جست‌وجوی استاد و پژوهشگر

Zehang Richard Liمشاهده پروفایل

استادیار

• Statistical Methods
• Demography
• Epidemiology
• +۷ مورد دیگر

Zehang Richard Li is an Assistant Professor in the Department of Statistics at the University of California Santa Cruz. His research focuses on statistical methods for demography, epidemiology, and global health, with expertise in latent variable modeling, space-time models, survey sampling, data integration, and weakly supervised learning. He develops workflows and pipelines for complex statistical analysis and real-world data-driven decision-making. Ph.D. in Statistics from the University of Washington (advisor: Tyler McCormick) Postdoctoral Researcher at Yale School of Public Health (Department of Biostatistics, advisor: Forrest Crawford) His work emphasizes high-dimensional data and uncertainty quantification in prevalence mapping. He leads the development of the SUMMER R package and SAE4Health platform, including ShinyApps for subnational health indicator analysis. Current projects address farmworker health under climate change through a UCOP grant and Bayesian frameworks for integrating verbal autopsy data via NIH funding. Recent publications highlight methodological advances in small area estimation, verbal autopsy analysis, and pandemic modeling. Key article themes include: Bayesian hierarchical modeling and tensor decomposition (2025) Domain adaptation for cross-population cause assignment (2024) Verbal autopsy validation and diagnostic accuracy (2023) Bayesian multilevel poststratification for disease prevalence (2022) Respiratory virus transmission dynamics and immune mechanisms (2021) Grants supporting his research include: National Institutes of Health Melinda and Bill Gates Foundation Vital Strategies Hellman Fellows Program University of California Office of President (UCOP) UCSC Committee on Research He advises Ph.D. students Yu (Zoey) Zhu, Qianyu Dong, Sho Kawano, and Toshiya Yoshida, all of whom have received academic recognition for their work on Bayesian models, small area estimation, and prevalence mapping.

Jayur Madhusudan Mehtaمشاهده پروفایل

دانشیار

• Environmental Archaeology
• Coastal Hazards
• Human-Environment Relationships
• +۲ مورد دیگر

Jayur Madhusudan Mehta is an Associate Professor in the Department of Anthropology at Florida State University, where he also serves as Undergraduate Program Director. His research specializes in human-environment interactions, coastal archaeology, and Indigenous heritage preservation, with field projects spanning the Gulf Coast and Mississippi Delta. Mehta holds a Ph.D. in Anthropology from Tulane University (2015), an M.A. from the University of Alabama (2007), and a B.A. from the University of North Carolina (2004). His interdisciplinary work integrates geoarchaeology, ethnohistory, and environmental reconstruction to study how past societies responded to ecological challenges. Current initiatives include mediating coastal hazards for Indigenous communities, restoring ancient fisheries through paleoenvironmental analysis, and documenting plantation archaeology at Evergreen Plantation in Louisiana. Mehta's publications predominantly explore climate adaptation, cultural landscape resilience, and monumentality in Mississippian societies. His methodological approaches combine remote sensing, sedimentology, and spatial analysis to reconstruct historical ecologies and settlement patterns. He actively recruits graduate students for coastal archaeology projects and leads field schools focused on African Diaspora archaeology. As principal investigator for multiple research consortia, Mehta collaborates with Indigenous communities and federal agencies to develop culturally informed conservation strategies.

J.N.K. Raoمشاهده پروفایل

استاد پژوهشی

• Statistics
• Survey Sampling
• Statistical Inference
• +۳ مورد دیگر

J.N.K. Rao is a Distinguished Research Professor in the Department of Mathematics & Statistics at Carleton University. A leading expert in survey sampling and statistical inference, he has made groundbreaking contributions to small area estimation (SAE) and data integration methodologies. Research Focus: Specializes in survey methodology, poverty mapping, Bayesian inference, and empirical likelihood techniques. Honors: Gold Medal of the Statistical Society of Canada (1993), Fellow of the Royal Society of Canada (1991), Waksberg Award (2005), SAE Outstanding Achievement Medal (2017). His recent work explores model-based SAE, combining probability and non-probability samples, and improving inference validity through robust calibration. Awards highlight his decades-long impact on statistical theory and practice. Email: jrao@math.carleton.ca

