جست‌وجوی استاد و پژوهشگر

Karthik Panchanathanمشاهده پروفایل

دانشیار

• Cooperation and Social Evolution
• Cultural Evolution
• Evolution of Learning and Development
• +۲ مورد دیگر

Karthik Panchanathan is an Associate Professor in the Department of Anthropology at the University of Missouri , where he also serves as Director of the Evolution and Social Science Group . His research spans evolutionary anthropology, focusing on cooperation, cultural evolution, developmental plasticity, and metascience. Current affiliation: University of Missouri Academic role: Associate Professor Research Interests: Cooperation and Social Evolution Cultural Evolution Evolution of Learning and Development Metascience Philosophy of Biology Recent publications (2024-2016) reveal expertise in: Modeling sensitive periods in development Evolutionary game theory and indirect reciprocity Metascience and scientific methodology Human behavioral ecology Developmental trade-offs and plasticity Interdisciplinary approaches to evolutionary theory Teaching includes: Courses on cultural anthropology Evolutions of human nature Theory in anthropology Department capstone seminar Contact Information: Email: PanchanathanK@missouri.edu Location: 225 Swallow Hall, Columbia, MO Office Hours: Tuesday 11 am-12 pm, Wednesday 2 pm-3 pm

Dipak Deyمشاهده پروفایل

استاد

• Bayesian analysis
• Bioinformatics
• Biostatistics
• +۸ مورد دیگر

Dipak Dey is a Professor in the Department of Statistics at the University of Connecticut . His work bridges theoretical and applied statistics, with a focus on Bayesian methodologies and computational statistics. Affiliations : University of Connecticut, Department of Statistics Contact : dipak.dey@uconn.edu , Office: AUST 327, Phone: (860) 486-4755 His research interests span Bayesian analysis , Biostatistics , Computational statistics , Statistical genetics , and Spatio-temporal modeling . He has pioneered techniques in spatial curvature processes and scalable Bayesian algorithms for large datasets. Recent publications highlight his contributions to Bayesian spatial modeling (blockNNGP, curvature processes), survival analysis (skew-t distributions, cure rate models), and computational statistics (variable selection in Gaussian processes, fast inference algorithms). Applications include insurance data , epidemiology , and environmental statistics . Scientific Awards : Board of Trustees Distinguished Professor (University of Connecticut) He actively collaborates on interdisciplinary projects and mentors researchers in advanced statistical methodologies for complex data structures.

Dakota W. Cintronمشاهده پروفایل

استادیار

• Latent Variable Modeling
• Measurement Theory
• Causal Inference
• +۵ مورد دیگر

Dakota W. Cintron is an Assistant Professor in the Division of Behavioral and Organizational Sciences at Claremont Graduate University. He specializes in advanced quantitative methods in psychology, focusing on latent variable modeling, measurement theory, and causal inference. Education: BS MS EdM PhD Research interests include studying how psychosocial factors influence well-being and health outcomes over time, particularly in at-risk populations. He applies methods like growth mixture modeling, alignment optimization, and natural language processing to analyze social disparities, emotional dynamics, and long-term health trends. Selected publications highlight his work on heterogeneous treatment effects in social policies, intersectional measurement invariance, and the use of big data for psychological modeling. His methodological contributions address classification accuracy in mixture models and enhance policy evaluation frameworks. Teaching: Psych 315E: Multilevel Modeling Psych 315NN: Bayesian Statistics Psych 302: Research Methods (PhD)

Oğuz Köklüمشاهده پروفایل

مدرس

• Statistics Education
• Probability Education
• Mathematics Teacher Education
• +۳ مورد دیگر

Oğuz Köklü is a Lecturer in the Department of Mathematics Education at Marmara University. He earned his Ph.D. in Mathematics Education from the University of Georgia (2017), M.S. in Mathematics and Science Education from Boğaziçi University (2012), and B.S. in Mathematics Teaching from Boğaziçi University (2008). Ph.D.: Mathematics Education, University of Georgia (2017) M.S.: Mathematics and Science Education, Boğaziçi University (2012) B.S.: Mathematics Teaching, Boğaziçi University (2008) His research focuses on Statistics Education , Probability Education , and Mathematics Teacher Training , with particular emphasis on Bayesian reasoning , statistical variability , and geometric proportionality . Recent publications analyze preservice teacher misconceptions and technology-enhanced instruction methods. Köklü’s work includes grants from TUBITAK and NSF , such as a 2023 workshop leader role for a TUBITAK-funded project on data science education for gifted students. He has advised 5 Master’s students and contributed to curriculum design frameworks in Turkish journals.

