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Mona IbrahimView profile

Research Fellow

• Social Protection
• Public Health
• Conflict and Fragile States
• +7 more

Dr Mona Ibrahim is a Research Fellow at the University of Oxford's Department of Social Policy and Intervention and an Associate Fellow of Nuffield College, serving as Strategic Policy Lead for high-impact collaborations with UN agencies, governments, and civil society in fragile and conflict-affected contexts. Her work focuses on evidence-based policy to strengthen social protection and public health systems across sub-Saharan Africa, with recent leadership in re-imagining humanitarian-development-peace nexus programming. Her educational foundation includes a medical degree from Sudan, providing frontline clinical experience in conflict zones that directly informs her research approach. This background enables unique integration of clinical insights with policy design for vulnerable populations. Dr Ibrahim's research centers on building age-sensitive, gender-transformative social protection systems in crises, with six core pillars: Community-led mutual aid models for social assistance Adolescent-friendly health services integration Cash 'plus' interventions for HIV and food security Violence prevention in welfare systems Gender-responsive programming in conflict settings Health system resilience during political transitions Her Sudan-focused portfolio navigates fragmented governance to develop ground-up protection mechanisms. Analysis of her 15 most recent publications reveals consistent emphasis on social protection as a cross-cutting enabler for health and development goals in conflict zones, particularly highlighting how food security interventions reduce HIV vulnerability among adolescents and how community-based surveillance systems function amid health system collapse. Key geographic focus remains Sudan and sub-Saharan Africa with strong methodological diversity including capture-recapture mortality studies and systematic reviews of HIV responses. Recognition for her contributions includes: Two departmental awards for excellence (2024) Highly commended for the 2025 Social Science Impact Awards She leads a major funded portfolio on Sudanese social protection systems through the Centre for Evidence-Based Intervention, convening high-level dialogues with the African Union and WHO to reframe social assistance in conflict zones. Her partnerships with WFP, WHO, and UNDP translate research into regional frameworks for adolescent health and cash programming. Based at Oxford's Centre for Evidence-Based Intervention, Dr Ibrahim co-leads the CEBI research groups on Child and Family Welfare, Public Health, Social Inequality, and Violence Prevention. She actively shapes global policy through advisory roles in the WHO Partnership for Maternal, Newborn and Child Health, Inter-agency Task Team on HIV in Emergencies, and African Union’s Calestous Juma Executive Dialogues.

Sean Travis AllenView profile

Associate Professor

• Public Health
• Epidemiology
• Substance Use
• +12 more

Sean Travis Allen, DrPH, MPH, is an Associate Professor in the Department of Health, Behavior and Society at the Bloomberg School of Public Health, Johns Hopkins University. His research focuses on structural drivers of public health among marginalized populations, particularly people who use drugs. He is actively engaged in advancing harm reduction, rural health equity, and drug policy reform. Education: DrPH from The George Washington University (2015), MPH and BS from University of Kentucky (2012, 2010) Postdoctoral Training: Johns Hopkins University, Drug Dependence Epidemiology Training Program Professional Experience: Former Senior Policy Advisor, White House Office of National Drug Control Policy Dr. Allen’s research interests span rural health, HIV prevention, harm reduction, drug policy, injection drug use, overdose prevention, geospatial analyses, and epidemiology. His work emphasizes structural interventions and policy change as tools for reducing health disparities. The recent publications reflect a strong trend in harm reduction research, particularly around syringe services programs, public health vending machines, fentanyl test strips, and PrEP access among people who inject drugs. His studies frequently employ mixed methods, combining quantitative modeling with qualitative insights, and focus on underserved rural communities in Appalachia and the Midwest. Geospatial analysis is a key methodological strength in assessing healthcare access disparities. Dr. Allen has no listed scientific awards in the provided text. He has advised or collaborated with numerous researchers and institutions, though specific student names are not listed. His work is supported by active research projects, including adapting HIV prevention interventions for rural populations and implementing syringe services in Indigenous communities. He has been involved in national policy discussions, including during his tenure at the White House ONDCP. Dr. Allen leads or contributes to innovative projects such as public health vending machines and network-oriented HIV prevention, particularly in rural and Indigenous settings. His research often involves community-based participatory approaches and policy evaluation.

