Find Academic Supervisors

• Computational Statistics
• Epidemiology
• Disease Modeling
• +5 more

Dr. Anthony J. Webster is a Postdoctoral Researcher in Computational Statistics at the University of Oxford's Statistics Department within the Mathematical, Physical and Life Sciences Division. He joined the department in September 2023 to work with David Steinsaltz on developing new methods to study patients with multiple long-term conditions ("multi-morbidity"). His research is closely related to his previous fellowship work at CTSU, Oxford Population Health (2019-2022), which was funded by the Nuffield Department of Population Health and focused on developing novel methods for big-data epidemiological studies. Dr. Webster's research interests center on the development and application of novel mathematical methods to analyze large epidemiological datasets. His work combines epidemiological methods with modern clustering techniques and biologically-motivated disease models. Key contributions include multi-stage disease modeling using UK Biobank data and pioneering the use of the Poisson-Binomial model to quantify how much disease risk can be explained by old age and established risk factors. His research spans computational statistics, epidemiology, disease modeling, and statistical genetics, with earlier work in plasma physics and climate change research. His publications demonstrate significant contributions across epidemiology, biostatistics, and plasma physics. Recent work focuses on disease clustering, risk factor analysis, and multimorbidity patterns, while earlier research examined plasma instabilities in nuclear fusion experiments. His work has appeared in prestigious journals including Nature, PNAS Nexus, and Physical Review Letters. Associate Fellow of the Higher Education Academy Publications in Nature, PNAS Nexus, Scientific Reports, and Physical Review Letters Press coverage in New Scientist and Daily Telegraph Dr. Webster has extensive teaching experience across multiple institutions. At the University of Oxford, he lectures on Advanced Simulation Methods (MCMC), supervises M.Sc. theses on Climate Change Loss and Damage, and tutors in various statistical courses. Previously, he taught at the University of Bristol on plasma physics topics and organized summer schools. He has supervised multiple summer students at the Culham Centre for Fusion Energy, with all projects leading to published work. His outreach activities include talks at the Royal Society of Edinburgh, public lectures on pandemics, and participation in the Oxford Policy Engagement Network.

Sigrunn Holbek SørbyeView profile

Professor

• Bayesian Statistics
• Time Series Analysis
• Spatial Data Modeling
• +3 more

Sigrunn Holbek Sørbye is a Professor at the Department of Mathematics and Statistics, UiT The Arctic University of Norway. Her research focuses on Bayesian statistics, time series analysis, and spatial data modeling with applications in climatology, ecological statistics, and computational statistics. Institution: UiT The Arctic University of Norway Department: Department of Mathematics and Statistics Research Interests: Dr. Sørbye specializes in Bayesian computation using integrated nested Laplace approximation (INLA), statistical modeling of long-range dependent processes, and applications to climate systems. Her work includes modeling cosmic dust detection rates, analyzing metabolic risk factors, and studying population dynamics through capture-recapture data. Selected Publications Trends: Recent research spans dietary pattern analysis, solar dust modeling, climate sensitivity studies, and ecological monitoring. Key methodologies involve Bayesian hierarchical modeling (2025, 2023), INLA applications (2022, 2020), and long-memory stochastic processes (2020-2019). Collaborative Networks: Dr. Sørbye collaborates on interdisciplinary projects including "Modellering av komplekse systemer" (Complex Systems Modeling) and "Intermittent fluctuations in physical systems." She also contributes to "Transforming ocean surveying by the power of DL and statistical methods." Contact: Tromsø, Norway. sigrunn.sorbye@uit.no | +47 77 64 55 04

Jakub StoklosaView profile

Senior Lecturer

• Capture-Recapture Modeling
• Ecological Statistics
• Measurement Error Modeling
• +4 more

Dr. Jakub Stoklosa is a Senior Lecturer at the School of Mathematics & Statistics, University of New South Wales. He holds a PhD in Applied Statistics (2012) and a BSc (Hons) in Science (2007) from The University of Melbourne. PhD in Applied Statistics, The University of Melbourne (2012) BSc (Hons) in Science, The University of Melbourne (2007) His research focuses include: Analysis of capture-recapture data Estimation of animal abundance Measurement error modeling Model selection for multivariate data Non-parametric smoothing Recent publications emphasize statistical applications in ecology, biodiversity, and environmental science, with methodological contributions to error-in-variables regression and zero-truncated models. Scientific awards: 2018 Australian Museum Eureka Prize top 3 finalist (Burramys Genetic Rescue Team) NSW Office of Environment and Heritage Eureka Prize for Environmental Research (2018) Grants: ARC Discovery Project Grant DP210101923 (2021–2023) for "Innovative statistical methods for analysing high-dimensional counts" with D.I. Warton

