جست‌وجوی استاد و پژوهشگر

• Network Science
• Evolutionary Dynamics
• Complex Systems
• +۵ مورد دیگر

Dr. Wei Zhang is a Researcher at the Complex Systems and Data Science group within The University of Sydney. Her work focuses on network science, evolutionary dynamics, and complex systems, with an emphasis on modeling social systems and analyzing meso-scale structures in social networks. She combines theoretical approaches, data-driven modeling, and web-based experimental methods to study emergent collective phenomena. Dr. Zhang holds a PhD in Network Science from ETH Zurich. Her research spans interdisciplinary topics including data science applications to complex systems and the detection of structural patterns in social networks. Recent projects include exploring domain adaptation techniques in machine learning and developing methods for 3D object detection and model compression. Her publications reflect expertise in computer vision, machine learning, and environmental science. Key themes include domain adaptation networks, 3D reconstruction, and LiDAR-based forestry analysis. While no specific awards are mentioned, her work demonstrates significant contributions to theoretical and applied data science. Dr. Zhang collaborates on projects involving interdisciplinary teams, though specific grants or lab affiliations are not detailed in the provided text. Her current research continues to bridge complex systems theory with modern data-driven methodologies.

• Evolutionary Biology
• Population Genetics
• Phylogenetics
• +۴ مورد دیگر

Xia Hua is a Lecturer in the Mathematical Sciences Institute at the Australian National University. Their research focuses on evolutionary processes in biological and linguistic systems, with a focus on phylogenetics, population genetics, and chemical evolution. Hua holds a Ph.D. from Stony Brook University and has supervised multiple research projects in evolutionary biology and computational linguistics. Current research includes molecular dating methodologies, deep coalescence in phylogenetic analysis, and speciation gene identification. Collaborative projects involve astrophysical studies of stellar populations using phylogenetic techniques, as well as climate change adaptation studies in Australian flora. Recent work explores interdisciplinary connections between galaxy formation and biological evolution. Projects: Integrating theory/data to model evolution under climate change (2024-2027), ARC Plant Biosecurity Centre (2024-2029) Key collaborations: GALAH survey (solar twin abundance catalog), Omega Centauri stellar population studies Hua's research bridges computational modeling with empirical data analysis, with notable contributions in phylogenetic algorithms, molecular clock calibration, and evolutionary linguistics. Active in both biological and astrophysical communities through interdisciplinary collaborations.

John Levi Martinمشاهده پروفایل

استاد

• Social Structures
• Political Fields
• Quantitative Sociology
• +۵ مورد دیگر

John Levi Martin is the Florence Borchert Bartling Professor of Sociology at the University of Chicago. He holds a B.A. from Wesleyan University (1987), M.A. (1990), and Ph.D. (1997) from UC Berkeley. His research focuses on social structures, political fields, and quantitative methodologies, with notable publications like Social Structures (2009) and The Explanation of Social Action (2021). He has held previous faculty positions at the University of Wisconsin-Madison and Rutgers University. His work integrates classical sociological theory with innovative methodological approaches, including algebraic social network analysis and field theory. Recent projects explore AI ethics, political polarization, and historical sociological dynamics. Martin advises on interdisciplinary research at the intersection of culture, power, and social organization. Publications span sociological theory, methodology, cultural sociology, and political sociology, with frequent contributions to journals like American Journal of Sociology and Sociological Theory . His research emphasizes structural emergence, inequality mechanisms, and the critique of Cartesian frameworks in social science.

Magnus Bordewichمشاهده پروفایل

استاد

• Discrete Mathematics
• Theoretical Computer Science
• Phylogenetics
• +۲ مورد دیگر

Magnus Bordewich is a Professor in the Department of Computer Science at Durham University. He holds a D.Phil. and MMath from the University of Oxford. Previously, he was a post-doctoral fellow at the University of Canterbury, New Zealand, and Leeds University. His research focuses on discrete mathematics, theoretical computer science, and applications in phylogenetics, including network reconstruction and algorithmic approaches to evolutionary biology. Recent publications explore phylogenetic diversity metrics, tree-child networks, and computational complexity in biological systems. Bordewich received the Erskine Fellowship (2015) and a Top Cited Article award from Elsevier (2010) for his work on hybridization events in evolutionary histories. He currently supervises postgraduate student Jia Cheng.

