جست‌وجوی استاد و پژوهشگر

• Bayesian Statistics
• Spatial Epidemiology
• Disease Mapping
• +۶ مورد دیگر

Miguel Ángel Martínez Beneito is an Associate Professor in the Department of Statistics and Operations Research at the Faculty of Mathematics, University of Valencia. His research focuses on Bayesian statistics, spatial epidemiology, and disease mapping, with applications in public health and risk cluster detection. Education: PhD in Statistics from the University of Valencia (2005), thesis on statistical methods for detecting risk foci in epidemic outbreaks. His research interests include Bayesian modeling, spatial statistics, and computational epidemiology. He is a member of the Valencia Bayesian Research Group (VABAR), contributing to advanced statistical methodologies in health sciences. The recent publications attributed to him span topics in stochastic processes, biomechanics, and mathematical biology. However, there is a possibility of name disambiguation, as some works on biomechanics appear more aligned with a researcher from the University of Zaragoza. The core research at UV remains in statistical and epidemiological modeling. Scientific Contributions: Development of Bayesian methods for disease mapping. Application of statistical models to public health surveillance. Potential contributions to stochastic modeling in biological systems. He advises students in statistics and public health, though no specific advisees are listed. He has collaborated extensively with researchers in applied mathematics and biomechanics, though the nature of these collaborations requires further clarification due to potential name overlap. He is affiliated with the VABAR research group, focusing on Bayesian inference and its applications in real-world health problems.

Laura K. Beresمشاهده پروفایل

عضو هیئت علمی

• Implementation Science
• HIV Care and Treatment
• HIV Prevention
• +۱۸ مورد دیگر

Laura K. Beres is an Associate Research Professor in the Department of International Health at the Johns Hopkins Bloomberg School of Public Health. She is also a Visiting Scholar at the Centre for Infectious Disease Research in Zambia. Her work spans global health, implementation science, and social and behavioral interventions, with a focus on HIV prevention and care in low-resource settings such as Zambia and Lesotho. Education: PhD, Johns Hopkins Bloomberg School of Public Health, 2019 MPH, Emory Rollins School of Public Health, 2011 BS, Northwestern University, 2004 Laura Beres specializes in mixed-methods research, utilizing implementation science and human-centered design to improve health outcomes. Her research interests include re-engagement in HIV care, person-centered interventions, participatory research, and causal inference through quasi-experimental designs. She has led formative and rapid qualitative studies to inform health interventions in sub-Saharan Africa. Her recent publications focus on patient re-engagement, tracer contact effectiveness, and person-centered care models in Zambia. These works employ diverse methodologies including instrumental variable analysis, stepped-wedge trials, and narrative analysis, contributing significantly to the understanding of HIV care delivery in real-world settings. Scientific Awards: Advising, Mentoring and Teaching Recognition Award (AMTRA), JHSPH, 2021 R. Bradley Sack Family Scholarship, JHSPH, 2019 Procter & Gamble Fellowship, JHSPH, 2016 Delta Omega Honor Society, 2010 Robert W. Woodruff Merit Scholar, Emory, 2009–2011 Laura Beres has served as an HIV & AIDS Advisor to the Lesotho Ministry of Local Government and contributed to national strategic planning. She co-authored the WHO Consolidated Guideline on SRHR for women living with HIV and supports the Baltimore City Health Department in monitoring and evaluation. She teaches courses in formative research and human-centered design at JHSPH. Research Projects: She leads initiatives on long-acting injectable PrEP for adolescents in Zambia, risk stratification for pregnant women with HIV in Kenya, stigma reduction integrating mental health and violence prevention, and health systems strengthening in Zambian prisons and clinics.

