جستجوی استاد راهنمای دانشگاهی

Dagfinn Aune serves as a Research Fellow at the Department of Epidemiology and Biostatistics within the School of Public Health, Faculty of Medicine at Imperial College London. He concurrently holds positions as Associate Professor at Oslo New University College and Senior Researcher at the Cancer Registry of Norway in Oslo. His work centers on large-scale epidemiological investigations into diet, obesity, and chronic disease mechanisms across international populations. Education: PhD in Epidemiology, Norwegian University of Science and Technology (2016) MSc in Nutrition, University of Oslo (2008) Research interests focus on the interplay between dietary patterns, adiposity, physical activity, and smoking with chronic disease outcomes. His work examines how these factors influence cancer risk (particularly breast, gastrointestinal, and hematological malignancies), pregnancy complications, diabetes progression, and mortality across diverse populations. He employs systematic review methodologies and analyzes data from major cohorts including EPIC and Norwegian registries. Publication trends reveal consistent emphasis on obesity-cancer relationships, with recent work (2023-2025) expanding into metabolomic mediators, cardiometabolic interactions, and rare cancer epidemiology. His research frequently utilizes systematic reviews, meta-analyses, and multinational cohort studies to establish evidence for cancer prevention guidelines. Scientific Awards: No awards specified in source materials Advising and grant activity centers on major collaborative projects including the World Cancer Research Fund's Continuous Update Project, the EPIC study, and South American case-control research. While specific student mentorship isn't documented, his leadership in systematic review protocols suggests substantial training responsibilities. His grant portfolio includes funding from WCRF International and Norwegian research councils for large-scale epidemiological analyses. Labs and teams include the Centre for Translational Nutrition and Food Research at Imperial College London, where he collaborates with nutrition scientists and biostatisticians. He maintains active roles in the EPIC consortium and WCRF International's CUP Global Programme, coordinating multinational analyses of diet-cancer relationships through the Cancer Registry of Norway.

• Nutrition and Chronic Disease
• Cancer Epidemiology
• Obesity and Physical Activity
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Professor Chris Holmes is a Professor of Biostatistics at the University of Oxford, where he moved from Imperial College London in February 2004. He is a Fellow at St Anne's College and works in the Department of Statistics. His research focuses on applications and statistical methods development in genomic sciences and genetic epidemiology, holding a prestigious Programme Leaders Grant in Statistical Genomics from the Medical Research Council. Prior to his position at Oxford, Professor Holmes completed his doctorate in Bayesian statistics at Imperial College London, investigating novel nonlinear pattern recognition methods. This was followed by a post-doctoral position and then a lectureship at Imperial. Before his academic career, he worked in industry for several years in scientific computing, developing techniques for real-time pattern recognition models in defense and SCADA systems. Professor Holmes has a broad interest in the theory, methods and applications of statistics and statistical modeling, with a particular foundation in Bayesian statistics which he views as providing a unified framework for stochastic modeling and information processing. His specific research interests include: Bayesian statistics and stochastic simulation Markov chain Monte Carlo methods Pattern recognition and nonlinear, nonparametric methods Spatial statistics Statistical genetics and genomics Genetic epidemiology His recent publications (2023-2025) demonstrate a strong focus on the intersection of biostatistics, artificial intelligence, and healthcare applications. His work spans multiple domains including AI-driven disease classification in neurology, genomic data analysis for health equity, machine learning tools for healthcare prediction, and addressing bias in medical AI systems. A notable trend across his research is the application of advanced statistical methods to solve pressing problems in genomics, epidemiology, and medical diagnostics, with an increasing emphasis on health equity and the ethical implications of AI in healthcare. Professor Holmes currently supervises PhD students Oscar Clivio, Sahra Ghalebikesabi, and Natalia Garcia Martin. His research is supported by multiple grants, including the MRC Programme Leaders Grant in Statistical Genomics which funds his work in statistical genomics. He is actively involved in three research groups at Oxford that reflect the breadth of his scholarly interests: Computational Statistics and Machine Learning Statistical Genetics and Epidemiology Statistical Theory and Methodology