• Pathogen Ecology
• Evolutionary Biology
• Ecological Systems
• +۳ مورد دیگر

Roman Gort is a Researcher affiliated with the Professorship for Pathogen Ecology at ETH Zurich's Department of Environmental Systems Science. He is based at the CHN J 14 building on Universitätstrasse 16 in Zürich, Switzerland. His work is embedded within the Environmental Systems Sciences faculty, focusing on interdisciplinary research at the intersection of ecology, evolution, and pathogen dynamics. Research interests inferred from his institutional role include pathogen-host interactions, evolutionary mechanisms shaping microbial ecosystems, and the application of ecological principles to infectious disease studies. His position supports academic activities within the Evolutionsbiologie (Evolutionary Biology) research group, though specific projects or publications are not detailed in the provided text. Contact information includes a direct phone line (+41 44 632 66 56) and institutional email. No awards or grants are explicitly mentioned in the profile.

Thomas Poigerمشاهده پروفایل

مدرس

• Environmental Science
• Systems Science
• Sustainability
• +۳ مورد دیگر

Dr. Thomas Poiger is a Lecturer at the Department of Environmental Systems Science (D-USYS) at ETH Zurich. His affiliation with this leading research institution positions him within interdisciplinary environmental science and engineering disciplines. While specific educational background is not detailed in the provided text, his role as a lecturer suggests engagement in teaching and academic supervision within environmental systems science. Research interests are inferred from his departmental affiliation, focusing broadly on environmental systems analysis, sustainability frameworks, and ecological modeling. No specific publications or grants are listed in the available information. No scientific awards or advising activities are explicitly mentioned in the provided content. His professional activities likely include contributions to curriculum development and academic administration within ETH Zurich's environmental science programs.

Felix J. Thoemmesمشاهده پروفایل

دانشیار

• Quantitative Methods
• Causal Inference
• Social Sciences
• +۴ مورد دیگر

Felix J. Thoemmes is an Associate Professor in the Department of Psychology at Cornell University's College of Human Ecology, with his office located in G201F Martha Van Rensselaer Hall. His academic work bridges methodological rigor and applied research in social sciences. His primary research focuses on quantitative methods for causal inference , including specialized techniques like propensity score analysis with clustered data and software development for regression-discontinuity designs. He actively collaborates on interdisciplinary projects in developmental and health psychology, addressing complex real-world problems through advanced statistical approaches. Dr. Thoemmes teaches graduate and undergraduate courses including Quantitative Methods II and Special Topics in Quantitative Psychology , while supervising student research through courses like Empirical Research and Directed Readings. His teaching spans both the Psychology and Human Development programs.

Harold Eysterمشاهده پروفایل

پژوهشگر ارشد

• Socio-Environmental Systems
• Urban Ecology
• Climate Change Adaptation
• +۳ مورد دیگر

Harold Eyster is a Gund Postdoctoral Fellow at the University of Vermont , working with Rachelle Gould and Brian Beckage. He holds a PhD from the University of British Columbia (2021) under Kai Chan and a BA in Environmental Science and Public Policy from Harvard University. His research focuses on socio-environmental systems, urban ecology, and climate change adaptation, with a particular emphasis on renewable energy transitions and human-nature relationships. He currently serves as an Applied Climate Scientist at The Nature Conservancy in Colorado, applying transdisciplinary methods like remote sensing, Bayesian models, and GIS to study renewable energy siting and urban cooling dynamics. His work bridges ecological and social sciences to address sustainability challenges through just and inclusive frameworks. Key interests include: Urban biodiversity and tree-mediated climate regulation Renewable energy impacts and spatial planning Relational values in conservation decision-making Methodologies for interdisciplinary research His research has been published in journals like Journal of Animal Ecology , PNAS , and Conservation Biology , with a focus on actionable insights for policymakers and practitioners.

