the Department of Social Work at the University of Colorado Colorado Springs. She holds a PhD in Social Work from the University of Houston, an MSW from Our Lady of the Lake University, and a BSW from Winona State University. With over 15 years of practice experience in non-profits, social services, schools, and communities, her work bridges culturally-grounded approaches to mental health, immigration, and community organizing. Her research focuses on culturally-responsive interventions, school-based mental health, and political determinants of health with an emphasis on immigrant populations. Publications appear in journals like Applied Developmental Science and Journal of Racial Ethnic Health Disparities. She co-facilitates the Central American Minors (CAM) Working Group addressing newcomer immigrant children’s needs in Houston. Key research areas include decolonized social work practices, trauma resilience, and advocacy for marginalized communities. Active as a peer reviewer for Psychology in the Schools and International Journal of Intercultural Relations.

Ullrich KötheView profile

Associate Professor

• Machine Learning
• Neural Networks
• Explainable AI
• +6 more

Prof. Dr. Ullrich Köthe is an Associate Professor and group leader in the Visual Learning Lab Heidelberg at the University of Heidelberg . He focuses on Explainable Machine Learning , leveraging Invertible Neural Networks to enhance transparency and utility in image analysis and medical applications . He also maintains the widely used VIGRA image analysis library. Education: PhD in Informatics, University of Hamburg, 2000 Habilitation in Informatics, University of Hamburg, 2008 His research interests center around machine learning , image analysis , and scientific computing , particularly the development of robust algorithms for medical imaging , computer vision , and life sciences . His work on invertible neural networks and parameter-free segmentation has led to significant advancements in the field. Recent publications highlight his contributions to Bayesian inference , neural network interpretability , and stochastic modeling , with applications ranging from disease outbreak dynamics to connectomics . Key trends include generative models , parameter-free segmentation , and likelihood-free inference . Scientific Awards: DAGM 2003 Main Prize DAGM Best Paper Award 2008 He has supervised numerous Master and Bachelor theses in machine learning and image analysis , with teaching roles in Advanced Machine Learning and Explainable AI . His collaborative research grants include funding from HARMAN International (2024). He leads the Explainable Machine Learning subgroup and has contributed to open-source software projects like ilastik and VIGRA , which are critical tools in bioimage analysis .

Gaurab AryalView profile

Associate Professor

• Empirical Industrial Organization
• Econometrics
• Market Design
• +1 more

Gaurab Aryal is an Associate Professor of Economics at Boston University's Department of Economics, with previous positions at Washington University in St. Louis and the University of Virginia. He holds a Ph.D. in Economics from The Pennsylvania State University and specializes in empirical industrial organization. His research focuses on market design, pricing strategies, and competitive dynamics in industries such as airlines, insurance, and procurement. Key interests include econometric modeling of auctions, analysis of collusion mechanisms, and the impact of information asymmetries on market outcomes. Professor Aryal's work has appeared in leading journals including the Review of Economic Studies and American Economic Review, with recent studies examining airline subcontracting patterns, multidimensional insurance markets, and Cournot oligopoly frameworks. His research integrates theoretical modeling with innovative empirical approaches to address real-world competition policy questions. He has received multiple research grants including the Bankard Fund for Political Economy grant and Weidenaum Center award, supporting investigations into coordinated market behaviors and institutional design. Professor Aryal actively mentors graduate students and serves on departmental committees, including PhD admissions and executive committees. He teaches courses on market structure, auction theory, and empirical industrial organization.

Haibing LuView profile

Professor

• AI Fairness and Governance
• Data Security & Privacy
• Big Data Analytics
• +4 more