Charity G. Moore Pattersonمشاهده پروفایل

استاد

• Biostatistics
• Clinical Trials
• Data Coordination
• +۷ مورد دیگر

Charity G. Moore Patterson is a Professor and the founding Director of the SHRS Data Center at the University of Pittsburgh’s School of Health and Rehabilitation Sciences. She is affiliated with the Department of Physical Therapy and leads major biostatistical and data coordination efforts in rehabilitation research. Her work is supported by the National Institutes of Health, PCORI, and the Department of Defense. Education: PhD in Biostatistics, University of South Carolina MSPH in Biostatistics, University of South Carolina BS in Mathematics and Statistics, Eastern Kentucky University Dr. Patterson’s research focuses on biostatistics, clinical trials, and data coordination for exercise, rehabilitation, and physical therapy studies. Her work emphasizes rigorous trial design, longitudinal data analysis, and translational applications in musculoskeletal and neurological disorders. She has contributed extensively to studies on low back pain, Parkinson’s disease, stroke recovery, and health disparities. Her recent publications reflect a strong trend in multicenter clinical trials, pragmatic study designs, and data harmonization , particularly in pain and neurorehabilitation. She frequently employs cluster-randomized, stepped-wedge, and randomized crossover designs, with a focus on real-world outcomes and healthcare utilization. Dr. Patterson serves as a reviewer for leading scientific journals and national funding agencies, contributing to the advancement of methodological standards in rehabilitation research. Advising and Grants: Mentors research teams and collaborates on federally funded projects. Principal and co-investigator on NIH, PCORI, and DoD grants focused on low back pain, vestibular recovery, and data science in rehabilitation. Labs and Teams: She leads the SHRS Data Center, a hub for biostatistical support, data management, and research coordination across interdisciplinary projects within the School of Health and Rehabilitation Sciences.

• Cardiovascular Medicine
• Artificial Intelligence in Healthcare
• Machine Learning
• +۷ مورد دیگر

Andreas Coppi is an Associate Research Scientist in the Department of Cardiovascular Medicine at Yale School of Medicine, with affiliations in the Center for Outcomes Research & Evaluation (CORE) and Internal Medicine. He is actively engaged in research at the intersection of artificial intelligence and cardiovascular health. Research Interests: His work focuses on leveraging machine learning and deep learning to improve cardiovascular diagnostics and outcomes. Key areas include AI-driven analysis of electrocardiograms and echocardiograms for early detection of structural heart disease, heart failure, and cardiomyopathies. He also contributes to innovative research in long COVID and digital health applications. Publication Trends: His recent publications demonstrate a strong trend in developing and validating AI models using real-world clinical data, particularly ECGs and imaging. These models aim to enhance screening, risk stratification, and early diagnosis across diverse patient populations. Scientific Collaborations: He frequently collaborates with leading researchers including Harlan Krumholz, Rohan Khera, and Akiko Iwasaki, contributing to high-impact studies published in journals such as The Lancet Digital Health , JAMA Cardiology , and European Heart Journal - Digital Health . Advising and Grants: While no formal students are listed, his role in large collaborative trials and AI development suggests involvement in mentoring and team-based research. He is likely supported by institutional and federal grants related to cardiovascular outcomes and AI in medicine, though specific funding is not detailed. Laboratories and Teams: He is associated with research teams at the Center for Outcomes Research & Evaluation (CORE), focusing on data science applications in cardiology and patient-centered outcomes.

