Dr. Tim Burnett is a Senior Lecturer in Economics and International Business at Aston University, affiliated with the Aston Business School and the Centre for Business Prosperity. His research focuses on finance, public policy, education, data analysis, social policy, and education technology. He actively participates in academic conferences such as the Royal Economic Society Conference and TeachEconference. Key research areas include financial misconduct detection, academic integrity in remote assessments, defense acquisition processes, and the socioeconomic factors influencing education pipelines. His work often intersects with policy implementation and transdisciplinary approaches to sustainability education. Notable publications explore topics ranging from defense procurement strategies to the impact of service bundling in UK communication markets. Burnett’s research methodologies include complex systems analysis and capture-recapture techniques for estimating regulatory effectiveness. Though no formal awards are listed, his contributions to pedagogical innovation in remote learning and policy design for international students reflect his commitment to educational excellence and institutional best practices.
Audrey Béliveau is an Associate Professor at the University of Waterloo, affiliated with the Department of Statistics and Actuarial Science. She can be reached at audrey.beliveau@uwaterloo.ca and is located in M3 4232. Her research focuses on Bayesian statistical methods, network meta-analysis, and environmental and population dynamics modeling. She has contributed to software development, notably the Bugsnet R package for Bayesian network meta-analyses. Her work spans interdisciplinary applications, including estimating homeless population sizes, methane emissions quantification, and genetic mark-recapture methods for ecological studies. She also explores error propagation in medical treatment comparisons and Bayesian approaches for item response modeling in online assessments. Béliveau’s research emphasizes methodological rigor and practical tools, such as automated R packages for reproducible statistical analyses. She regularly publishes in top-tier journals, addressing both theoretical and applied challenges in statistics.
Diana Cole is a Senior Lecturer in Statistics at the University of Kent, affiliated with the School of Mathematics, Statistics and Actuarial Science. She earned her PhD in Statistics from the same university in 2003, focusing on stochastic branching processes in biology. Her research interests include ecological statistics, integrated population modeling, identifiability, parameter redundancy, and generalized linear mixed models. She is a core member of the SE@K (Statistical Ecology at Kent) research group and the National Centre for Statistical Ecology (NCSE). Dr. Cole teaches courses such as Statistical Consultancy and Data Presentation (MAST6012) and Data Modelling and Consultancy (MAST7200). She actively supervises PhD students in statistical ecology, emphasizing applications in ecological and environmental data analysis. Her publications span ecological modeling, statistical methodology, and interdisciplinary applications, with a focus on parameter redundancy and identifiability in complex models. Notable contributions include her 2020 book Parameter Redundancy and Identifiability , which provides theoretical and practical insights into model identifiability. Her work bridges statistical theory and ecological applications, addressing challenges in population dynamics, conservation biology, and environmental monitoring. Recent studies explore (e)DNA concentration modeling, state-space approaches for ecological time series, and methodological advancements in capture-recapture and removal models.
Eleni Matechou is an Honorary Academic in Statistics at the University of Kent, affiliated with the School of Mathematics, Statistics and Actuarial Science. Her academic background includes a BSc in Statistics from Athens University of Economics and Business, an MSc in Statistics with Applications in Medicine from the University of Southampton, and a PhD jointly conducted at the University of Kent and the Max Planck Institute for Demographic Research. She has held positions such as Research and Teaching Fellow at Victoria University of Wellington, Departmental Lecturer at the University of Oxford, and is currently a member of the Statistical Ecology @ Kent (SE@K) group and the National Centre for Statistical Ecology (NCSE). Her research focuses on statistical ecology, particularly developing models for wildlife populations, migration patterns, and environmental DNA (eDNA) monitoring. Key areas include Bayesian and frequentist approaches to capture-recapture models, mixture models, and integrating citizen science data for ecological inference. She is actively involved in methodological advancements for biodiversity assessment and conservation, emphasizing the use of innovative technologies like robotics and eDNA. Professionally, Eleni chairs the Environmental Statistics Section of the Royal Statistical Society and serves as Book Reviews Editor for the Journal of Agricultural, Biological and Environmental Statistics . Her work bridges statistical rigor with ecological applications, addressing challenges in monitoring biodiversity and informing conservation strategies. Collaborations span institutions globally, reflecting her interdisciplinary approach to solving ecological problems.