• Data Science
• Data Analytics
• Data Visualization
• +۱۲ مورد دیگر

Mohammad Shan-A-Khuda is a Lecturer in the Department of Computing at the School of Built Environment, Engineering and Computing, Leeds Beckett University. He holds a PhD in Data Science and an MSc in multidisciplinary informatics from the University of Leeds. His academic work spans teaching, research, and interdisciplinary collaboration in computing and data science. Education: PhD in Data Science, Leeds Beckett University MSc in Multidisciplinary Informatics, University of Leeds Mohammad's research focuses on data analytics, visualization, and statistical modelling of large datasets, particularly in social and public health domains. He applies multilevel and machine learning models to understand fear of crime, cybercrime victimization, road accidents, and dementia. His work bridges computing, social science, and policy, emphasizing real-world impact and interdisciplinary collaboration. The 15 most recent articles reflect a strong trend in applying data science to societal challenges, using machine learning, statistical modelling, and visualization. Key domains include criminology, public health, transportation safety, and policy analysis, with methodologies centered on supervised learning, geospatial analysis, and multilevel modelling. Scientific Awards: No formal awards mentioned in the text. Mohammad actively supervises MSc dissertation projects and mentors students in areas such as crime prediction, traffic visualization, and dementia modelling. He has led research projects with West Yorkshire Police, contributing to institutional research impact and funding potential. His teaching spans core computing topics including programming, databases, algorithms, and mathematics for data science, reflecting a comprehensive academic profile. He is involved in research initiatives that integrate data science with public sector applications, particularly in collaboration with law enforcement and health domains, forming applied research teams focused on societal benefit and policy relevance.

• Science Education
• Educational Psychology
• STEM Education
• +۳ مورد دیگر

Semra Sungur is a Professor at the Middle East Technical University, affiliated with the Faculty Of Education, Mathematics And Science Education and the Department of Science Education. Her research focuses on science education, educational psychology, and STEM pedagogical practices. She has published extensively on student motivation, argumentation skills, epistemological beliefs, and teacher professional development. Key research interests include: Science teacher training and classroom environments Student engagement and self-efficacy in STEM Impact of media literacy and documentary films on scientific reasoning Gender and socioeconomic influences on educational outcomes Her recent work emphasizes Utility value interventions in science education Argumentation schemes in middle school contexts Multilevel analyses of science achievement factors Integration of history of science into curricula Prof. Sungur has advised 34 theses and holds significant research metrics including a WoS H-index of 19 and Scopus H-index of 1922. She actively contributes to educational policy through validated scales like the Engagement Questionnaire for Science Classes and Attitude Toward Sustainable Development Scale .

Francesc Xavier Villalba Nicolasمشاهده پروفایل

استاد

• Romance Syntax
• Semantics
• Pragmatics
• +۶ مورد دیگر

Francesc Xavier Villalba Nicolas is a Professor at the Department of Catalan Studies, Universitat Autònoma de Barcelona, where he leads research at the Center for Theoretical Linguistics. His academic career spans over two decades since earning his PhD in Catalan Philology from UAB in 2000, with significant contributions to theoretical linguistics. His research focuses on three interconnected areas: Romance syntax and its interfaces with semantics and pragmatics, exclamative sentences across Romance languages, and the functional architecture of sentence structure. Villalba has published extensively in these fields, including a book on word order contrast and numerous reference chapters in authoritative linguistic handbooks. Villalba's scholarly impact is evidenced by 116+ research outputs, including recent publications in 2024 that explore the syntax-pragmatics interface of exclamative markers and the diachronic evolution of discourse markers in Spanish. His work demonstrates consistent engagement with both theoretical frameworks and experimental methodologies, particularly in examining how exclamations function within discourse and contribute to the common ground. 21 publications in ISI Social Sciences Citation Index (96 citations, h-index 5) 14 publications in Scopus (85 citations, h-index 4) 1167 citations in Google Scholar (h-index 18) As an academic supervisor, Villalba has directed multiple PhD theses on topics including resumptive relative clauses, exclamatives in Catalan, and complementizer deletion in Spanish. He currently leads the EXPLETIVENESS AND EXPRESSIVE MEANING project (2024-2027) as Principal Investigator, continuing his investigation into the expressive dimensions of language structure. His research program bridges theoretical linguistics with empirical approaches, making significant contributions to our understanding of how syntax interfaces with meaning and discourse.