• Bayesian statistics
• Stochastic simulation
• Markov chain Monte Carlo
• +۵ مورد دیگر

David Steinsaltz is an Associate Professor of Statistics at the University of Oxford, affiliated with Worcester College. His research focuses on stochastic processes, biodemography, survival analysis, and Bayesian methods, with applications to aging, mortality, and population dynamics. He holds a PhD in probability theory from Harvard University, followed by postdoctoral work at UC Berkeley. His work bridges theoretical probability and applied statistics, addressing questions in demography, ecology, and epidemiology. Education: PhD in Mathematics (Probability Theory), Harvard University (1996); Postdoctoral Research, UC Berkeley (Departments of Demography and Statistics). Research interests include stochastic flows, Markov processes, and statistical methods for longitudinal data. He contributes to interdisciplinary projects, such as earthquake impact modeling and vaccine efficacy analysis. His collaborations span fields like biostatistics, ecology, and machine learning. He advises students on topics including survival analysis and demographic modeling.

• Stochastic processes
• Biodemography
• Survival analysis
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Nora Uglik-Marucha is an NIHR Doctoral Research Fellow at King’s College London’s Department of Biostatistics & Health Informatics, affiliated with the Institute of Psychiatry, Psychology & Neuroscience. Her work focuses on autism in women and misophonia through advanced psychometric methodologies. She holds MSc and BSc degrees in Clinical Neuropsychiatry and Psychology from King’s College London. Research interests include gender bias in autism screening tools, measurement invariance analysis, and questionnaire development. Her doctoral project develops novel autism assessment tools for women under Dr. Silia Vitoratou and Prof. Francesca Happé. Key contributions include the S-Five tool for misophonia assessment and validation studies across cultures. She has published on misophonia mechanisms, cross-cultural measurement robustness, and autism screening equity.

• Autism in women
• Psychometrics
• Questionnaire development
• +۴ مورد دیگر

Dr. Bin Zhou is a Research Fellow in Health Analytics and Machine Learning at Imperial College London's School of Public Health, affiliated with the Global Environmental Health Research Group and the Abdul Latif Jameel Institute for Disease and Emergency Analytics. He holds a PhD in Epidemiology and Biostatistics from Imperial College London and degrees from Tsinghua University (BEng, MEng, Bachelor of Economics). His research focuses on global cardiovascular health, environmental health, and data analytics. Key areas include worldwide trends in cardiometabolic risk factors, treatment coverage, and co-occurrences, with contributions to the Non-communicable Disease Risk Factor Collaboration (NCD-RisC). His work integrates large-scale health data and advanced statistical methods to support global NCD prevention strategies, collaborating with the WHO and national health agencies. Dr. Zhou is a World Heart Federation Salim Yusuf Emerging Leader, a member of the European Society of Cardiology and the International Society of Global Health, and serves on the editorial board of the Journal of the American Heart Association. His research has addressed topics such as obesity trends in China, global diabetes prevalence, hypertension management, and the health impacts of urbanization and air pollution. He has published extensively on epidemiological trends and health policy, with a focus on translating data into actionable public health interventions.