Pengfei LiView profile

Professor

• Finite Mixture Models
• Empirical Likelihood
• Experimental Design
• +5 more

Roles & Affiliations Professor at Department of Statistics and Actuarial Science , University of Waterloo since 2012. Serves as Associate Editor for Canadian Journal of Statistics and Metrika . Previously held roles at University of Alberta (2008-2011) and University of British Columbia (2008 postdoc). Education PhD in Statistics (2007) - University of Waterloo MA in Statistics (2004) - Nankai University BSc in Statistics (2001) - Nankai University Research Focus Specializes in statistical methodologies including finite mixture models, empirical likelihood, experimental design, biased sampling problems, capture-recapture data, and density ratio models. Current interests include statistical inference under constraints and analysis of non-probability survey samples. Awards CRM-SSC Prize in Statistics (2022) Institute of Mathematical Statistics Fellow (2022) Multiple awards for teaching and research excellence from University of Waterloo Students & Grants Advised over 10 PhD/Master’s students. Active grants include NSERC funding since 2009 and startup grants from University of Waterloo. Supervises postdocs in statistical methodology development.

David BorchersView profile

Professor

• Ecology
• Wildlife Population Dynamics
• Spatial Capture-Recapture
• +3 more

Prof. David Borchers is a Professor in the Department of Statistics at the University of St Andrews, UK, affiliated with the School of Mathematics and Statistics. He specializes in developing statistical methods for ecological applications, particularly in estimating wildlife population abundance, distribution, and dynamics using advanced survey techniques. His research integrates spatial capture-recapture, distance sampling, and hidden Markov models to address challenges in conservation and wildlife management. Key research areas include spatial capture-recapture methods, acoustic and digital survey technologies, and ecological modeling of species such as snow leopards, gibbons, and marine mammals. He collaborates with global organizations like the Snow Leopard Trust and the Global Snow Leopard & Ecosystem Protection Program. His work emphasizes methodological innovation, such as improving detection probability estimates and addressing biases in survey data. Borchers has supervised numerous PhD students and led projects funded by EPSRC and other grants. His contributions span theoretical statistics and applied ecology, with a focus on bridging gaps between data collection and ecological inference. Current projects include automated animal density estimation using AI and acoustic data, and the PAWS initiative for global snow leopard assessment. He holds leadership roles in research units and has published extensively in journals like Biometrics , Methods in Ecology and Evolution , and Frontiers in Marine Science . His methodologies are widely adopted in conservation policy and wildlife management worldwide.

Michail PapathomasView profile

Senior Lecturer

• Bayesian Statistics
• Biostatistics
• Ecological Statistics
• +7 more

Dr Michail Papathomas is a Senior Lecturer in Statistics at the School of Mathematics and Statistics, University of St Andrews. He is affiliated with the Centre for Research into Ecological & Environmental Modelling. His research focuses on Bayesian statistical methodology, mixture modeling, and applications in ecology, public health, and genomics. He has supervised PhD students including Chao Gao, Thu Nguyen, and Hanyu Wang. His work bridges theoretical developments with practical applications in areas like spatial capture-recapture techniques and antibiotic resistance epidemiology. Recent projects include analysis of multidrug-resistant infections in East Africa and chemical evolution studies of galaxies. Education: PhD in Statistics (inferred from academic role) Research interests span Bayesian nonparametrics, Dirichlet process mixtures, and statistical methods for ecological and biomedical data. He collaborates internationally on projects addressing global health challenges and environmental monitoring. His publications often integrate advanced computational methods with real-world datasets. Key research trends include: (1) Developing flexible statistical frameworks for complex ecological systems; (2) Addressing parameter identifiability in log-linear models; (3) Applying mixture models to genomic and epidemiological datasets. Grants: Received funding for a cancer research studentship from The Melville Trust, and Scottish Funding Council support for blockchain applications in irrigation governance. Led development of spatial capture-recapture methodologies and contributed to tools for galaxy spectral analysis. Active in interdisciplinary collaborations across medicine, ecology, and astrophysics.