Phil Hammond is a Professor (Research) in the School of Biology at the University of St Andrews, Scotland. He is affiliated with several key research units including the Sea Mammal Research Unit (SMRU), the Scottish Oceans Institute (SOI), the Centre for Research into Ecological & Environmental Modelling (CREEM), and the Marine Alliance for Science & Technology Scotland (MASTS). His work spans marine mammal ecology, population dynamics, and conservation science. B.A., University of York D.Phil., University of York His research focuses on the foraging behaviour and diet of seals and cetaceans, statistical and mathematical modelling of marine mammal populations, and estimating animal abundance. He investigates human impacts on marine mammals, including whaling, fisheries bycatch, and seal-fishery interactions, contributing directly to the conservation of vulnerable species. His expertise aligns with UN Sustainable Development Goals related to life below water and climate action. The most recent articles highlight advanced methodologies such as spatial capture-recapture, acoustic monitoring via signature whistles, and long-term trend analysis in cetacean populations across regions like the North Atlantic, Gulf of California, and Black Sea. These works reflect a strong emphasis on conservation-oriented ecological modelling, climate change impacts, and innovative survey techniques. Associate Editor, Marine Mammal Science (2011–present) Member, Red List Authority, IUCN (2006–present) Member, Working Group on Marine Mammal Ecology, ICES (2005–present) Member, Cetacean Specialist Group, IUCN (1998–present) Chair, Scientific Committee, International Whaling Commission (1992–1993) Member, Scientific Committee, International Whaling Commission (1981–2013) Hammond has led major research projects funded by NERC, the European Commission (Marie Curie Fellowship), and the UK Department for Environment, Food and Rural Affairs. He has supervised postgraduate research and contributed to national and international policy through advisory roles. He has organized training workshops on abundance estimation and served on multiple scientific committees and peer review panels. He is actively involved in collaborative research networks and has contributed to open-access datasets on marine mammal abundance, killer whale dynamics, and environmental change impacts. His leadership in projects like EcoSTAR and Monitoring Marine Mammals from Autonomous Underwater Vehicles underscores his commitment to integrating technology and ecology for marine conservation.
Brian Irwin is a Unit Leader and Adjunct Associate Professor at the University of Georgia's School of Forestry and Natural Resources, affiliated with the Georgia Cooperative Fish and Wildlife Unit. His education includes a Ph.D. from Cornell University (Natural Resources), M.S. from Auburn University (Fisheries and Allied Aquacultures), and B.S. from the University of Illinois (Biology). Research focuses on fisheries management, invasive species control, aquatic ecosystem dynamics, and adaptive management strategies. Notable projects include studies on Oneida Lake fish communities, Great Lakes sea lamprey control, and climate adaptation in inland fisheries. His work bridges ecological science with policy, emphasizing structured decision-making frameworks for sustainable resource management. A key achievement is the Robert L. Kendall Award-winning 2017 paper on variance analysis in fishery data. Labs/Teams: Georgia Cooperative Fish and Wildlife Unit, Warnell School collaborations. Grants and advising include projects on sturgeon conservation, angler behavior analysis, and invasive species impact modeling.
Dr. Brian Shamblin is a Senior Research Scientist at the University of Georgia's Warnell School of Forestry & Natural Resources. He leads the Nairn Lab and focuses on applying genetic tools to address wildlife conservation challenges, particularly in marine turtles. His work emphasizes understanding population structure, migratory connectivity, and reproductive ecology through advanced genetic methodologies. Key contributions include refining genetic tagging techniques for loggerhead and green turtles to estimate population parameters and inform management strategies. Shamblin collaborates extensively on projects like the Northern Recovery Unit Genetic Capture-Recapture Project, aiming to improve conservation outcomes for endangered species. His research also extends to salt marsh ecosystems, analyzing genetic diversity in foundational species like Juncus roemerianus to assess ecosystem resilience. Research interests include wildlife population dynamics, conservation genetics, and the application of genetic data to resolve ecological questions. Shamblin’s studies often bridge molecular biology and field ecology, addressing gaps in understanding species’ life histories and population connectivity. He has pioneered approaches to non-invasively sample nesting turtles, enabling large-scale genetic studies without physical disturbance. His findings contribute to global marine turtle conservation efforts, particularly in regions like the Gulf of Mexico and Brazil. Shamblin’s work is supported through interdisciplinary collaborations with institutions such as the Georgia Department of Natural Resources and the U.S. Geological Survey. He maintains an active lab website and has authored numerous peer-reviewed articles on topics ranging from turtle migration patterns to salt marsh genetics. His research underscores the importance of integrating genetic data with field observations to achieve effective conservation outcomes.