• Global Public Health
• Epidemiology
• Biostatistics
• +۳ مورد دیگر

Professor Emma Moore is a leading sociolinguist at the School of English, University of Sheffield . Specializing in the social dimensions of language, her work integrates methodologies from anthropology and sociology to investigate how linguistic variation constructs identity and social affiliations. Research focus: Sociolinguistic style, dialect contact, youth language, identity negotiation, and community-based fieldwork Key projects: Adolescence and grammar (1999-), Isles of Scilly dialect (2008-), language and inequality (2014-), language perception software (2016-) Educational background : PhD in Sociolinguistics, University of Manchester Stanford University (USA) during PhD research Research trends across her 2021-2025 publications reveal interdisciplinary exploration of: Socio-syntactic variation Clinical linguistics (2025 MDS-UPDRS studies) Digital discourse post-pandemic Indexicality and cognitive representations Dialect contact in insular communities Educational policy implications Scientific recognition : British Academy Mid-Career Fellow (2019-2020) Elected Fellow, Royal Anthropological Institute (2014) AHRC/BA funded research projects (1999-2015) Research group leadership : Mentored 9 PhD students (2004-2024) and supervised 3 undergraduate SURE projects, including analyses of: Gender in rap performance Language style and workplace inequality Oral history digitization Professional contributions : Editorial Board: Language in Society (2015-), Gender and Language (2011-2017) External Examiner: Lancaster University MA in English Language (2013-2017) Collaborative software development for dialect perception testing

• Sociolinguistics
• Syntax
• Language Variation
• +۱۲ مورد دیگر

Sylvia Richardson is an MRC Investigator at the MRC Biostatistics Unit and holds a Research Professorship at the University of Cambridge, where she served as Director of the Biostatistics Unit from 2012 to 2021. She is affiliated with the Cambridge Mathematics of Information in Healthcare Hub (CMIH) at the Centre for Mathematical Sciences. Her work bridges advanced statistical methodology with critical healthcare applications, particularly in the analysis of complex biomedical data. Richardson's research spans multiple domains of biostatistics with a strong emphasis on Bayesian approaches. Her work has significantly advanced spatial modeling and disease mapping techniques, developed sophisticated methods for handling measurement error in epidemiological studies, and pioneered mixture and clustering models for integrative analysis of heterogeneous data sources. Her research addresses fundamental challenges in analyzing longitudinal health data, multimorbidity patterns, and complex disease trajectories. Her publication record demonstrates consistent methodological innovation applied to pressing healthcare challenges. Recent work focuses on traumatic brain injury outcomes, multimorbidity progression, genomic analysis, and statistical approaches to pandemic data. The articles reveal a strong pattern of methodological development driven by real-world healthcare challenges, with particular attention to longitudinal analysis, Bayesian computation, and integrative modeling approaches that can handle diverse and complex data structures. While specific awards are not detailed in the available information, Richardson's leadership as Director of the MRC Biostatistics Unit for nearly a decade and her continued Research Professorship reflect significant recognition of her contributions to the field. Her work with major international consortia like CENTER-TBI demonstrates her role in large-scale collaborative research efforts addressing critical health challenges. Richardson's research has substantial implications for healthcare policy and practice, particularly in understanding disease progression, developing predictive models for patient outcomes, and creating methodological frameworks that can integrate diverse data sources to generate meaningful clinical insights. Her work continues to influence both statistical methodology and healthcare applications through ongoing research and leadership in the field.

• Biostatistics
• Bayesian Statistics
• Spatial Modeling
• +۷ مورد دیگر

Dr Jonathan Cook is a Research Fellow at Jesus College, University of Oxford, affiliated with the Medical Sciences division. He holds a primary medical qualification from Queen’s University (Canada, 2021) and a PhD investigating viral immune evasion mechanisms under Prof Jeffrey Lee. His work was supported by the Vanier Canada Graduate Scholarship and recognized with the Stuart Alan Hoffman Memorial Prize. As an incoming Banting Fellow at the Jenner Institute, he focuses on vaccine design for infectious diseases. His research interests include malaria eradication, emerging pathogens, and structure-based vaccine strategies. **Education**: - PhD (Investigation of viral entry glycoproteins), University of Toronto, supervised by Prof Jeffrey Lee - Primary Medical Qualification, Queen’s University, Canada **Research Interests**: - Malaria Eradication : Developing vaccines targeting Plasmodium species. - Emerging Infectious Diseases : Designing rapid-response strategies for pathogens like SARS-CoV-2. - Structure-Based Vaccine Design : Leveraging protein structural data to enhance immunogenicity. **Awards**: - Vanier Canada Graduate Scholarships Programme (2017–2020) - Stuart Alan Hoffman Memorial Prize (2021) - Banting Fellowship (incoming) **Grants/Advising**: Works on Jenner Institute-funded projects. No listed advisees yet. **Labs/Teams**: Collaborates with Prof Lee's lab at the Jenner Institute and the University of Toronto's Medical Microbiology program.