Li-Chun ZhangView profile

Professor

• Graph sampling
• Analysis of integrated data
• Statistical uses of administrative sources
• +4 more

Professor Li-Chun Zhang is a faculty member in Social Statistics at the University of Southampton. His research focuses on graph sampling, analysis of integrated data, statistical uses of administrative sources, population size estimation, and machine learning. Research Interests Graph sampling Analysis of integrated data Statistical uses of administrative sources Population size estimation Machine learning Recent Research Trends Recent publications highlight his work on improving road safety data in Oman, census methodologies, graph spatial sampling, categorical linkage-data analysis, and robust capture-recapture techniques using administrative data. His research emphasizes statistical innovation in multisource data integration and machine learning applications. Supervision Jillian Delaney (PhD Social Stats & Demo PT) Luciano Perfetti Villa (PhD Social Stats & Demo) Dadi Liu (PhD Social Stats & Demo) Contact Email: L.Zhang@soton.ac.uk

Hannah WorthingtonView profile

Lecturer

• Statistical Ecology
• Animal Conservation
• Population Management
• +7 more

Hannah Worthington is a Lecturer in Statistics at the University of St Andrews, affiliated with the Statistics Centre for Research into Ecological & Environmental Modelling. She holds a PhD in Statistical Development of Integrated Multi-State Stopover Models from the University of St Andrews (2016). Her research focuses on developing and applying statistical ecology methods to animal conservation and population management. Key interests include capture-recapture techniques, spatial capture-recapture, passive acoustic/visual monitoring, and workflow pipelines for new technologies. She also investigates public health issues such as antibiotic misuse in East Africa through mixed-methods approaches, linking multidimensional poverty to healthcare behaviors. Her work contributes to UN Sustainable Development Goals related to environmental protection and global health. Recent publications highlight her contributions to citizen science data analysis, spatial modeling bias reduction, and antibiotic resistance studies in East Africa. Her earlier work includes foundational research on hidden Markov models for birth cohort recruitment and therapy termination in clinical psychology. Scientific Awards: Conference Award (2012), Conference Award (2013) Summer Studentship (2009, 2010) Travel Bursary (2014) She actively participates in academic activities such as conferences (e.g., International Statistical Ecology Conference 2020) and public engagement (e.g., EXPLORATHON @ The Shops in 2023). Her research collaborations span institutions in East Africa (Kenya, Tanzania, Uganda) and Mongolia. She supervises postgraduate research students, offering projects on topics like movement ecology and statistical inference integration with machine learning. Hannah leads the development of statistical tools for ecological modeling, including a publicly available R package for seal population analysis (Zenodo, 2020). She collaborates with the HATUA Consortium on antimicrobial resistance research and maintains expertise in Hidden Markov Models and multidisciplinary data integration.

Matt GearyView profile

Associate Professor

• Conservation Biology
• Animal Behaviour
• Wildlife Conservation
• +3 more

Matt Geary is an Associate Professor in Conservation Biology/Animal Behaviour at the University of Chester's School of Natural Sciences . He serves as REF coordinator, research lead, and Faculty Postgraduate Tutor, chairing key committees for research and postgraduate education. Geary leads MRes Biological Sciences and MSc Wildlife Conservation programs while teaching conservation, ecology, and statistical/field methods. PhD in Conservation Ecology (Manchester Metropolitan University) MRes in Ecology and Environmental Science (University of York) BSc in Biology (Newcastle University) PGCert in Higher Education (University of Chester) His research specializes in conservation of threatened species (birds, mammals, amphibians) through statistical/ecological modeling and survey optimization . He focuses on endangered species in the UK and globally, with particular emphasis on birds and using camera traps and genetic analysis to inform conservation strategies. Geary's work spans population viability analysis , habitat association studies , and non-invasive sampling techniques . He has developed camera trap protocols for species like wolves and pangolins while investigating genetic diversity in island endemics. His funded projects include studies on Grenada Dove and Capercaillie conservation. He teaches conservation technologies , field research techniques , and population biology modules. Geary has designed multiple programs including BSc Zoology and MRes Research Methods , integrating work-based learning and employability skills into curricula.