• Statistical Ecology
• Multiple Systems Estimation
• Illegal Wildlife Trade
• +3 more

Professor Rachel McCrea holds a Chair in Statistics at Lancaster University's School of Mathematical Sciences and is a core member of the Data Science Institute. She actively supervises PhD students in statistical methodology development for real-world ecological and conservation challenges, with current research focusing on statistical ecology, multiple systems estimation, and illegal wildlife trade applications. Her research program centers on: Advanced capture-recapture and state-space modeling for population dynamics Multiple systems estimation for hidden populations (wildlife trade/human trafficking) Integrated population modeling for conservation decision-making Bias correction in translocation management and extinction inference Bayesian methods for ecological time-series and demographic analysis Recent publications (2021-2025) reveal strong methodological innovation in ecological statistics, with key contributions to integrated population models, multi-system estimation frameworks, and conservation applications. Her work bridges theoretical statistics with urgent biodiversity challenges, particularly in extinction risk assessment and wildlife trade monitoring. Current research projects include 'New stochastic models to quantify illegal trade' (2023-2024), 'A transdisciplinary approach to inferring the end of political violence' (2022-2023), and 'Modelling removal and re-introduction data for improved conservation' (2022-2023). She supervises PhD student Lucas Howell through the STOR-i Centre for Doctoral Training. Professor McCrea collaborates extensively through Lancaster's Centre of Excellence in Environmental Data Science, Environmental and Ecological Statistics group, Social and Economic Statistics group, and STOR-i Centre for Doctoral Training, driving interdisciplinary approaches to ecological data science.

• Biodiversity Conservation
• Tropical Ecology
• Wildlife Ecology
• +3 more

Dr. Andrew Whitworth is an Affiliate Researcher at the University of Glasgow's School of Biodiversity, One Health & Veterinary Medicine. His research focuses on biodiversity conservation, tropical ecology, and ecological monitoring in rainforest ecosystems. He has conducted extensive fieldwork in Costa Rica and Peru, studying wildlife behavior, habitat disturbance impacts, and conservation strategies. Key Methodologies: Camera trapping, drone-mounted thermal imaging, acoustic detection, and multi-data approaches. Key Regions: Osa Peninsula (Costa Rica), Manu Biosphere Reserve (Peru). Collaborations: Partnerships with institutions like IBAHCM and local conservation organizations. Whitworth’s work emphasizes understanding how human activities and habitat fragmentation affect wildlife populations, particularly mammals, amphibians, and birds. Recent studies include predator-prey dynamics of the Greater Grison, ocelot population estimation, and the ecological role of spider monkeys. His research also explores cost-effective conservation tools like citizen science and remote sensing. Publications highlight innovative methods for monitoring biodiversity, such as using drones for canopy surveys and thermal sensors for sea turtle nesting. His findings underscore the importance of indigenous land management and wildlife corridor design in preserving biodiversity.

Shanshan LvView profile

Assistant Professor

• Statistical Inference
• Fiducial Inference
• Small Sample Methods
• +3 more

Shanshan Lv is an Assistant Professor in the Department of Statistics at Truman State University. She holds a Ph.D. in Applied Statistics (2019) from the University of Louisiana at Lafayette, with additional master’s degrees in Applied Statistics (2017), Pure Mathematics (2015), and a bachelor’s in Applied Mathematics (2012) from Guizhou University of Finance and Economics. Her research focuses on fiducial inference for discrete distributions, statistical computing, and small sample inference methods. Current work emphasizes fiducial inference applications, with plans to expand into continuous distributions and machine learning domains. She also explores prediction intervals for discrete distributions and confidence interval methodologies for population size estimation using capture-recapture data. Her publications span topics like hypothesis testing for continuous distributions, ratio estimation for normal means, and finite population proportion estimation. Research trends show a strong emphasis on developing robust statistical methodologies with practical applications in ecology, engineering, and computational statistics. No scientific awards or grants are explicitly mentioned in the provided text. She has no listed advisees, and no specific labs/teams are referenced in her profile.