Atul Anandمشاهده پروفایل

دانشیار بالینی

• Geriatrics
• Multimorbidity
• Electronic Health Records
• +۵ مورد دیگر

Atul Anand is a Clinical Associate Professor and consultant geriatrician at the University of Edinburgh, working within the Centre for Cardiovascular Science under the Deanery of Clinical Sciences. He serves as clinical data lead for the DataLoch programme—a regional repository of health and social care data in South East Scotland—and actively mentors PhD students while leading major research initiatives focused on aging populations. His educational background includes a PhD in Cardiovascular Science (thesis: Clinical Biomarkers in Older Patients with Aortic Stenosis), a Bachelor of Medicine and Bachelor of Surgery, and a Bachelor of Science in Pathology, all foundational to his dual expertise in clinical geriatrics and cardiovascular research. Dr. Anand’s work centers on electronic health records (EHRs) to tackle challenges in multimorbidity , frailty assessment , and delirium detection among older adults. He develops predictive tools for rehabilitation needs using hospital admission data, including a pandemic-era triage system for frail elderly, and investigates cardiovascular outcomes through biomarkers like troponin. His research bridges clinical practice and data science to address gaps in elderly care representation. Analysis of his 2024–2025 publications reveals a strong emphasis on sex-specific cardiovascular risk models , delirium-dementia linkages , and systems engineering for care transitions . Key trends include leveraging UK-wide EHRs for multimorbidity clustering, refining frailty metrics via longitudinal studies, and optimizing myocardial infarction diagnostics for elderly populations using AI and biomarker kinetics. His sole documented scientific award is: British Geriatrics Society Rising Star Award for Research (2020) Dr. Anand secures significant grant funding as Principal Investigator for NIHR/EPSRC’s SET4 project (2023–2025) on systems engineering for multimorbidity care, ESRC’s data training initiative (2024–2025), and British Heart Foundation’s chest pain pathway redesign (2023–2025). He also co-investigated MRC’s MiRisk project (2021–2023) for personalized myocardial infarction care in older patients, advocating for inclusive clinical trial design. He leads the DataLoch programme and collaborates on the AIM-CISC Programme (AI-driven multimorbidity clustering), integrating hospital and social care datasets. His teams include researchers from the University of Edinburgh, NHS Scotland, and external partners, focusing on translating data analytics into clinical tools for frailty prediction and care transition optimization.

• Statistical Mechanics
• Ising Model
• Probability Theory
• +۳ مورد دیگر

Sébastien Ott is a Lecturer in the Department of Mathematics at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with both the SB-SMA-SMA-ENS and SB-MATH-MATH-GE units. He contributes to teaching courses such as Probability and Statistics and Large Deviations , focusing on mathematical foundations of statistical physics. Research interests centered on Statistical Mechanics and Probability Theory , particularly in systems like the Ising and Potts models. His work investigates critical phenomena, correlation decay, interface behavior, and large deviation principles. Articles often address topics such as Ornstein-Zernike asymptotics, phase transitions, and spatial mixing properties. His publications reveal a focus on Ising/Potts model phase transitions Large deviations and fluctuation regimes Surface localization/delocalization Renormalization group applications Correlation length analyticity with connections to mathematical physics and percolation theory.

• Clinical and Health Psychology
• Geropsychology
• Cognitive Behavior Therapy
• +۷ مورد دیگر

Dr. Deborah Koder is a Lecturer in the Department of Psychological Sciences at Swinburne University of Technology, School of Health Sciences, where she teaches and supervises postgraduate clinical psychology students. She is also a clinical psychologist with over 35 years of experience specializing in geropsychology, particularly in residential aged care settings. Her work spans clinical practice, research, supervision, and policy advocacy, with a strong focus on improving mental health access for older adults. PhD, James Cook University Master of Psychology (Clinical), University of Sydney Bachelor of Science in Psychology (Hons), University of New South Wales Master of Leadership (Health and Human Services), University of Tasmania Graduate Certificate of Higher Education Learning and Teaching, Deakin University Dr. Koder’s research centers on the application of cognitive behavioral therapy (CBT) for depression and anxiety in older adults, especially within residential aged care. She investigates barriers to mental health care, develops and evaluates CBT adaptations for cognitively impaired residents, and promotes systemic models involving staff and families. Her work emphasizes training, supervision, and service delivery innovation to build workforce capacity in geropsychology. She leads and contributes to randomized controlled trials, systematic reviews, and translational research aimed at improving psychological care in under-served aged care populations. Her recent publications highlight trends in adapting CBT for nursing homes, evaluating clinical placements, and conducting large-scale prevalence studies of mental illness in aged care. These works reflect a consistent focus on evidence-based, accessible, and collaborative mental health interventions. She has secured major external funding from The Ian Potter Foundation and The Arcare Family Foundation to scale up psychological service delivery models. Her research bridges clinical practice and policy, often informing national guidelines and training frameworks. Alistair Heron Prize for Excellence in Ageing Research and Practice (2020) Hesta Award Team Excellence in Aged Care (2000) Vice Chancellor Community Engagement Award, Swinburne University of Technology (2000) Dr. Koder actively supervises HDR students and has coordinated clinical placements for Swinburne’s postgraduate psychology programs. She has held leadership roles in research grants focusing on improving evidence-based psychological treatments in aged care. Her professional activities include membership in the Australian Psychological Society, Psychology and Ageing Interest Group, and the Clinical Supervision Research Collaborative. She has served on national committees and contributed to policy discussions on psychologist roles in aged care. She is a key figure in the Swinburne Wellbeing Clinic for Older Adults, where she previously served as Clinical Supervision Co-ordinator for the National Telehealth Service. Her work continues to shape clinical training, supervision frameworks, and mental health service models in residential aged care through collaborative, interdisciplinary teams.