• Malaria Eradication
• Emerging Infectious Diseases
• Structure-Based Vaccine Design
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Rafael Perera is a Professor of Medical Statistics at the Nuffield Department of Primary Care Health Sciences (NDPCHS), University of Oxford, where he has been since 2002. He holds leadership roles as Director of the Statistics Group and Director of Graduate Studies , overseeing academic leadership and methodological research. He is also a Statistical Editor of BMJ and BMJ Medicine , and a fellow at St Hugh’s College Oxford . Education : DPhil, MSc, MA Rafael’s research focuses on monitoring for managing long-term conditions (e.g., Type 2 diabetes, hypertension) and complex multimorbidity phenotypes . His work includes impact of extreme temperatures on health , meta-analysis methods , and methodology for infectious diseases . He leads large methodological groups and has been a PI on NIHR-funded infrastructure programs (BRC, ARC, MIC). Recent publications highlight his expertise in clinical prediction models , digital health interventions , and diagnostic test evaluation . His grants span applied research , global health transformation , and ageing research . Scientific Awards : National and international recognition for methodology development in clinical trials (NIHR Progress Report 2008/09) Rafael supervises DPhil and MSc students and leads a fully accredited Clinical Trials Unit . His editorial and policy influence extends to healthcare policy panels and the Centre for Evidence-Based Medicine as Director of Research Methodologies.

• Medical Statistics
• Primary Care Health Sciences
• Monitoring of Long-Term Conditions
• +۶ مورد دیگر

Gordon Lowe is an Honorary Senior Research Fellow at the University of Glasgow's School of Cardiovascular & Metabolic Health. He holds a DSc from Glasgow University (2006) and has been recognized with prestigious awards, including the Kettle Lecture (2006) and the Investigator Award from the International Society of Thrombosis and Haemostasis (2009). His research focuses on vascular diseases (coronary heart disease, stroke, peripheral arterial disease, venous thrombosis) and haemostasis, particularly in relation to haemophilia. He led the Haemostasis and Thrombosis Research Laboratory from 1987, contributing to clinical trials and epidemiological studies on thrombotic and haemorheological factors. Education: MB, ChB (with Honours and gold medal) from the University of St. Andrews (1972). Postgraduate training in internal and vascular medicine at Dundee, Nottingham, and Glasgow. Career highlights include serving as Professor of Vascular Medicine at Glasgow University (1993–2009) and continuing as an Emeritus Professor. Research interests include the interplay between haemostatic factors and cardiovascular outcomes, with over 550 refereed publications. He chairs editorial boards for journals like Journal of Thrombosis and Haemostasis and contributes to clinical guidelines through the Scottish Intercollegiate Guidelines Network (SIGN). Professional roles include past presidency of the British Society for Haemostasis and Thrombosis, and active participation in clinical trial committees. Scientific contributions span meta-analyses of coagulation factors, epidemiological studies on VTE risk, and historical analyses of thrombosis. He is affiliated with the Diabetes, Renal, Endocrine, and Metabolic Medicine Research Theme within his school.