Haibing Lu is a Professor and Department Co-Chair of Information Systems & Analytics at Santa Clara University's Leavey School of Business. He holds a Ph.D. in Information Technology from Rutgers University (2011), and B.S./M.S. in Mathematics from Xi'an Jiaotong University (2002/2005). His research focuses on AI fairness, data privacy, cybersecurity, and big data analytics, addressing real-world challenges in healthcare, transportation, and cloud computing. Education: Ph.D. in Information Technology, Rutgers University, 2011 M.S. in Mathematics, Xi'an Jiaotong University, 2005 B.S. in Mathematics, Xi'an Jiaotong University, 2002 Research interests include: AI governance and ethical frameworks Privacy-preserving technologies (e.g., differential privacy) Cybersecurity for IoT and smart grids Applications of machine learning in healthcare and transportation His work has been featured in prestigious journals like IEEE Transactions on Dependable and Secure Computing, ACM Transactions on MIS, and M&SOM, alongside media outlets such as The New York Times and WIRED. Key publications include studies on AI fairness in LLMs, privacy in cloud computing, and secure authentication protocols. Awards include: AACSB Innovations That Inspire Award (2021) M&SOM Best Paper Award Repeated SCU Leavey School Excellence Awards for Teaching/Research/Service Grants and funding sources include NSF, IBM, PARC, and industry partnerships like AKTANA and Ultimate Software. He advises on interdisciplinary projects involving data science, cybersecurity, and sustainable energy systems. Labs/Initiatives: Leads research in Information Systems & Analytics at SCU, with collaborations on metaverse-driven data management and AI governance frameworks.

• Body Image
• Interoception
• Perception and Cognition
• +4 more

Dr. Sarah Cooney is an Assistant Professor at University College Dublin's School of Psychology and Director of the UCD Body Lab. She holds a PhD from University College Dublin and has postdoctoral experience at Trinity College Dublin. Her research focuses on body image, interoception, perceptual cognition, and eating disorders, with a particular interest in how these factors interact across diverse populations. She has secured grants including the Ad Astra Start-Up and the HRB-funded BodyWise project. Dr. Cooney actively contributes to public engagement, including events on body image and mental health, and serves on committees such as the EDIP (Equality, Diversity, and Inclusion in Psychology). She teaches courses like 'Brain & Behaviour' and coordinates advanced research methods modules. Her work bridges experimental psychology with educational technology, exemplified by her development of the Cartesian-Garden VR tool for teaching mathematics. PhD: University College Dublin Postdoctoral Fellowships: Trinity College Dublin (2017–2019) and UCD (2018–2019) Her research interests include: Body representation and sensorimotor integration Interoceptive awareness and its clinical implications Developmental spatial-numerical cognition Multisensory learning in immersive environments Dr. Cooney's articles explore topics ranging from body image disturbances in adulthood to the influence of sports/music experience on motor imagery. She has authored over 50 peer-reviewed publications and actively participates in academic conferences, including the Psychonomic Society and Spatial Cognition events.

• Clinical Psychology
• Neuropsychological Assessment
• Cultural Competency in Healthcare
• +3 more

Dr. Lawrence Pick is a Professor in the Department of Psychology at Gallaudet University's Human Services and Sciences school. He has been teaching in the Clinical Psychology PhD Program since 2009, specializing in neuropsychological assessment and culturally-responsive mental health services for deaf and hard-of-hearing individuals. His research focuses on developing accessible clinical tools, evaluating service equity, and supporting trainees in multicultural competency. Dr. Pick holds a Ph.D. and is a board-certified clinical neuropsychologist (ABPP-CN). He teaches courses such as Neuroanatomy & Neurophysiology, Psychopharmacology, and Clinical Psychology Practicum. He serves as an editor for journals like Journal of Deaf Studies and Deaf Education and reviews for granting agencies in neuropsychology and rehabilitation psychology. His work emphasizes linguistic and cultural adaptations in psychological practices, including telepsychology accessibility and forensic considerations for deaf youth. He collaborates on initiatives like the Multidimensional Inventory of Deaf Acculturative Stress and has published extensively on topics ranging from sexual assault among Deaf women to cognitive testing for deafblind children.

• Chemical Engineering
• Bioprocess Engineering
• Materials Science
• +4 more

Dr. Georg Pesch is an Assistant Professor/Lecturer at the University of College Dublin's School of Chemical and Bioprocess Engineering, with an ORCID identifier 0000-0003-4676-1908. His roles include coordinating modules such as Chemical Thermodynamics and Applied Research Design. He holds a BSc, MSc, and Dr.-Ing. from the University of Bremen, Germany, and completed postdoctoral research at Delft University of Technology. Previously, he was a Group Leader at the University of Bremen's Faculty of Production Engineering (2018–2022). Dr. Pesch's research focuses on dielectrophoretic technologies for particle separation, electrokinetic filtration, and catalytic reactor design. His work integrates computational fluid dynamics (CFD), nuclear magnetic resonance (NMR) imaging, and microfluidics to advance high-throughput separation systems and operando reaction analysis. Key projects include developing bio-inspired catalyst supports for heat management and antifouling strategies for underwater optics. He has secured grants from the Deutsche Forschungsgemeinschaft, Science Foundation Ireland, and industry partnerships. His scientific contributions span over 50 peer-reviewed articles, emphasizing applications in biomedical engineering (e.g., tumor cell isolation), energy storage (lithium-ion battery recycling), and materials science. Teaching responsibilities include advanced chemical engineering modules and work placement coordination. Current projects include the CFD-MRI Reactions initiative and investigations into foam fractionation for pharmaceutical applications. Grants: Electrokinetic Material Recycling, CFD-MRI Reactions, High-Throughput Separation of Tumor Cells. Lab Focus: Dielectrophoretic Particle Chromatography, NMR-Validated Catalytic Reactors.