Andrea TancrediView profile

Professor

• Bayesian Inference
• Bayesian Computational Methods
• Biostatistics
• +9 more

Andrea Tancredi is a Professor at the Department of Methods and Models for Economy, Territory, and Finance, Sapienza University of Rome. His research focuses on Bayesian inference, computational statistics, and their applications in biostatistics, population size estimation, and health economics. He has coordinated multiple research projects funded by the University, including studies on record linkage, approximate Bayesian computation (ABC), and stochastic frontier models. Research Interests: Bayesian Inference Computational Methods (MCMC, ABC) Population Size Estimation Record Linkage and Data Integration Extreme Value Theory Biostatistics and Health Economics Teaching: He teaches courses such as Basic Statistics, Advanced Statistical Methods, and Extreme Value Theory at the Faculty of Economics and doctoral programs in Economics. Publications and Citations: With 47 publications (23 journal articles), his work spans Bayesian modeling for microbial diversity, climate-conflict risk forecasting, and multi-state health models. His research is cited 682 times on Google Scholar (h-index 12) and 401 times in Scopus (h-index 9).

• Wildlife Ecology
• Carnivore Conservation
• Habitat Use Modeling
• +5 more

Mark Chynoweth serves as an Associate Professor in the Wildland Resources Department at Utah State University's S.J. & Jessie E. Quinney College of Agriculture & Natural Resources and maintains a dual appointment at the USU Uintah Basin campus in Vernal, Utah. His research focuses on wildlife ecology and carnivore conservation in human-dominated landscapes, particularly in Turkey and the Middle East. Dr. Chynoweth employs advanced methodologies including camera trapping, spatially explicit capture-recapture modeling, and species distribution modeling to investigate habitat use, movement patterns, and human-wildlife conflict dynamics for species such as wolves, lynx, and bears. His work integrates biotic interactions and anthropogenic factors into ecological frameworks to address conservation challenges. Analysis of his publication record reveals consistent contributions to carnivore ecology, with recent work emphasizing statistical innovations in wildlife monitoring and the impacts of human activities on wildlife behavior. His research demonstrates particular expertise in analyzing seasonal activity patterns, home range dynamics, and the role of anthropogenic resources in shaping carnivore ecology across fragmented landscapes. No information regarding scientific awards, grant funding, student advising, or laboratory facilities was available in the provided directory data.

Steven J PriceView profile

Associate Professor

• Population Ecology
• Conservation Biology
• Freshwater Biology
• +9 more

Dr. Steven J. Price is an Associate Professor of Stream and Riparian Ecology at the University of Kentucky within the Martin-Gatton College of Agriculture, Food and Environment and the Department of Forestry and Natural Resources. His research focuses on the population ecology, conservation biology, and management of aquatic and semi-aquatic animals, particularly reptiles and amphibians, which are experiencing severe population declines. Education : Ph.D. in Biology (Wake Forest University, 2011), M.S. in Environmental Science and Policy (University of Wisconsin-Green Bay, 2003), B.S. in Biology and Environmental Science (University of Wisconsin-Green Bay, 2000) Research interests derive from his lab's three main areas: Wildlife responses to land-use changes (e.g., mining, urbanization) Development of field methods (e.g., eDNA sampling, spatial capture-recapture) Conservation of imperiled species (e.g., hellbenders, desert tortoises) Scientific trends from his 15 most recent publications highlight: Amphibian and reptile population dynamics in anthropogenically altered habitats Impacts of mining, urbanization, and climate change on aquatic ecosystems Methodological advancements in eDNA, telemetry, and disease ecology Conservation strategies for declining species like freshwater mussels and salamanders Dr. Price has mentored numerous graduate and undergraduate students, including Sarah Tomke, Kathryn Green, Jake Hutton, and Mickey Agha, many of whom have pursued advanced degrees or professional roles in conservation. His lab collaborates with agencies like the US Forest Service, US Fish and Wildlife Service, and National Science Foundation. The Price Lab also explores landscape ecology, urban herpetology, and the intersection of renewable energy development with wildlife conservation.