• Vascular Medicine
• Haemostasis
• Thrombosis
• +۳ مورد دیگر

Keming Yu is a Professor and Chair in Statistics at the Department of Mathematics, Brunel University London, within the College of Engineering, Design and Physical Sciences. He is also the Impact Champion for REF in Mathematical Sciences. He joined Brunel in 2005 after holding positions at the University of Plymouth, Lancaster University, and The Open University. He earned his PhD from The Open University and earlier degrees in Mathematics and Statistics from Chinese institutions. PhD in Statistics – The Open University, UK MSc in Statistics – China BSc in Mathematics – China His research centers on quantile regression, Bayesian modeling, survival analysis, and statistical methods for big data . His work spans applications in health, finance, environment, and social sciences. He has made significant contributions to robust and flexible regression methods, including expectile, mode, and censored quantile regression. His recent publications (2023–2025) show a strong focus on streaming data, spatiotemporal modeling, high-dimensional data, and Bayesian methods . He frequently publishes in top-tier journals such as the Journal of the Royal Statistical Society Series A, B, and C , Statistica Sinica , and Computational Statistics and Data Analysis . His work often involves collaboration with international researchers, especially in China and Europe. He has contributed to methodological discussions in leading statistical journals, demonstrating active engagement with the academic community. His work on financial risk, environmental statistics, and health data analysis reflects interdisciplinary impact. Reviewed and contributed to discussions on safe testing, confidence sequences, and betting-based inference. Active in developing methods for nonignorable missing data, censored models, and functional covariates. He supervises PhD students and is involved in teaching and curriculum development, including as Course Director for the MSc Statistics with Data Analytics. His research is supported by extensive publication output and academic service. He leads or contributes to research on Bayesian models, robust regression, and scalable methods for big data , often involving collaborations in interdisciplinary teams. His lab or research group focuses on statistical methodology development with real-world applications.

• Quantile Regression
• Bayesian Statistics
• Survival Analysis
• +۱۲ مورد دیگر

Simon Crouch is a Senior Research Fellow in Biostatistics at the University of York's Health Sciences department. With a strong mathematical background from Cambridge and Warwick, he leads the analytics team within the Epidemiology and Cancer Statistics Group and works closely with the Haematological Malignancy Research Network (HMRN) and Cardiovascular Health team. His work focuses on statistical modeling of complex epidemiological data related to hematological malignancies. University of Cambridge: MA, MMath in Mathematics University of Warwick: PhD in Mathematics University of Lancaster: MSc in Medical Statistics Dr. Crouch specializes in the statistical modeling of complex epidemiological data, with particular focus on hematological malignancies. His research encompasses predictive modeling, event history analysis, and machine learning applications in cancer epidemiology. He has made significant contributions to understanding myelodysplastic syndromes, lymphoma classification, and survival analysis in blood cancers through population-based studies. His work often involves collaboration with international registries including the European Myelodysplastic Syndromes Registry (EUMDS) and the Haematological Malignancy Research Network. Analysis of his recent publications reveals a strong focus on myelodysplastic syndromes (MDS), with particular attention to risk stratification, survival analysis, and treatment outcomes. His work increasingly incorporates genomic and molecular data to refine disease classification and prediction models. The trend shows progression from purely statistical methodology development toward integrated translational research that combines clinical, genomic, and epidemiological data to improve patient outcomes. Extensive publication record with 113 research outputs including 66 articles, 21 patents, and numerous meeting abstracts Active participation in major international research consortia including MDS-RIGHT and ImmunAID Significant contributions to the development of statistical methodologies for cancer epidemiology Dr. Crouch actively supervises PhD students in mathematical and statistical modeling applied to cancer epidemiology, with particular interest in time-to-event models, complex longitudinal models, and simulation techniques. His research has been supported through multiple projects, including the European Myelodysplastic Syndromes Registry and the MDS-RIGHT project focused on facilitating informed decision-making in hemato-oncology. He contributes to the Advanced Health and Social Statistics module for postgraduate students at the University of York.