• Prosocial Behavior
• Adolescence
• Toddlers
• +4 more

Xinyue Xiao is an Assistant Professor in the Department of Psychological Sciences at Northern Arizona University. Her research focuses on prosocial behavior, adolescence, and gender differences. Research Interests: Prosocial Behavior, Adolescence, Toddlers, Gender Difference, Intergroup Contact Theory, Caregiver Psychology, Intergroup Relations Her recent work examines the intersection of gender, peer relationships, and prosocial behavior in children and adolescents. Key themes include intergroup contact theory, social identity, and classroom dynamics. Recent publications highlight longitudinal studies on intergroup friendships, gender discrimination, and prosocial behavior in diverse social contexts. Notable trends include analyses of coeducational environments and multidimensional social identities.

Laurent DonzéView profile

Professor

• Applied Statistics
• Econometrics
• Survey Methodology
• +7 more

Laurent Donzé is a Professor of Applied Statistics and Modelling at the Department of Informatics, Faculty of Economics and Social Sciences, University of Fribourg. He is also a Research Professor at KOF ETH Zurich and a Professor of Econometrics at the University of Neuchâtel. He leads the ASAM research group and has extensive experience in teaching mathematics, econometrics, and statistics. His educational background includes a Ph.D. in Econometrics from the University of Fribourg, followed by research roles at IRE and KOF ETH Zurich. His academic journey reflects deep engagement with statistical methodology and applied economic research. Donzé's primary research interests lie in applied statistics, particularly survey methodology, fuzzy statistics, imputation, causal inference, matching techniques, and wage discrimination analysis . He has made significant contributions to the development and application of fuzzy statistical tools, especially in defuzzification and fuzzy regression. His recent publications (2019–2025) demonstrate a consistent focus on fuzzy confidence intervals, fuzzy p-values, fuzzy ANOVA, and fuzzy regression models , often applied to real-world datasets like SHARE and Swiss SILC. These works emphasize robust statistical inference under uncertainty and contribute to both theoretical and applied advancements in fuzzy statistics. Among his scientific recognitions is the Best Student Paper Award at IJJCI 2020 . He has also edited special issues and contributed to leading journals and conferences in computational intelligence and fuzzy systems. Donzé has been involved in numerous research and teaching initiatives, including grants from the Swiss National Science Foundation, mentoring at the Swiss Study Foundation, and leadership in statistical societies. He has supervised research projects and collaborated with institutions such as Nestlé, the Swiss Federal Statistical Office, and pharmaSuisse. He is actively involved in academic and professional communities, serving as president of the Education and Research section of the Swiss Statistical Society and contributing to the development of statistical infrastructure in social sciences.

Saida HeshmatiView profile

Assistant Professor

• Positive Relationships & Love
• Human Flourishing Across the Lifespan
• Longitudinal Analysis
• +4 more