Stephen GregoryView profile

Researcher

• Conservation Biology
• Population Modelling
• Fisheries Management
• +3 more

Stephen Gregory is a Senior Statistician at the University of East Anglia's School of Environmental Sciences, specializing in conservation biology and statistical ecology. He holds a PhD from the University of Paris-Sud and an MSc from the University of Oxford. His research focuses on population modeling, Allee effects, and fisheries management, with applications to species like Galapagos rodents and Malaysian orangutans. Academic Background: PhD in Ecology & Statistics (Paris-Sud XI), MSc (Oxford), BSc (Swansea) Professional Affiliations: Royal Statistical Society Fellow, ICES Working Groups on North Atlantic Salmon His work integrates statistical methods with ecological challenges, including spatial population dynamics and conservation strategies under global change. Recent research explores Tweedie distributions for patchy ecological data and co-occurrence patterns using simulation approaches. Awards: Fellow of the Royal Statistical Society Key contributions include studies on salmonid recruitment dynamics and the environmental drivers of fish population structures.

Heather BradleyView profile

Associate Professor

• Infectious Disease Epidemiology
• Public Health Surveillance
• Racial Disparities in HIV/Hepatitis C
• +3 more

Heather Bradley is an Associate Professor of Epidemiology at Emory University's Rollins School of Public Health. Her research focuses on infectious disease epidemiology with emphasis on surveillance methodology, racial disparities in HIV and hepatitis C infections, and intersections between substance use and public health crises like the opioid epidemic and COVID-19. She previously held roles at the CDC and Georgia State University, contributing to epidemic intelligence and public health policy. Education: PhD (Johns Hopkins Bloomberg School of Public Health), MHS (Johns Hopkins), BA (Centre College). Key Research Projects: NIH-funded studies on improving Black community representation in COVID-19 surveillance (Represent ATL 2.0 and Represent ATL). Epidemiological modeling of PWID populations in New York and nationwide. CDC collaborative work estimating HIV/hepatitis outcomes during the pandemic through CAMP 2.0. Publications emphasize methodological innovations in surveillance, overdose mortality analysis, and health equity in marginalized populations. She directs HepVu.org, a public health data resource for HIV prevention.

• Ecology
• Conservation Biology
• Wildlife Behavior
• +9 more

Dr. Lucinda Kirkpatrick is a Lecturer in the School of Environmental and Natural Sciences at Bangor University, where she actively supervises PhD students and conducts interdisciplinary research in ecology and conservation. Her work bridges wildlife behavior, biodiversity monitoring, and disease ecology, with a focus on bats, rodents, and broader ecosystem dynamics. Her research interests include wildlife social networks , capture-mark-recapture modeling , habitat use in tropical and temperate ecosystems , and the application of technology in ecological monitoring . She has developed and employed miniaturized Bluetooth Low Energy proximity loggers to study animal contacts, contributing to understanding disease transmission and social structures in wild populations. Dr. Kirkpatrick's recent publications reveal a strong trend in long-term ecological datasets , spatial modeling , and conservation applications across diverse systems—from Tanzanian rodent populations to great ape monitoring in the Democratic Republic of the Congo. Her work frequently appears in high-impact journals such as Nature Ecology and Evolution , PLoS ONE , and Journal of Animal Ecology . She has been invited to speak at international events, including a 2025 workshop on proximity logging for animal behavior and a 2024 conference session on One Health in the Anthropocene. Her scientific contributions are supported by extensive collaborative networks and fieldwork across Africa and Europe. Scientific Contributions and Activities: Developed novel methods for non-invasive bat marking using bee markers. Contributed to the PREDICTS project database on terrestrial biodiversity responses. Presented invited talks on animal behavior monitoring and conservation in the Anthropocene. Dr. Kirkpatrick is actively involved in mentoring and research supervision, with no indication of retirement or former status. She continues to publish cutting-edge research and engage with the global ecological community.

• Representative method
• non-random samples
• public statistics
• +2 more

Dr. Maciej Beręsewicz serves as a Professor in the Department of Statistics at Poznan University of Economics and Business (UEP), holding key institutional roles including Member of the Competition Committee for "Mini-grants for Research," University Evaluation Team, and Rector's Committee for Academic Teacher Awards. His office is located in Building C, Room 406, with contact email Maciej.Beresewicz@ue.poznan.pl and phone 61 854 36 80. His research centers on representative methods, non-random samples, public statistics, big data applications, and statistical package development. He specializes in methodological innovations for non-probability surveys, capture-recapture modeling, and integrating administrative/online data sources into official statistics frameworks. Recent publications demonstrate a cohesive trajectory in survey methodology, particularly calibration techniques for probability/non-probability sample integration, quantile estimation, and job vacancy analysis using online advertisements. His R packages ( nonprobsvy , singleRcapture ) operationalize these methods for practical statistical implementation. Prof. Beręsewicz maintains significant external engagements through the Central Statistical Office of Poland (Real Estate Price Statistics Team, Quality Group), Baltic-Nordic-Ukrainian Network on Survey Statistics (Scientific Committee), and international bodies including the International Association of Official Statisticians and International Association of Survey Statisticians.