• Epidemiology
• Genetic Epidemiology
• Causal Inference
• +۷ مورد دیگر

Yi-Qian Sun is a Senior Researcher in the Department of Clinical and Molecular Medicine at the Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU). Her work focuses on epidemiology, causal inference, and the interplay between lifestyle factors (e.g., vitamin D, body mass index) and chronic diseases such as cancer, dementia, and oral health conditions. PhD in Medicine, Linköping University, Sweden (2004) Medical Degree, Capital Medical University, China (1992) Her research combines genetic epidemiology, epigenetics, and biostatistical modeling to investigate causal relationships between risk factors and disease outcomes. She has led projects on vitamin D as a biomarker for lung cancer, causal links between oral health and systemic health, and Mendelian randomization studies for lifestyle-disease associations. Recent publications highlight her focus on vitamin D metabolism, obesity-related disease risks, and oral-systemic health connections. Her work spans population-based (HUNT Study) and clinical research, utilizing databases like UK Biobank for cross-cohort analyses. Prof. Sun collaborates internationally and applies advanced statistical tools (Stata, R) for study design and data analysis. She leads the HUNT4 Oral Health Study within the GLIDE2 Oral Health Genomics Consortium.

• Theoretical Computer Science
• Algorithms
• Approximation Algorithms
• +۷ مورد دیگر

Shaofeng Jiang is an Assistant Professor at Peking University, affiliated with the School of Computer Science and the Center on Frontiers of Computing Studies. He previously held an assistant professor position at Aalto University and was a postdoctoral researcher at the Weizmann Institute of Science under Robert Krauthgamer. He earned his PhD from the University of Hong Kong under Hubert Chan and completed his bachelor's at Shandong University. PhD: University of Hong Kong, supervised by Hubert Chan Bachelor's: Shandong University His research lies in theoretical computer science, focusing on algorithm design for massive and high-dimensional data. Key interests include approximation algorithms, online algorithms, streaming algorithms, clustering, coresets, and dimensionality reduction. His work often bridges theoretical guarantees with practical applications in distributed and parallel computing environments. The recent publications reveal a strong trend in developing efficient and scalable algorithms for clustering problems, particularly through coreset construction, dimensionality reduction, and distributed models like MPC. There is a growing emphasis on fairness, robustness, and dynamic settings, indicating a forward-looking research agenda in adaptive and responsible algorithmic systems. He actively mentors PhD students and teaches both undergraduate and graduate courses in programming and computational social science. He has served on program committees for top conferences including NeurIPS, ICML, and STOC, and co-organized a Dagstuhl seminar on clustering. Scientific Service and Leadership: Co-organizer, Dagstuhl Seminar on New Trends in Clustering (2026) Area Chair, NeurIPS 2024 and 2025 Program Committee, IPDPS 2019, SWAT 2022, COCOA 2024, ICALP 2026 He has received no explicitly mentioned scientific awards. His grants and funding sources are not detailed in the text. He leads a research group focused on theoretical foundations of data-efficient algorithms, collaborating with students on cutting-edge problems in high-dimensional and streaming data analysis.