Saida Heshmati is an Assistant Professor of Psychology in the Division of Behavioral & Organizational Sciences at Claremont Graduate University, specializing in positive developmental psychology. Her research examines how optimal development unfolds across the lifespan, particularly in at-risk populations, using cutting-edge methodologies including ecological momentary assessment, network analysis, and cultural consensus theory. Her research focuses on human flourishing across the lifespan , positive relationships and love , and longitudinal analysis of well-being. Heshmati employs innovative approaches such as experience sampling methods, observational analysis, and wearable physiology monitors to understand moment-to-moment well-being dynamics. Her work bridges developmental psychology, cross-cultural studies, and positive psychology to explore how cultural contexts shape love experiences and well-being outcomes. Recent publications reveal strong emphasis on love perception across cultures , daily well-being tracking , and methodological innovations in psychological assessment. Her 2025-2024 work shows growing focus on cross-cultural love studies, immigrant well-being, and dynamical systems approaches to psychological processes. International Positive Psychology Association (IPPA) 2023 Early Career Researcher Award John Templeton Foundation Grant #63364 (2024-2028): "Embracing Love Across Cultures: Decoding Cultural Beliefs on Love and Their Impact on Wellbeing" Heshmati directs the Well-Being & Developmental Methods Research Lab and leads a major 5-year cross-cultural study across six countries (India, Japan, Brazil, Saudi Arabia, Spain, Kenya) examining everyday love experiences. Her Templeton-funded project represents significant grant acquisition focused on transdisciplinary love research. She teaches courses including "Positive Relationships Across the Lifespan" and "Positive Education, The Science of Human Flourishing" while mentoring graduate researchers through her lab. The Well-Being & Developmental Methods Research Lab operates two major initiatives: the Cross-Cultural Love Project and the main lab focused on developmental methods. The lab employs experience sampling methods, day reconstruction techniques, and dynamical systems modeling to study well-being indicators across diverse populations. Current team includes graduate students, faculty collaborators, and undergraduate research assistants working on multi-country data collection and analysis.

• Applied Econometrics
• Empirical Development Economics
• Political Economy
• +6 more

Kausik Chaudhuri is a Professor in the Leeds University Business School at the University of Leeds , specializing in Applied Econometrics , Empirical Development Economics , and Political Economy . He received his BSc and MSc from the University of Calcutta and MA/PhD from the State University of New York at Albany .

Paul SarbescuView profile

Associate Professor

• Transport Psychology
• Traffic Behavior
• Dangerous Driving
• +7 more

Assoc. Univ. Dr. Paul Sarbescu is a tenured Associate Professor in the Department of Psychology at the Faculty of Sociology and Psychology, West University of Timișoara (UVT). He has been a teaching staff member since 2008 and achieved tenure in 2015. He holds a doctorate in Psychology from the University of Bucharest (2013) and completed his undergraduate and master's studies at UVT, later obtaining formal qualification in psychology in 2018. His primary research focus lies in Transport Psychology , particularly examining dangerous and aggressive driving behaviors, personality predictors of traffic violations, and implicit cognitive processes in driving. He employs both self-report and non-self-report methodologies, contributing significantly to the psychometric validation of psychological tools in Romanian contexts. The recent publications (2022–2014) reflect a consistent trajectory in traffic psychology, personality assessment, and methodological rigor. Key themes include the role of anger and impulsivity in speeding, the development of implicit measures for risky driving, cross-cultural validation of driver behavior questionnaires, and the application of personality models to traffic outcomes. His work bridges individual differences with real-world behavioral outcomes in transportation. His scientific contributions have been recognized with several awards: 2019 – Professor Bologna Award (ANOSR) 2018 – “Gabriela Colţescu” Award for Social and Political Sciences (UVT Excellence Gala) 2016 – Award for exceptional results in scientific research (“Orizonturi Universitare” Association & Romanian Academy) 2013 – APIO Award for best research in Work and Organizational Psychology Paul Sarbescu teaches across academic levels, including Psychological Statistics and Psychology Applied to Transport at the bachelor's level, Psychodiagnostics Applied in Transport and Analysis of Road and Work Accidents in the PMOT master's program, and Applied Statistics in Behavioral Sciences in the doctoral school. He also authored the book Applied Statistics in Psychology: Application Manual (2010). His research is supported by active publication in high-impact journals and contributions to international encyclopedias, indicating sustained scholarly engagement and mentorship potential.