Larry V. Hedgesمشاهده پروفایل

استاد

• Statistical Methods in Social Sciences
• Meta-Analysis
• Education Policy Evaluation
• +۳ مورد دیگر

Larry V. Hedges is the Board of Trustees Professor of Statistics and Social Policy at Northwestern University's School of Education and Social Policy (SESP), one of the university's most distinguished academic positions. He also holds affiliations with the Institute for Policy Research and previously served as the Stella M. Rowley Professor at the University of Chicago. His work focuses on statistical methods for meta-analysis, evaluation research, and interdisciplinary applications across social, medical, and biological sciences. Education: PhD (1980), Mathematical Methods in Educational Research, Stanford University MA (Statistics), Stanford University BA (Mathematics), University of California, San Diego Research Interests: Development and application of statistical techniques for meta-analysis, causal inference, and evidence-based policy evaluation. Notable areas include frameworks for international comparative education studies, cost analysis of systematic reviews, and gender/ethnic gaps in academic achievement. Awards: Yidan Prize for Education Research (2018) – World's largest education award Sells Award for Distinguished Multivariate Research (2014) Statistician of the Year (2013) Fellowships: American Academy of Arts and Sciences, American Statistical Association, National Academy of Education Professional Contributions: Co-founder of the Society for Research on Educational Effectiveness, member of the National Education Sciences Board, and contributor to major initiatives like the What Works Clearinghouse. His work emphasizes rigorous methodological standards across disciplines. Labs/Teams: Leads methodological research through SESP and collaborative projects at the Institute for Policy Research, focusing on policy-relevant statistical innovations.

Xin Wangمشاهده پروفایل

استادیار

• Spatial Data Analysis
• Bayesian Statistics
• Survey Sampling
• +۲ مورد دیگر

Xin Wang is an Assistant Professor in the Department of Mathematics and Statistics at San Diego State University. Her research develops statistical methods for spatial data analysis, Bayesian inference, and survey sampling with applications in environmental science and public health. Dr. Wang's methodological work includes clustered coefficient regression models for small area estimation, spatial heterogeneity detection techniques, and spatio-temporal cluster analysis. Her applied research examines aquatic toxicity assessment, environmental monitoring, and warranty claim patterns using these advanced statistical approaches. She teaches graduate courses in mathematical statistics and survey methodology. Previously at Miami University, she developed curriculum linking statistical theory with computational implementation. Dr. Wang holds a PhD from Iowa State University and collaborates with researchers in epidemiology, materials science, and ecology on interdisciplinary projects requiring sophisticated data analysis.

Alia Dietschمشاهده پروفایل

دانشیار

• Human cognition and behavior
• Nature-based recreation
• Noncompliance
• +۷ مورد دیگر

Dr. Alia Dietsch serves as an Associate Professor in Parks, Protected Areas, and Natural Resources Management at The Ohio State University's School of Environment and Natural Resources. Her work bridges social science theory with practical conservation applications, focusing on human dimensions of natural resource management. She maintains an active research program collaborating with state and federal natural resource agencies to inform planning, management, and communication efforts. Dr. Dietsch employs social psychological approaches to understand how human cognition influences individual behaviors across various conservation contexts. Her research spans human cognition and behavior, nature-based recreation, noncompliance issues, equity and justice in conservation, public lands management, and human-wildlife interactions, with particular expertise in carnivore-related conflicts. She utilizes advanced methodologies including multilevel modeling, survey sampling, and geospatial analysis to investigate complex human-nature relationships. Her publication record demonstrates consistent scholarly output across high-impact conservation journals, with recent work examining trauma in nature-based leisure, trust in conservation partnerships, wildlife value orientations, and human dimensions of wildlife management. Her research increasingly addresses equity, justice, and power dynamics in conservation decision-making, reflecting evolving societal values toward wildlife. Dr. Dietsch leads the Dietsch Team which has worked extensively on human-nature interactions, carnivore conservation, wildlife management, nature-based experiences, and recreation management on public lands. She directs significant projects including The National Visitor Survey in partnership with the U.S. Fish and Wildlife Service, which has surveyed over 15,000 visitors across 110+ national wildlife refuges to inform management decisions. She also contributes to America's Wildlife Values project and the Environmental and Social Sustainability Lab. As an educator, Dr. Dietsch teaches ENR 2300 (Society and Natural Resources), ENR 3600 (Recreation Management on Public Lands), and ENR 6510 (Research Design for Environmental Social Sciences), mentoring numerous graduate students who appear as co-authors on her publications. Her work has practical applications for wildlife managers seeking to understand public perspectives and improve conservation outcomes through evidence-based approaches.