Joe Watsonمشاهده پروفایل

پژوهشگر

• Statistics
• Environmental Statistics
• Spatio-Temporal Modeling
• +۱ مورد دیگر

Joe Watson is a researcher affiliated with the Department of Statistics at the University of British Columbia (UBC), Faculty of Science. His work focuses on statistical methodology for environmental and spatio-temporal data analysis. Research Interests: Joe's research addresses challenges in environmental statistics, particularly preferential sampling and spatio-temporal modeling. His studies provide theoretical frameworks and computational tools for analyzing complex ecological and environmental datasets. Publications: His notable contributions include advancements in Monte Carlo testing for sampling bias, general theories for environmental network sampling, and multi-data-type species distribution models.

Jun Zhuمشاهده پروفایل

استاد

• Spatial statistics
• Spatio-temporal statistics
• Markov random fields
• +۷ مورد دیگر

Jun Zhu is a Professor of Statistics at the University of Wisconsin-Madison, affiliated with the Department of Statistics and cross-listed in the Department of Entomology, Department of Biostatistics and Medical Informatics, and the Center for Demography and Ecology. His research focuses on spatial and spatio-temporal statistical methodologies, applied to ecological, environmental, agricultural, and health systems. He holds prestigious awards including the Distinguished Achievement Medal from the American Statistical Association and election to the International Statistical Institute. Education: PhD in Statistics (Iowa State University, 2000), MSE in Mathematical Sciences (Johns Hopkins University, 1995), BA in Mathematics and Computer Science (Knox College, 1994). Research emphasizes methodological development for spatial data analysis, with applications in agriculture, ecology, and public health. Key contributions include cluster detection algorithms, spatial regression models, and spatio-temporal analyses of environmental and demographic phenomena. His work bridges theoretical statistics with interdisciplinary collaborations, addressing real-world challenges such as disease mapping and climate change impacts. Scientific Awards: Distinguished Achievement Medal (ASA) Elected Member (International Statistical Institute) Fellow (American Statistical Association) Presidential Award (American Society of Agronomy) Teaching and advising: Leads courses on spatial statistics, time series analysis, and statistical consulting. Advises on methodological and collaborative projects at the intersection of statistics and environmental science. Labs/Teams: Active in interdisciplinary research teams focused on spatial demography, ecological modeling, and statistical ecology.

• Bayesian Statistics
• Epidemiological Modeling
• Disease Dynamics
• +۱ مورد دیگر

Ben Lambert is Associate Professor of Statistics at the University of Oxford and directs the Schmidt AI in Science programme. His research develops computational methods for biological and epidemiological systems, focusing on Bayesian inference in disease transmission. Research: Models mosquito-parasite interactions in malaria, COVID-19 outbreak dynamics, and diagnostic testing strategies. Creates open-source educational resources for statistical methods. Leadership: Manages postdoctoral fellows applying AI to scientific challenges. Fellow of Reuben College.

Barbara Blockمشاهده پروفایل

استاد

• Marine Biology
• Animal Tracking Technology
• Climate Change Impacts
• +۳ مورد دیگر

Barbara Block is the Charles and Elizabeth Prothro Professor of Marine Sciences and Professor of Oceans at Stanford University, with a secondary appointment as a Senior Fellow at the Woods Institute for the Environment. She is affiliated with the Hopkins Marine Station, a leading research facility for marine studies. Her education includes a B.A. in Zoology from the University of Vermont (1980) and a Ph.D. in Zoology from Duke University (1986). Block's research focuses on marine predator ecology, climate change impacts, and ocean conservation. She pioneered the use of biotelemetry to track species like tuna and sharks, revealing migration patterns and habitat use. Her work integrates technology (e.g., satellite tags, environmental DNA) with ecological modeling to address conservation challenges, fisheries management, and climate adaptation. Her recent articles emphasize the effects of climate change on marine ecosystems, the behavior of top predators, and the utility of sharks and tuna as ocean observing platforms. She collaborates globally on initiatives like the Tagging of Pacific Pelagics (TOPP) program and advises on large marine protected areas (MPAs). Block leads the Block Lab, which develops innovative methods for studying marine life and informing policy. Her lab’s work includes projects on the White Shark Café—a critical foraging area for white sharks—and the ecological implications of tuna spawning in the Mediterranean. She advocates for interdisciplinary approaches to ocean sustainability, blending ecology, technology, and policy.