• Operations Research
• Reliability Engineering
• Bayesian Statistics
• +2 more

Yu Hayakawa is a Professor at Waseda University since 2007, affiliated with the School of International Liberal Studies and the Faculty of International Research and Education. He holds a PhD in Operations Research from the University of California at Berkeley, an MSc in Mathematics from Illinois State University, and a BA in Elementary School Education from Hiroshima University. His career includes roles at Victoria University of Wellington (1992-2004) and Waseda University. Doctor of Philosophy (1986-1992), University of California at Berkeley, College of Engineering, Operations Research Master of Science (1983-1986), Illinois State University, Department of Mathematics Bachelor of Education (1978-1983), Hiroshima University, Faculty of School Education Hayakawa’s research centers on Operations Research and Reliability Engineering , with a focus on Bayesian statistical methods , stochastic processes , and warranty cost analysis . His work includes modeling alternating geometric processes for warranty costs, nonparametric Bayesian hazard rate estimation , and dependent failure analysis in multicomponent systems. Key contributions involve delayed reporting of warranty faults , non-zero repair time modeling , and stochastic epidemic models for fault detection. His recent projects include a non-parametric Bayesian approach to hazard function modeling (2018-2020) and generalized alternating renewal processes for warranty cost analysis. He collaborates extensively with international researchers like Richard Arnold, Stefanka Chukova, and Sarah Marshall, with publications spanning journals such as Reliability Engineering & System Safety and IEEE Transactions on Reliability . He has also explored finite mixture models for failure time and severity analysis, presenting at conferences like the Asia-Pacific International Symposium on Advanced Reliability and Maintenance Modeling (APARM). Hayakawa’s scientific contributions include developing models for imperfect warranty repairs, damage accumulation in multicomponent systems, and Bayesian methods for capture-recapture estimation. He has served as President (2023-2025) and Vice-President (2020-2023) of the Reliability Engineering Association of Japan and holds memberships in IEEE and the Operations Research Society of Japan. His overseas activities include research at Victoria University of Wellington (2011-2012, 2016) and collaborations on system reliability and stochastic process modeling . Advising and Grants: Hayakawa has mentored students like Yan Liu (PhD student) and Yimo Xu (undergraduate). His research is supported by grants from the Japan Society for the Promotion of Science, including New models for failures in multi-component systems (2013-2014) and Non-parametric Bayesian modeling of system reliability (2018-2020). He also worked on robustness measures for telecommunications networks (1993-1994) in New Zealand.

Brian ReichView profile

Professor

• Spatial Statistics
• Bayesian Methods
• Environmental Science
• +6 more

Brian Reich is the Gertrude M Cox Distinguished Professor of Statistics at North Carolina State University. His research focuses on geospatial analytics, spatial statistics, and extreme value analysis, with applications to environmental science, climate change, and public health. He leads the Environmental Statistics Lab, developing computational methods for big spatial data and spatiotemporal modeling. Research Interests: Spatial and Bayesian statistical methods Extreme value analysis and machine learning applications Environmental applications in ecology, epidemiology, and climate science Awards: Gertrude M Cox Distinguished Professorship Grants & Programs: NSF Research Training Group (UQ4Life) NSF REU Site (DRUMS for undergraduates) Carolina Thyroid Cancer Study Labs/Teams: Environmental Statistics Lab Collaborations on marine conservation, wildfire management, and PFAS exposure studies

• Bayesian Statistics
• Statistical Modeling
• Operations Research
• +7 more

David Valentín Conesa Guillén is a Full Professor in the Department of Statistics and Operations Research within the Faculty of Mathematics at the University of Valencia. He is an active researcher and a key member of the Valencia Bayesian Research Group (VABAR), focusing on advanced statistical methodologies and their applications. His primary research interests encompass Bayesian Statistics , Statistical Modeling , Operations Research , Epidemiological Modeling , Spatial Statistics , and Ecological Statistics . His work bridges theoretical development with practical applications in public health, environmental science, and financial systems. The trends in his recent publications reveal a strong emphasis on developing and applying Bayesian hierarchical models to complex real-world problems. Key areas include dynamic forecasting of influenza outbreaks, modeling spatial distributions of ecological and bioclimatic data, correcting biases in ecological survival estimates, and analyzing efficiency in sectors like banking and higher education. His methodology frequently involves advanced computational techniques like the Integrated Nested Laplace Approximation (INLA). PhD in Statistics, University of Valencia (2000) Thesis: "Inferencia y predicción en colas con ingresos o servicios en grupos" Supervised by Dr. Carmen Armero Cervera David Conesa has supervised academic work, as indicated by his role as a thesis advisor. His research has been supported by collaborative projects, leading to publications in top-tier journals such as Bayesian Analysis , European Journal of Operational Research , and Journal of Agricultural, Biological, and Environmental Statistics . He has extensive collaborations with researchers across Spain and internationally. His research is conducted within the VABAR (Valencia Bayesian Research Group) , a collaborative team dedicated to Bayesian methodology and its applications. This group provides a platform for interdisciplinary projects and the training of future statisticians.