Peter M Steinerمشاهده پروفایل

استاد

• Causal Inference
• Replication Design
• Survey Methodology
• +۳ مورد دیگر

Peter M. Steiner is a Professor in the Department of Human Development and Quantitative Methodology at the University of Maryland, specializing in quantitative methodology, measurement, and statistics (QMMS). He previously held faculty positions at the University of Wisconsin-Madison (2010–2019), the Institute for Policy Research at Northwestern University (2007–2010), and the Institute for Advanced Studies in Vienna (1997–2007). He earned a Ph.D. and M.Sc. in Statistics from the University of Vienna and an M.Sc. in Economics from Vienna University of Economics and Business. His research focuses on causal inference methodologies, including causal replication designs, quasi-experimental techniques, and factorial survey methods. Key areas include double robust estimation, propensity score analysis, mediation analysis, and addressing selection bias. He has contributed to improving replication practices in social sciences and developed frameworks for assessing correspondence between experimental and non-experimental results. Education: Ph.D. in Statistics, University of Vienna M.Sc. in Economics, Vienna University of Economics and Business M.Sc. in Statistics, University of Vienna He received the prestigious Causality in Statistics Education Award from the American Statistical Association in 2019. His work emphasizes methodological rigor in evaluating policy interventions and experimental designs, with applications in education and social sciences. Courses taught include Graphical Models for Causal Inference, Causal Inference & Evaluation, and Causal Mediation Analysis. Key Contributions: Pioneered within-study comparison designs for causal replication Developed DAG-based causal modeling frameworks Advanced multilevel propensity score methods His research portfolio includes over 50 peer-reviewed articles in top journals like Psychological Methods , Journal of the American Statistical Association , and Sociological Methods & Research . Current projects focus on integrating machine learning with causal inference and improving reproducibility in social science research.

Soheil Hemmatiمشاهده پروفایل

استادیار

• Mathematical Optimization
• Healthcare Decision-Making
• Stochastic Optimization
• +۴ مورد دیگر

Soheil Hemmati is an Assistant Professor in the Department of Industrial & Systems Engineering at the University of Oklahoma. His research focuses on mathematical optimization models and their applications in healthcare decision-making, particularly in cancer care. He has expertise in stochastic optimization, integer programming, and bilevel optimization techniques for clinical applications. Ph.D. in Industrial and Systems Engineering from the University of Florida M.S. and B.S. in Industrial Engineering from Sharif University of Technology Dr. Hemmati's work spans cancer screening optimization, adaptive radiation therapy planning, and health policy modeling. He has developed novel approaches for organ-at-risk sparing, personalized screening schedules, and toxicity prediction frameworks using machine learning. His research intersects with cyber-physical systems through interdiction modeling applications. His recent publications in journals like American Journal of Obstetrics and Gynecology and Physics and Imaging in Radiation Oncology demonstrate his focus on clinical implementation challenges. He actively collaborates with cancer centers and has mentored students including Grant M. Benson (moving to UC Berkeley) and Kiana Amani. 2024 ASTRO Meeting Abstract Acceptance Dr. Hemmati leads a research group at the Carson Engineering Center, with lab collaborations spanning radiation oncology, biomedical engineering, and public health domains.

James LeBretonمشاهده پروفایل

استاد

• Personality Psychology
• Organizational Behavior
• Psychometrics
• +۳ مورد دیگر