Michael Carlمشاهده پروفایل

استاد

• Machine Translation
• Computational Linguistics
• Translation Studies
• +۶ مورد دیگر

Dr. Michael Carl is a Professor at Kent State University's Department of Modern & Classical Language Studies and Director of the Center for Research and Innovation in Translation and Translation Technology (CRITT). He specializes in Machine Translation, Computational Linguistics, and Translation Process Research, with a focus on analyzing behavioral translation data through the CRITT TPR-DB. Over 25 years, his work has explored translation dynamics, cognitive effort, and the integration of AI into translation workflows. His research emphasizes empirical methods, including eye-tracking and keystroke logging, to study translation processes. Recent work addresses post-editing strategies, syntactic complexity impacts, and modeling human translation using active inference agents. His CRITT TPR-DB contains extensive behavioral datasets, enabling cross-linguistic and cross-modal analysis of translation behaviors. Publications span theoretical contributions to applied studies, often bridging computational linguistics and cognitive science. He has organized global conferences and workshops, advancing interdisciplinary collaboration in translation studies. No scientific awards are explicitly listed, but his sustained contributions reflect a leadership role in the field.

Moritz Bammelمشاهده پروفایل

پژوهشگر

• Embodied Cognition
• Ecological Psychology
• Dynamical Systems Theory
• +۳ مورد دیگر

Moritz Bammel is a doctoral candidate and research associate affiliated with the Institute of Sustainability Psychology (ISP) at Leuphana University Lüneburg , under the Professorship of Psychology (Methodology and Evaluation Research). He holds a M.A. in Philosophy (Free University Berlin) and a M.Sc. in Mind and Brain (Humboldt University Berlin), alongside a B.Sc. in Cognitive Science (Osnabrück University). His research focuses on embodied cognition, ecological psychology, and dynamical systems theory. He employs methods like eye-tracking, motion capture, EEG, and nonlinear analysis (recurrence, fractals) to study reading comprehension as an embodied phenomenon. His work bridges experimental psychology and philosophical inquiry, particularly in cognitive science. Publications span neuroscience, cognitive psychology, and philosophy, including studies on spontaneous thought decoding (Biological Psychiatry), moral psychology (Philosophical Psychology), and neuroreductionism (Psychopathology). His doctoral project investigates reader-text dynamics in naturalistic settings. Teaching activities are coordinated via the university's myStudy portal. His academic work is grounded in interdisciplinary approaches linking cognitive mechanisms to philosophical frameworks.

Christina Ludemaمشاهده پروفایل

دانشیار

• Infectious Diseases
• Women's Health
• Health Equity
• +۳ مورد دیگر

Christina Ludema is an Associate Professor in Epidemiology and Biostatistics at Indiana University's School of Public Health. She holds a Ph.D. and M.S.P.H. from UNC-Chapel Hill and a B.S. from Calvin College. Her research examines social determinants of infectious disease behaviors, women's health, and health equity, with active projects on lactation mastitis antibiotic stewardship (NIH-funded) and COVID-19 impacts. Research Focus: Investigates structural factors affecting health behaviors, including food insecurity, HIV comorbidities, and pandemic responses. Current NIH R03 grant focuses on antibiotic use in mastitis treatment. Key Publications: Research spans HIV care continuity, COVID-19 vaccination predictors, and alcohol monitoring methodologies, emphasizing causal inference and health disparities.