Seger BreugelmansView profile

Associate Professor

• Greed
• Regret
• Cross-Cultural Comparisons
• +3 more

Seger Breugelmans is an Associate Professor at Tilburg University's Department of Social Psychology (Tilburg School of Social and Behavioral Sciences). His research focuses on emotion measurement, cross-cultural comparisons, greed, and social dilemmas. He has contributed to over 100 publications since 1998, with recent work exploring the moral dimensions of regret and greed's ethical implications. His projects include the Compose 3.0 initiative (2023–2025), addressing smart freight and decision-making in logistics. Notable datasets include studies on envy-driven schadenfreude and cultural variations in pride expression. Breugelmans collaborates globally, with active research in the Netherlands, Russia, and Turkey. His research themes coalesce around understanding how emotions like guilt, regret, and greed shape social behavior across cultures. Recent articles highlight greed's role in economic outcomes and moral dilemmas, while earlier work addressed poverty's psychological impacts. He co-authored chapters in Handbook of Ethics and Social Psychology (2025), advancing theories on moral emotions. Despite prolific output, no explicit awards are cited, but his work is widely cited and accessed (e.g., 360+ downloads for 'Greed: What is it good for?'). His advising spans 11 supervised works, though specific student names are not listed. Active collaborations include projects on multiculturalism, retirement decision-making, and experimental asset markets. His lab's focus on emotion-driven behavior integrates experimental methods with cross-cultural frameworks, yielding insights into societal and individual dynamics.

C. Shawn GreenView profile

Professor

• Cognitive Psychology
• Perceptual Learning
• Cognitive Neuroscience
• +9 more

Dr. C. Shawn Green is a Professor in the Department of Psychology at the University of Wisconsin–Madison , where he leads the Learning and Transfer Lab . His research investigates human learning across perceptual, cognitive, and motor domains, with a focus on transfer, rate, and depth of learning. He frequently employs video games, psychophysics, and cognitive training paradigms to explore general learning principles. University: University of Wisconsin–Madison School: College of Letters and Science Department: Department of Psychology Position: Professor Lab: Learning and Transfer Lab Dr. Green’s research centers on cognitive and perceptual learning , particularly how action video game experience enhances attention, perception, and cognitive control. His work explores transfer of learning —why some training generalizes while other skills remain task-specific—and investigates individual differences in learning rates. He also studies motivation to learn , linking exploration-exploitation dynamics to real-world decision-making. His lab uses behavioral experiments, psychophysics, and collaborations with neuroscientists to uncover the mechanisms behind learning enhancement. Analysis of his recent publications (2023–2025) reveals a strong focus on video games and cognition , transfer of learning , educational applications , and methodological innovation (e.g., PLFest platform). There is also growing interest in esports , planning assessment , and expectancy effects in training. His work bridges cognitive science, education, and public policy. Dr. Green actively mentors graduate and undergraduate students and collaborates widely. He values holistic admissions and encourages co-mentorship across psychology subfields. He has served as Editor-in-Chief of the Journal of Cognitive Enhancement and contributes to policy discussions on digital media and learning. Learning and Transfer Lab: Investigates general learning principles using video games and psychophysics PLFest: Open platform for perceptual learning research Collaborations: Extensive work with Daphne Bavelier, Adam Gazzaley, and others Policy Engagement: Contributed to reports on video games, education, and cognitive training

Kevin HarmonView profile

Assistant Professor

• User Experience (UX)
• Decision Making
• Information Systems
• +5 more

Kevin Harmon serves as Assistant Professor in the Information Systems Department at the University of Arkansas' Walton College of Business. His research examines system delays' impact on user performance and experience across diverse technological contexts, bridging psychology and information systems. Education: Ph.D. in Management Information Systems, Texas Tech University (2022) MBA, Texas Tech University (2020) M.S. in Data Science, Texas Tech University (2018) M.A. in Psychology, Texas Tech University (2015) B.S. in Psychology, Truman State University (2012) Dr. Harmon's research integrates cognitive psychology with information systems to investigate latency effects on human-technology interaction. His work spans NeuroIS, UX design, and IT gender gap analysis, revealing critical insights about decision-making under system constraints and demographic disparities in technology careers. Current projects examine how artificial delays affect fake news credibility and neural adaptation during performance degradation. As an educator, he teaches Business Analytics to MBA and Executive MBA students, emphasizing data-driven decision frameworks. His scholarly contributions appear in premier journals including Management Information Systems Quarterly and Journal of the Association for Information Systems , where he also serves as ad-hoc reviewer. Research trends in his 12 most recent publications (2013-2024) demonstrate consistent focus on cognitive aspects of human-computer interaction, evolving from foundational memory studies toward contemporary NeuroIS investigations of system latency. His work increasingly incorporates intersectional analysis of gender/ethnicity in IT careers while maintaining rigorous experimental methodology. Dr. Harmon actively contributes to academic discourse through editorial reviews and professional membership in the Association for Information Systems, advancing methodological standards in information systems research.