• Social Archaeology
• Settlement Archaeology
• Landscape Archaeology
• +۴ مورد دیگر

Prof. Dr. Johannes Müller holds the Chair for Prehistoric Archaeology and directs the Institute of Pre- and Protohistory at Christian-Albrechts-Universität zu Kiel since 2004. His academic journey includes studies at Freiburg and Edinburgh, a habilitation at FU Berlin, and leadership roles in Bamberg. His research focuses on social archaeology, settlement patterns, and human-environment interactions in European prehistory, particularly the Neolithic and Bronze Age. Müller leads major projects like the DFG Collaborative Research Center 'Scales of Transformation' and the 'Human Development in Landscapes' Graduate School. His fieldwork spans Germany, Poland, Bosnia-Herzegovina, and Ukraine, with excavations at sites like Okoliste and Bruszczewo. He coordinates international initiatives like the Priority Program 'Early Monumentality and Social Differentiation.' Müller is a leading figure in computational archaeology, advancing predictive mapping and geophysical survey techniques. His work bridges archaeology with environmental and demographic sciences, emphasizing interdisciplinary collaboration. Education: PhD and habilitation in Prehistoric Archaeology (Freiburg and Berlin) DAI travel grant and academic roles at Freiburg, Cologne, and Bamberg Research Interests: Müller’s research integrates social archaeology with landscape and environmental studies to explore societal complexity and inequality. Key themes include: Neolithic monumental architecture (e.g., megalithic tombs, fortified settlements) Trypillia mega-sites and their socio-environmental dynamics Climate change impacts on prehistoric societies Computational methods for predictive mapping Collaborations: German Archaeological Institute (DAI) International teams in Poland, Bosnia-Herzegovina, and Ukraine Partnerships with institutions like Poznan University and the State Museum of Sarajevo Labs/Teams: He oversees the Institute’s fieldwork and laboratory facilities, including geophysical surveys and environmental analysis. His team employs cutting-edge techniques like geomagnetic imaging and isotopic dating to reconstruct ancient landscapes.

• Nonparametric function and density estimation
• Shape-restricted inference
• Constrained regression models
• +۲ مورد دیگر

Mary C. Meyer is a Professor in the Department of Statistics at Colorado State University. Her research focuses on nonparametric function and density estimation, particularly under shape restrictions, with applications across ecological modeling, survey methodology, and statistical computing. Education: Ph.D. in Statistics from the University of Michigan (1996) Research Interests: Nonparametric function and density estimation Shape-restricted inference Constrained regression models Bayesian nonparametric methods Penalized isotonic regression Statistical software development Recent Publications show a focus on constrained regression splines, domain mean estimation, and applications in forest dynamics and survey methodology. She has developed several R packages including cgam and tools for cone projections. Grants: Funded by NSF grant DMS-0905656 for research on constrained optimization algorithms. Email Contacts: meyer@stat.colostate.edu and mmeyer@stat.uga.edu

Daniel Layton-Matthewsمشاهده پروفایل

دانشیار

• Geochemistry
• Mineral Exploration
• Isotope Geochemistry
• +۲ مورد دیگر

Daniel Layton-Matthews is an Associate Professor in Geological Science and Geological Engineering at Queen's University. His research program investigates chemical indicators in sedimentary rocks, post-depositional modification of minerals, and geochemical dispersion patterns for mineral exploration. Current research examines trace element signatures in ancient ore systems, with field sites including the Canadian Shield, Australian playa uranium deposits, and marine ferromanganese formations. His group develops analytical methods for in-situ geochemical analysis and isotopic tracing of element migration pathways. Research collaborations span industry partners and government geological surveys. Fieldwork integrates drone-based sampling techniques and advanced laboratory analysis including LA-ICP-MS and isotope ratio measurements.