Gracia Yunruo Dong is an Assistant Professor in the Teaching Stream at the University of Toronto, affiliated with the Department of Cell & Systems Biology and the Department of Statistical Sciences. She also collaborates with Island Health on healthcare equity research. PhD, MMath, and BMath in Statistics from the University of Waterloo CANSSI Distinguished Postdoctoral Fellow (2022–2024) at University of Toronto and University of Victoria Her research spans Computational Statistics , Healthcare Equity , Quasi-Monte Carlo Methods , and Population Health , with a focus on marginalized populations. She develops capture-recapture models for homeless populations, applies case-crossover designs to environmental health, and explores quasi-random number generation for high-dimensional integration. Her publications reflect interdisciplinary collaboration, combining Bioinformatics , Public Health , and Statistical Computing . Recent work addresses gaps in healthcare access, overdose prediction, and simulation experiments. CANSSI Distinguished Postdoctoral Fellowship NSERC funding for SMMEID network Dong teaches courses such as Epidemiology of Health & Disease and The Practice of Statistics I , integrating real-world applications into her instruction. She collaborates with researchers like Patrick Brown and Laura Cowen, applying statistical methods to ecological and human health challenges. Her affiliations with Vancouver Island Health Authority’s Applied Health Data Analytics team highlight her commitment to addressing health disparities through data-driven solutions.
Dr. Antica Čulina is a Senior Research Associate at the Ruđer Bošković Institute's Division for Marine and Environmental Research, Laboratory for Informatics and Environmental Modelling. Holding a DPhil in Zoology from the University of Oxford and BSc in Ecology from the University of Zagreb, her work focuses on open science, meta-analysis, and evolutionary ecology of birds. Education DPHIL in Zoology, University of Oxford (2010-2015) BSc in Ecology, University of Zagreb (2003-2008) Her research bridges biodiversity informatics with open science principles, particularly through the SPI-Birds network which she leads. This initiative standardizes long-tail ecological data across 120+ global contributors, influencing Dutch science policy through the NWO Open Science Fund. The eight featured publications demonstrate her expertise in ecological meta-research, statistical modeling of bird behavior, and FAIR data practices. Key contributions include quantifying research waste, developing open data frameworks, and analyzing pair bond dynamics in monogamous species. Scientific Achievements Dutch Data Prize recipient Veni fellowship (250,000 EUR) Lorentz Center workshop funding Multiple international grants As Executive Director of SPI-Birds, Associate Editor at Journal of Animal Ecology, and Co-Chair of SORTEE's Education Committee, she actively shapes open science policy. Her teaching spans quantitative ecology at Radboud University and life history courses at Wageningen University.
Associate Professor Siranda Torvaldsen is affiliated with the Northern Clinical School at the University of Sydney, where she holds an academic rank of Associate Professor. Her research focuses on maternal and child health, epidemiology, and public health, particularly in obstetrics, neonatal outcomes, and infectious diseases. She has conducted extensive studies on gestational diabetes, stillbirth trends, and maternal mortality in diverse populations. Her work also addresses issues such as smoking cessation during pregnancy, placenta accreta spectrum outcomes, and the global capacity of influenza vaccine production. Key research interests include analyzing population-based data to improve health outcomes, validating hospital data accuracy, and investigating the impact of interventions like bariatric surgery on subsequent pregnancies. Her recent studies have explored the epidemiology of maternal conditions, such as endometriosis and ART use, and their effects on pregnancy outcomes. She collaborates closely with researchers in obstetrics, neonatology, and public health. Dr. Torvaldsen has published widely in peer-reviewed journals such as BMJ Open , Acta Obstetricia et Gynecologica Scandinavica , and Vaccine , addressing topics ranging from interventional radiology in obstetrics to vaccine effectiveness. She has been funded by grants like the Stillbirth Foundation Australia for research on stillbirth causes and risk factors. Her work also extends to food security and healthcare equity, particularly among marginalized populations. She leads projects using record linkage and population data to assess public health indicators, contributing to evidence-based policy recommendations. Notable recent contributions include studies on neonatal morbidity rates and the validation of routinely collected health data for accuracy in reporting maternal conditions like gestational diabetes. Dr. Torvaldsen’s research integrates clinical, epidemiological, and public health perspectives to address critical gaps in understanding maternal and child health outcomes, with a focus on translating findings into actionable strategies for improving healthcare practices and policy.
Julie Paré is an Associate Professor at the University of Montreal’s Faculty of Veterinary Medicine, affiliated with the Department of Pathology and Microbiology. She holds a professional role as an Epidemiologist at the Canadian Food Inspection Agency (CFIA). Her research focuses on epidemiological applications in veterinary diagnostics and surveillance, particularly regarding zoonotic diseases and public health. She is a member of the GREZOSP research group, specializing in epidemiology of zoonoses and veterinary public health. Dr. Paré supervises graduate students, including master’s theses on topics such as West Nile virus distribution in horses and Mycobacterium avium paratuberculosis transmission in dairy herds. Her publications address critical issues in veterinary microbiology, infectious disease control, and livestock population analysis. She contributes to advancing methodologies in environmental sampling, risk factor analysis, and disease surveillance in animal populations. Her work bridges academic research and applied public health, emphasizing evidence-based approaches to mitigate zoonotic threats and improve veterinary healthcare systems.