James LeBreton is a Professor of Psychology at Pennsylvania State University specializing in Industrial-Organizational Psychology, where he serves as the SoDA Dual Title Degree Liaison and Primary Investigator of the Measurement, Applied Psychology, and Statistics (MAPS) Lab. His research bridges personality theory and organizational behavior with methodological innovation in psychometrics. Education: Ph.D. in Psychology, University of Tennessee (2002) LeBreton's foundational work centers on the Conditional Reasoning Theory of Personality, which posits that implicit motives (aggression, achievement, power) generate cognitive biases that drive behavior. His research demonstrates how these implicit processes influence counterproductive work behavior, leadership effectiveness, team dynamics, and job attitudes. Complementing this, his methodological expertise spans meta-analysis, multilevel modeling, and test validation, evidenced by his editorship of Organizational Research Methods and co-editorship of the APA Handbook on Multilevel Theory, Measurement, and Analysis . His recent publications reveal three converging trends: (1) international validation of conditional reasoning measures across cultural contexts, (2) refinement of implicit assessment techniques to capture dark personality traits, and (3) methodological critiques addressing interaction effects and measurement equivalence in organizational research. This work consistently prioritizes practical applications for personnel selection and workplace interventions. LeBreton actively mentors graduate students in the Industrial-Organizational program through the MAPS Lab, fostering research at the intersection of personality assessment and statistical methodology. His laboratory serves as a hub for developing psychometric tools that translate theoretical constructs into actionable organizational insights, with current projects focusing on cross-cultural test adaptation and bias mitigation in personality measurement.

• Cognitive Behavioral Stress Management
• Psychological Interventions
• HIV/AIDS
• +۴ مورد دیگر

Sierra A. Bainter, Ph.D. , is an Associate Professor in the Department of Psychology at the University of Miami's College of Arts and Sciences . She specializes in digital psychological interventions, syndemics, and health disparities research. Key affiliations: Sylvester Comprehensive Cancer Center, University of Miami Research focus: Cognitive Behavioral Stress Management (CBSM), HIV/AIDS, Latino health, network analysis of psychosocial problems Scientific contributions include developing engagement metrics for asynchronous mental health websites and analyzing multilevel barriers to HIV prevention. Recent publications examine: Digital interventions for cancer patients Syndemic effects on HIV outcomes Neighborhood influences on Latino health Bayesian statistical approaches in behavioral research Scientific Awards Florida Department of Health Grant (#6BC06) Sylvester Comprehensive Cancer Center Bridge Grant (#PG014720) As a grants recipient, she has received funding from NIH and affiliated institutions. Her lab collaborates with medical schools to translate psychological findings into clinical applications.

• Psychometrics
• Social Psychology
• Cross-Cultural Psychology
• +۱۲ مورد دیگر

Seda Can is a Professor at the Department of Psychology, Izmir University of Economics, Turkey. Her academic career focuses on psychometrics, social psychology, and behavioral science, with methodological expertise in structural equation modeling and measurement equivalence. Ph.D. in Psychometrics from Ege University (2010). Visiting Researcher at Utrecht University (2011-2012) in Methodology and Statistics in Social Sciences. M.A. in Measurement and Evaluation from Middle East Technical University (2003). B.A. in Psychology from Hacettepe University (1999). Her research spans cross-cultural studies on interpersonal touch, infidelity responses, and pro-environmental behaviors. She investigates personality traits influencing risky driving and predictors of physical attractiveness globally. Recent work emphasizes environmental psychology, including waste separation practices and altruistic attitudes toward waste pickers. Methodological contributions involve comparing Bayesian and maximum likelihood estimations in multilevel confirmatory factor analysis and analyzing collinearity in latent variables. Publications from 2010-2025 cover psychometrics, cognitive psychology, and social psychology, with trends toward behavioral science and cross-cultural analysis.

• Cognitive Aging
• Longitudinal Data Analysis
• Structural Equation Modeling
• +۶ مورد دیگر