• Statistical Modeling
• Epidemiology
• Cancer Research
• +۶ مورد دیگر

Dominic Furniss serves as Professor of Plastic and Reconstructive Surgery at the University of Oxford's Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS), concurrently holding an Honorary Consultant Plastic Surgeon position. His clinical expertise centers on hand surgery and supermicrosurgery for lymphoedema treatment. His educational background includes undergraduate medical studies at Trinity College, Cambridge (Junior and Senior Scholar, first-class degree in genetic pathology) followed by clinical training at Oxford University Clinical School. He completed basic surgical training in London before returning to Oxford's Plastic Surgery Department in 2003. Professor Furniss leads pioneering research into genetic and non-genetic causes of hand conditions through multiple initiatives including the Furniss Group, Centre for OA Pathogenesis, and Hand Research Group. His work spans molecular genetics of Dupuytren's disease, carpal tunnel syndrome epidemiology, and kidney stone disease mechanisms. Recent investigations extend to AI applications in health data through the PHAIR study and causal inference methods in genetic epidemiology. Analysis of his 2024-2025 publications reveals a strategic shift toward large-scale epidemiological studies of hand injuries, interdisciplinary genetic research, and AI integration in surgical practice. These works bridge orthopaedics, genetics, and medical informatics with significant real-world clinical implications. His major scientific recognitions include: Pushpa Chopra Award Plenary Prize of the MRS Wellcome Trust Intermediate Fellowship (first awarded to a plastic surgeon) Professor Furniss has secured substantial research funding including the NIHR Clinical Lectureship (2007) and Wellcome Trust Fellowship (2012). He directs multiple research streams: RAMBOH-1 studies, Molecular Genetics of Carpal Tunnel Syndrome project, and HAWAII initiative. His team actively investigates public perceptions of health data sharing for AI through the PHAIR study while advancing supermicrosurgical techniques for lymphoedema. He maintains active leadership in the Athena SWAN gender equality initiative as a Self-assessment team member, demonstrating commitment to inclusive academic culture.

• Plastic and Reconstructive Surgery
• Hand Surgery
• Genetics of Musculoskeletal Disorders
• +۳ مورد دیگر

Bärbel Finkenstädt Rand is a Senior Tutor at the Warwick Medical School , University of Warwick, with extensive research contributions at the intersection of statistics, machine learning, and biomedical sciences. Her work focuses on developing advanced methodologies for analyzing temporal and spatio-temporal data, particularly in circadian rhythms and disease dynamics. Research Themes : Bayesian inference, Hidden Markov Models, circadian rhythm stability, transcriptional bursting, and wearable sensor data analysis. Collaborations : Chronotherapy Group at Warwick, Université Paris-Saclay, and interdisciplinary teams across medicine, genetics, and computational biology. Publications reveal a strong emphasis on circadian health monitoring, gene expression dynamics, and epidemic modeling using stochastic frameworks. Her recent work prioritizes personalized medicine applications through telemonitored biomarkers and IoT platforms . Methodological Innovations include spline-based HMMs, distributed delay systems, and harmonic modeling for nonstationary time series. Applications span oncology, sleep medicine, and population ecology.

• Statistical Methodology
• Machine Learning
• Bayesian Inference
• +۶ مورد دیگر

Ardo van den Hout is a Professor of Statistics at the Department of Statistical Science, University College London. He holds a PhD in Social Statistics from Utrecht University (2004) and has previously worked at the MRC Biostatistics Unit in Cambridge. His research focuses on advanced statistical methodologies including longitudinal data analysis, survival analysis, multi-state models, and applications in aging research and public health. He has authored influential works such as Multi-state Survival Models for Interval-censored Data (2017). Research Interests Development and application of multi-state models for complex health data Survival analysis techniques for interval-censored and longitudinal datasets Methodological advancements in cognitive decline and disease progression modeling Integration of socio-economic factors in health expectancy analysis Key Contributions Pioneered penalized likelihood approaches for multi-state models Developed frameworks for estimating life expectancies in health and disease Advanced methods for handling missing/misclassified data in longitudinal studies Awards Recipient of the Gopal Kanji Prize 2012 for outstanding contributions to statistics Professional Activities Maintains an active research program with collaborations across biostatistics, epidemiology, and health economics. Supervises doctoral students focusing on statistical methodologies with real-world health applications. His work frequently addresses critical questions in aging populations, cancer research, and public health policy.

• Longitudinal Data Analysis
• Survival Analysis
• Multi-state Models
• +۵ مورد دیگر