Simon Bonner is an Associate Professor in Environmetrics in the Department of Statistical and Actuarial Sciences at The University of Western Ontario. Previously, he held positions at the University of Kentucky (Assistant Professor), University of British Columbia (Postdoc), and completed his PhD at Simon Fraser University. His research focuses on developing statistical models for ecological data, particularly Bayesian hierarchical methods applied to wildlife population monitoring via mark-recapture experiments. He has contributed to studies on salamanders impacted by mountaintop removal mining, predator-prey dynamics, and conservation challenges in diverse ecosystems. Education: PhD in Statistics, Simon Fraser University Postdoc, University of British Columbia Research Interests: Ecological statistics, Bayesian modeling, and hierarchical models Applications in wildlife population dynamics, conservation, and environmental impact studies Methodological advancements in capture-recapture and occupancy modeling Advising & Grants: Supervises PhD/MSc students in statistical ecology and applied data science Focus on interdisciplinary projects with collaborators in biology and environmental science Labs & Teams: Lead of the Ecological Statistics and Applied Data Science Laboratory at Western University Collaborations with researchers on salamander ecology, predator behavior, and conservation biology
Francisco Álvares is a Principal Researcher at CIBIO-InBIO, Research Center in Biodiversity and Genetic Resources, affiliated with the University of Porto, Portugal. He holds a PhD and leads research on large carnivores, particularly the Iberian wolf, in human-dominated landscapes. He is also an external collaborator at the Museu de História Natural e da Ciência da Universidade do Porto, managing the Mammal collections. Position: Principal Researcher Institution: CIBIO-InBIO, University of Porto Research Group: CONGEN Email: falvares@cibio.up.pt Membership: Large Carnivore Initiative for Europe (IUCN), Iberian Wolf Research Team His research focuses on wildlife ecology, conservation, and management of large carnivores, with emphasis on human-wildlife interactions such as livestock depredation, behavioral responses to infrastructure, and ethno-biological aspects. He has conducted fieldwork across Europe, Africa, and Asia, assessing populations of canids including wolves, jackals, and wild dogs. His work integrates ecological monitoring with conservation policy, contributing to environmental impact assessments for major infrastructure projects. The recent publications highlight trends in conservation physiology (e.g., hair cortisol as a stress biomarker), population genetics, disease ecology (e.g., sarcoptic mange), and spatial ecology of wolves and other carnivores. His studies often employ non-invasive methods and long-term monitoring to inform management strategies in human-modified landscapes. He has participated in over 50 research and monitoring projects, many related to hydroelectric and wind energy developments in Portugal, ensuring ecological considerations are integrated into infrastructure planning. His advisory roles extend to national and international bodies, including the European Commission. Scientific Contributions: Over 40 publications, including 24 in indexed journals Projects: EDP Sabor, EDP Tua, LoboNW, LoboSulDouro, and others Supervision: Involved in student theses and research training Francisco Álvares leads field teams and collaborates with international scientists, contributing to global understanding of carnivore conservation. His work bridges science and policy, promoting sustainable coexistence between humans and wildlife.
Dr. Antony Overstall is an Associate Professor in the Department of Mathematical Sciences at the University of Southampton. His research focuses on Bayesian statistical methodology, particularly in optimal experimental design, multiple systems estimation, and computational statistics. He actively supervises PhD students in Mathematical Sciences and has developed influential R packages such as 'acebayes' for Bayesian experimental design. His work spans applications in health sciences, criminology, and pharmaceutical manufacturing. Dr. Overstall is affiliated with the Statistics research group and the Statistical Sciences Research Institute (S3RI). He is currently accepting PhD applications in his areas of expertise. Key Research Themes: Bayesian optimal design, meta-analysis, human trafficking victim estimation, adaptive clinical trials, and statistical software development. Recent publications demonstrate contributions to zero-truncated meta-analyses, Gibbs optimal design algorithms, and robust models for modern slavery estimation. His interdisciplinary collaborations include projects with public health, criminology, and biological science domains. Supervised students are engaged in iPhD and PhD programs focusing on mathematical sciences applications.
Brunero Liseo is a Full Professor of Statistics at the Department of Methods and Models for Economics, Territory, and Finance (MEMOTEF), Sapienza University of Rome. He teaches Basic Statistics and Advanced Statistical Methods in Economics and Finance programs. His research focuses on: Bayesian Statistics (objective priors, hierarchical models) Copula Theory (conditional copulas, vine copulas) Stochastic Processes (skew-Brownian motion, long-memory processes) Statistical Modeling (Gaussian extensions, data integration) Recent work includes applications in financial risk analysis , population estimation , and data linkage . He is involved in the research project New Statistical Methods for the Analysis of Human Migration .