• Bayesian Statistics
• Statistical Modeling
• Functional Data Analysis
• +4 more

Raffaele Argiento is a Full Professor of Statistics at the Department of Economics, University of Bergamo since September 2021. His academic career focuses on advanced statistical methodologies with applications across various domains including environmental science, public health, and data analysis. His research is prominently featured in high-impact statistical journals and conference proceedings. Argiento's research interests center around Bayesian statistical methods, particularly in functional data analysis, nonparametric Bayesian modeling, and clustering techniques. His work demonstrates expertise in developing innovative statistical approaches for complex data structures, including spatio-temporal data, categorical variables, and high-dimensional datasets. His research has significant applications in environmental monitoring (particularly air pollution analysis), public health (obesity rate modeling), and seismic monitoring through crowdsourced data. His methodological contributions include advancements in mixture models, partition models, and computational algorithms for statistical inference. His recent publication record shows a strong trend toward developing computationally efficient Bayesian methods for real-world applications. The research spans from theoretical developments in nonparametric Bayesian statistics to practical implementations for environmental monitoring, health data analysis, and functional data processing. His work demonstrates a consistent focus on bridging theoretical statistical advancements with practical applications across multiple scientific domains. Professor Argiento teaches several advanced statistical courses at the University of Bergamo, including Applied Statistical Modelling , Probability and Statistics , and Statistical Models for both undergraduate and graduate programs in Economics and Data Analysis. His teaching reflects his research expertise, emphasizing modern statistical methodologies and computational approaches.

Dankmar BöhningView profile

Professor

• Medical Statistics
• Meta-analysis
• Capture-Recapture Methods
• +3 more

Professor Dankmar Böhning holds a Chair in Medical Statistics at the University of Southampton, affiliated with the Southampton Statistical Sciences Research Institute (S3RI) as Deputy Director. His expertise spans mathematical sciences and medicine, with a focus on meta-analysis, capture-recapture methods in health/social sciences, count data analysis, and mixture models. Education: Bielefeld and Berlin universities (Mathematics/Social Sciences), PhD (1981) and Habilitation (1992) from Free University Berlin. Career highlights include roles as Chair in Statistics at University of Reading (2005–2011) and visiting positions at institutions in Vienna, Graz, PennState, Bangkok, and Manila. Research interests include applying statistical methods to healthcare challenges, including epidemiological studies and clinical trials. He leads projects like CLASP Cancer and capture-recapture for contact-tracing efficacy. Active in teaching statistical inference and epidemiology courses at undergraduate and postgraduate levels. Key achievements: Bualuang ASEAN Chair Professor Prize (2022), editorial roles (e.g., Biometrical Journal), and leadership in national/international research collaborations. His recent work focuses on pandemic modeling (Covid-19) and improving diagnostic testing strategies.

• Ecology
• Wildlife Management
• Conservation Biology
• +3 more

Richard Bischof is a Professor at the Norwegian University of Life Sciences (NMBU), affiliated with the Ecology and Natural Resource Management Section. His research focuses on wildlife population dynamics, spatial ecology, and conservation biology, particularly in large carnivores and boreal/tropical ecosystems. He specializes in advanced methodologies like spatial capture-recapture modeling and noninvasive genetic sampling to estimate population parameters and inform conservation strategies. Key research interests include understanding the effects of environmental variability, human activities, and management practices on species distribution and population trends. His work often addresses challenges in monitoring elusive species such as bears, wolves, and wolverines, emphasizing the integration of genetic data and spatial analysis to improve conservation outcomes. Recent studies highlight his contributions to quantifying population dynamics of Scandinavian large carnivores, evaluating the impacts of wind energy development on forest biodiversity, and analyzing behavioral adaptations of tropical mammals to anthropogenic pressures. Bischof’s interdisciplinary approach bridges ecological theory with applied conservation, addressing pressing issues like transboundary wildlife management and the mitigation of human-wildlife conflicts.