Partha Lahiriمشاهده پروفایل

استاد

• Survey Sampling
• Small-Area Estimation
• Bayesian Inference
• +۳ مورد دیگر

Partha Lahiri is a Professor at the University of Maryland, College Park, holding dual appointments in the Joint Program in Survey Methodology (JPSM) and the Department of Mathematics . He also serves as an Adjunct Research Professor at the Institute of Social Research, University of Michigan, Ann Arbor. Previously, he was the Milton Mohr Distinguished Professor of Statistics at the University of Nebraska-Lincoln. His expertise spans Survey Sampling , Small-Area Estimation , Bayesian and Empirical Bayes Inference , and Resampling Methods . He has advised organizations such as the United Nations Development Program, World Bank, and Gallup, and contributed to panels like the U.S. Census Advisory Committee. He is a Fellow of the American Statistical Association and the Institute of Mathematical Statistics, and an elected member of the International Statistical Institute. Research interests include methodological advancements in small area estimation, survey data integration, and statistical linkage. His work emphasizes practical applications in policy and public health, including poverty measurement and pandemic-related studies (e.g., mask effectiveness perception during the pandemic). He has authored influential papers on topics like multi-goal prior selection, probabilistic record linkage, and resampling techniques for uncertainty quantification. His leadership roles, including directing JPSM, highlight his commitment to training future survey methodologists. Awards: ASA and IMS Fellowships, ISI Elected Membership Advisory Roles: U.S. Census Advisory Committee, National Academy of Sciences panels Publications Trends: Focus on small area estimation, Bayesian methods, and policy-relevant applications Grants/Projects: Collaborations with international organizations and academic institutions on statistical methodologies Lahiri’s research bridges theoretical statistics and practical survey challenges, with a strong emphasis on data integration and uncertainty estimation in complex systems.

Katherine Kral-O'Brienمشاهده پروفایل

استادیار

• Pollinator Conservation
• Grassland Ecology
• Agroecology
• +۳ مورد دیگر

Katherine Kral-O'Brien is an Assistant Professor at Iowa State University, focusing on pollinator conservation in agroecosystems and grassland ecosystems. Her research integrates ecological principles with practical conservation strategies, emphasizing butterfly and bee populations in managed and natural landscapes. She holds a PhD in Range Science from North Dakota State University, with prior degrees in Wildlife Biology and Range Science. Her work addresses challenges such as invasive species management, climate change impacts, and methodological improvements in ecological surveys. Key affiliations include the Iowa Monarch Conservation Consortium and the Department of Natural Resource Ecology and Management. Recent projects involve evaluating pollinator responses to conservation practices like prescribed burns and habitat restoration. Research themes include spatiotemporal dynamics of monarch butterflies, plant-pollinator network stability, and the ecological roles of large herbivores. She advocates for community-driven conservation and gender equity in STEM through collaborative initiatives. Current opportunities include seasonal research technician roles in Iowa and Minnesota.

• Environmental Economics
• Agricultural Economics
• Economics of Climate Change in Developing Countries
• +۳ مورد دیگر

Dr. Ashar Aftab is an Associate Professor in the Business School and the Institute of Hazard, Risk and Resilience at Durham University. He holds an MSc and PhD from the University of Edinburgh. His research focuses on environmental and agricultural economics, particularly addressing agricultural externalities, climate change impacts in developing countries, and policies to mitigate diffuse pollution and flooding. He designs incentive mechanisms using choice experiments to promote sustainable practices in agriculture. Current work includes flood adaptation policies and spatial targeting for pollution control in agricultural landscapes. Dr. Aftab’s research spans interdisciplinary catchment systems modeling and policy evaluation. His recent publications analyze international environmental agreements, farm household adaptation strategies in Pakistan, and synergies between spatial targeting and precision agriculture. He advises PhD students on environmental and development economics topics. He collaborates with institutions like the Institute of Hazard, Risk and Resilience to address complex environmental challenges. His work emphasizes practical policy solutions for sustainable land use and water resource management in vulnerable regions.