Paolo Ghisletta is a Full Professor of Psychology at the University of Geneva's Faculty of Psychology and Educational Sciences. With a distinguished career spanning over two decades at the university, he has progressed from Assistant Professor to his current position as Full Professor since 2015. His academic journey includes significant research contributions in cognitive aging, methodological approaches to longitudinal data analysis, and the study of individual differences in cognitive development across the lifespan. Ph.D. in Quantitative Psychology and Methodology, University of Virginia (1999) MA in Quantitative Psychology and Methodology, University of Virginia (1996) BA Mathematics and BA Psychology, Clarion University, Pennsylvania (1994) Ghisletta specializes in methodologies for analyzing multivariate data in lifespan development research, with particular expertise in Structural Equation Models and Multilevel Models. His work examines cognitive aging in relation to health, activities, and sensory functioning, as well as the management of psychological resources in adults and the elderly. He has made significant contributions to understanding inter- and intra-individual variability over the lifespan, exploring how these variations relate to cognitive performance, health outcomes, and aging trajectories. An analysis of Ghisletta's recent publications (2022-2025) reveals a strong focus on cognitive aging, particularly examining memory systems, longitudinal changes, and the relationship between cognitive performance and health outcomes. His methodological expertise is evident in numerous papers on statistical approaches for analyzing longitudinal data. A recurring theme is the investigation of individual differences in cognitive aging trajectories and their predictors, including cognitive reserve, social factors, and genetic influences. His research often employs sophisticated statistical techniques to disentangle complex relationships between cognitive variables across time. Ghisletta maintains an active research program with numerous collaborations across international institutions, particularly within European aging research consortia. His work has significant implications for understanding normal cognitive aging processes and identifying factors that may contribute to healthy cognitive aging or vulnerability to decline.

Gustav Nilsonneمشاهده پروفایل

پژوهشگر

• Neuroscience
• Metascience
• Psychoneuroimmunology
• +۴ مورد دیگر

Gustav Nilsonne is a researcher affiliated with Stockholm University (Department of Psychology, Division for Psychoneuroimmunology) and holds an associate professor position at Karolinska Institutet , while also being affiliated with Stanford University . His work bridges neuroscience and metascience , focusing on sleep and diurnal rhythms , brain-immune communication, and methodological rigor in scientific research. He actively investigates reproducibility, open science practices, and analytical pitfalls in longitudinal studies. Neuroscience Research : Explores bidirectional communication between the brain and immune system, including studies on stress-related diagnostics like exhaustion disorder. Metascience Contributions : Analyzes statistical artifacts in ability tilt studies, self-esteem-depression causal links, and publication ethics, advocating for robust analytical frameworks. Recent Publications (2022–2024) span psychoneuroimmunology, reproducibility crises, and methodological interventions like discrepancy review in peer assessment. Collaborative efforts, including the Psychological Science Accelerator and global pandemic response datasets, highlight his commitment to cross-cultural and large-scale empirical validation. His work challenges assumptions in genetic/environmental interpretations and emphasizes transparency in academic publishing. Leadership & Ethics : Contributed to debates on editorial self-publication practices, psychoneuroimmunology methods, and policy recommendations for improving scientific reliability. No listed students or awards in the provided text.

Debra Zuppinger-Dingleyمشاهده پروفایل

پژوهشگر

• Biodiversity
• Plant Ecology
• Community Ecology
• +۳ مورد دیگر

Debra Zuppinger-Dingley serves as Research Associate in the Department of Evolutionary Biology and Environmental Studies at the University of Zurich (2014–present) and Program Manager for the PhD Program in Ecology at the Life Science Zurich Graduate School (2015–present). Previously, she led the University Research Priority Programme Global Change and Biodiversity as General Manager (2017–2024) and Scientific Advisor (2015–2016). Her academic foundation includes: B.Sc. Hons in Terrestrial Ecology and Biogeography and B.Sc in Cellular Biology and Psychology from University of KwaZulu-Natal, South Africa M.Sc. in Environmental Sciences, University of Zurich (2008–2009) Ph.D. in Ecology, Life Science Zurich Graduate School (2010–2014) Dr. Zuppinger-Dingley investigates biodiversity maintenance mechanisms with emphasis on: Plant biodiversity-ecosystem functioning relationships and ecological service provisioning Invasion ecology dynamics and community assembly processes Plant competition/coexistence mechanisms and plant-soil feedback loops Integration of biodiversity science with global change policy frameworks Her publication trajectory (2011–2025) shows strategic evolution from foundational plant ecology to interdisciplinary social-ecological systems research, with 60% of recent papers involving international collaborations across 12 countries. This reflects growing emphasis on translating ecological research into policy-relevant knowledge. As PhD Program Manager, she oversees graduate curriculum development and student mentorship for 100+ ecology doctoral candidates. Her URPP leadership coordinated €4.2M in interdisciplinary research on climate-biodiversity interactions, resulting in 50+ collaborative publications and policy briefs for Swiss environmental agencies. She maintains active partnerships with ETH Zurich's Environmental Systems Science department and participates in EU biodiversity networks, providing students with access to alpine field stations and remote sensing infrastructure.