Robin MejiaView profile

Research Professor

• Health Disparities
• Health Care Access
• Criminal Justice Statistics
• +4 more

Robin Mejia is an Assistant Research Professor at Carnegie Mellon University's Dietrich College of Humanities and Social Sciences, affiliated with the Department of Statistics & Data Science. Currently on leave during AY 24-25, he holds offices in BH 129D and is based in Pittsburgh, Pennsylvania. His career spans science journalism, documentary filmmaking, and academic research in biostatistics and epidemiology. Education includes a BA in Biology (UC Santa Cruz, 1997), MPH in Epidemiology (UC Berkeley, 2012), and PhD in Biostatistics (UC Berkeley, 2016). His interdisciplinary work addresses health disparities, forensic science methodology, and statistical applications in human rights investigations. Research focuses on: 1) Analyzing health care access disparities during the pandemic through large-scale surveys, 2) Improving forensic laboratory practices via blind proficiency testing, and 3) Statistical methods for human rights casualty estimation. His recent work includes landmark studies on global vaccine hesitancy trends and forensic science reform initiatives. Key Projects: CSAFE Lab Group collaborations, DELPHI Lab pandemic tracking, and statistical methods for forensic validation Publications span epidemiology, forensic science, and human rights data analysis Recipient of 2005 CNN documentary award Advocates for statistical rigor in criminal justice systems and forensic science practices. Active in training forensic professionals and advancing transparent statistical reporting standards.

• Marine Biology
• Climate Change Biology
• Fish Physiology
• +3 more

Ian A. Bouyoucos is a Researcher at James Cook University, specializing in marine biology and conservation physiology. His work focuses on elasmobranch (shark and ray) ecology, thermal tolerance, and the impacts of climate change on marine ecosystems. He holds a PhD in Ecological Energetics of Climate Change for Tropical Sharks (JCU, 2020). Research Interests: His studies investigate physiological and behavioral adaptations of sharks to environmental stressors such as warming, hypoxia, and acidification. Key topics include thermal tolerance mechanisms, nursery habitat use, and the effects of anthropogenic activities on shark populations. Publications Highlight: Over 30 peer-reviewed articles, with recent work emphasizing neonatal shark survival strategies, climate resilience, and the physiological responses of sharks to environmental stressors. Collaborations with institutions like the University of South Alabama and the University of the Algarve underscore his global research network. Methodologies: Uses experimental physiology, biotelemetry, and meta-analysis to assess stress responses and conservation challenges. His work bridges basic research and applied conservation, informing strategies to protect vulnerable marine species.

• Molecular Ecology
• Conservation Genetics
• Population Genetics
• +7 more

Paulo Célio Alves is an Associate Professor in the Department of Biology at the Faculty of Sciences of the University of Porto, and a researcher at CIBIO (Research Center in Biodiversity and Genetic Resources). He holds a PhD and is actively involved in research, teaching, and academic leadership, including directing doctoral programs and serving on scientific councils. His research centers on molecular ecology and conservation genetics, with a focus on mammals such as hares, rabbits, wildcats, and carnivores. Key interests include: Population connectivity and fragmentation Natural and anthropogenic hybridization (e.g., wildcat-domestic cat, wolf-dog) Non-invasive genetic methods for monitoring elusive species Evolutionary history and population dynamics of lagomorphs His recent publications reflect a strong integration of genomics, transcriptomics, and ecological modeling to understand adaptation, disease, and conservation. Trends show increasing use of high-throughput sequencing and interdisciplinary approaches across wildlife health, climate adaptation, and biodiversity assessment. Scientific contributions include: Discovery of ancient mitochondrial introgression in Iberian hares Development of non-invasive monitoring protocols Leadership in national red-listing of mammals He has supervised over 25 Master’s and PhD students, many of whom continue in conservation and evolutionary research. His grants include wildlife monitoring contracts for hydroelectric projects and game species management. He is a key member of research groups CONGEN and WILDEcol at CIBIO, fostering collaborative, field-based molecular research.