Kerri Vierlingمشاهده پروفایل

استاد

• Avian Ecology
• Fire Ecology
• Disturbance Ecology
• +۳ مورد دیگر

Kerri Vierling is a Professor of Wildlife Resources and Director of the College of Natural Resources (CNR) Graduate Studies at the University of Idaho. She holds a Ph.D. in Biology (1998) and M.A. in Biology (1994) from the University of Colorado, along with a B.A. in Biology from The Colorado College (1990). Her research focuses on avian ecology, disturbance ecology, and the impacts of vegetation structure on wildlife distributions. Her work integrates remote sensing techniques (e.g., LiDAR) to investigate habitat relationships and land use effects on animal populations. Dr. Vierling has received numerous awards for teaching and advising, including the U of I Advising Excellence Award (2017), the CNR External Advisory Board’s Faculty Excellence Award (2017), and multiple College of Natural Resources Outstanding Teacher awards. Her advising mentorship has supported both undergraduate and graduate students in ecological and conservation fields. Her recent research emphasizes fire ecology, climate change vulnerability assessments, and avian biodiversity in temperate forests. Collaborative studies involve analyzing bird assemblages using remote sensing data and exploring pest control services provided by functional bird diversity in agricultural systems. Publications span topics from thermal ecology of tree cavities to landscape-scale habitat modeling. She actively participates in interdisciplinary projects linking ecological data with management strategies, such as optimizing LiDAR applications for wildlife distribution studies. Grants & Funding: Not explicitly listed in text, but inferred through research focus areas. Labs/Teams: Involved with CNR’s wildlife ecology and remote sensing research groups.

Brian Kellerمشاهده پروفایل

استادیار

• Missing Data Analysis
• Bayesian Statistics
• Statistical Computing
• +۳ مورد دیگر

Brian Keller is an Assistant Professor in the Department of Educational, School & Counseling Psychology at the University of Missouri's College of Education & Human Development. His research focuses on statistical methodologies, particularly missing data analysis, Bayesian statistics, structural equation modeling, and multilevel modeling. He is the developer of Blimp statistical software, which supports advanced statistical computing methods. Key areas of expertise include missing data imputation techniques, Bayesian computational methods, and the application of statistical models to educational and psychological data. His work emphasizes methodological innovation, software development, and the rigorous analysis of complex datasets. Recent research trends in his articles highlight advancements in latent variable modeling, nonlinear effects, and the integration of computational tools like Blimp. His contributions address challenges in multilevel models, missing data mechanisms, and model comparison criteria such as DIC and WAIC. No specific scientific awards are listed for Brian Keller in the provided information. His professional affiliations include the College of Education & Human Development and the Blimp Statistical Software initiative. He advises students in the department but no specific advisee names are provided. Research grants and funding details are not explicitly mentioned in the text. Blimp Statistical Software is a key collaborative project, reflecting his commitment to advancing statistical methods and software solutions for researchers.

• Computational Social Science
• Misinformation Studies
• Social Media Algorithm Analysis
• +۴ مورد دیگر

Professor Jana Lasser holds a professorship in Data Analysis at the University of Graz, where she leads the Complex Social & Computational Systems research group at the interdisciplinary IDea_Lab. She serves as Associate Faculty at the Complexity Science Hub Vienna and previously held positions at Graz University of Technology as a Marie Curie Fellow and interim professor at RWTH Aachen. Her educational background includes a PhD in Physics from Georg-August-University Göttingen (2019), conducted at the Max Planck Institute for Dynamics and Self-Organization, with research on salt desert pattern formation. Her academic journey reflects a transition from geophysics to computational social science. Lasser's research centers on emergent phenomena in complex social systems, employing machine learning, natural language processing, and computational modeling. Key interests include misinformation spread on social media, counterspeech effectiveness, social media recommendation algorithms' societal impact, and the fracturing of societal understanding of honesty. Her work combines theoretical frameworks with real-world applications through agent-based simulations and large-scale text analysis. Her recent publications reveal strong thematic coherence across computational social science, with significant focus on political communication dynamics, platform governance, and methodological innovation. The 15 most recent works demonstrate increasing integration of computational methods with social theory, particularly in analyzing truth-concept evolution in political discourse and developing alternative social media architectures. ERC Starting Grant 101160928 DeSiRe for designing social media recommendation algorithms FWF standalone project P 37280-N on conspiracy theory spread netidee SCIENCE prize for digital civic innovation Marie Curie Fellowship for postdoctoral research Lasser actively supervises graduate students in computational social science, with current focus on topics related to her ERC-funded project. She leads the Survey Special Interest Group within the COST Action on Researcher Mental Health, conducting Europe's largest benchmark study on academic mental health. Her lab maintains strong collaborations with the Complexity Science Hub Vienna and international institutions.