Fredrik Sävjeمشاهده پروفایل

دانشیار

• Causal Inference
• Econometrics
• Experimental Design
• +۳ مورد دیگر

Dr. Fredrik Sävje is a Senior Lecturer and Associate Professor at the Department of Economics, Uppsala University , specializing in causal inference and econometrics. His research focuses on experimental design, variance estimation, and treatment effect analysis under complex interference structures. Academic Affiliation: Department of Economics, Uppsala University Email: fredrik.savje@nek.uu.se Dr. Sävje’s research interests span causal inference, econometrics, and statistical methodology. Key areas include: Design-based frameworks for causal inference Threshold blocking and covariate balancing Exposure-response models in bipartite experiments Robust variance estimation under interference His recent work emphasizes: Foundations of causal inference in randomized controlled trials Optimized covariate balancing via Gram–Schmidt Walk Design Relaxing assumptions in exposure mapping for treatment effects Generalizing inference methods to sparse and complex experimental graphs Dr. Sävje has co-authored software packages including GSWDesign.jl for covariate balancing and quickmatch for generalized full matching in R. His publications appear in top journals like Biometrika , Journal of the American Statistical Association , and Electronic Journal of Statistics .

Ioan Manolescuمشاهده پروفایل

استاد

• Probability Theory
• Statistical Mechanics
• Percolation Theory
• +۵ مورد دیگر

Ioan Manolescu is a professor in the Department of Mathematics at the University of Fribourg, Switzerland. His research focuses on probability theory and statistical mechanics, particularly percolation, random-cluster models, Potts models, and self-avoiding walks. He obtained his PhD from the University of Cambridge under Geoffrey Grimmett in 2012 and was a postdoc at the University of Geneva (2012-2015). Education ENS Paris (student) University of Cambridge (PhD, 2012) Supervisors: Geoffrey Grimmett Research Specializes in critical phenomena in statistical mechanics Key techniques: FKG inequality, Russo-Seymour-Welsh methods, star-triangle transformations Focus on universality and scaling relations across models His recent publications analyze arm exponents in FK-percolation, crossing widths in Poisson Boolean models, and universality in loop O(n) models. He teaches Analyse I & II at University of Fribourg, supported by assistants. Contact: ioan.manolescu@unifr.ch

• Health Economics
• Mental Health Policy
• Implementation Science
• +۴ مورد دیگر

Andy Healey is a Senior Research Worker at the Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London , specializing in Health Economics and Implementation Science . His work focuses on economic evaluation of health programs, mental health service optimization, maternal/child health interventions, and cost-effectiveness analysis. Key affiliations: Health Service & Population Research (IoPPN), Centre for Mental Health Policy and Evaluation Research spans mental health policy, maternal health, geriatric surgical care, diabetes management, and global health initiatives Recent publications highlight expertise in: Cost analysis of peer support discharge programs Economic evaluations in pregnancy and fetal growth monitoring Implementation science for mental health and arts-based interventions Global health economics in Sub-Saharan Africa He collaborates extensively across disciplines and institutions, contributing to 43 research outputs and 19 projects since 2014.

Emilien Arnaudمشاهده پروفایل

مدرس

• Artificial Intelligence
• Emergency Medicine
• Care Pathway Prediction
• +۵ مورد دیگر

Emilien Arnaud is a Lecturer-Researcher at Amiens-Picardie University , specializing in the intersection of Artificial Intelligence and Health Informatics . His clinical role as a Hospital Practitioner in Emergency Medicine informs his research focus on care pathway prediction and missing data completion in healthcare . Primary institution: Amiens-Picardie University Research domains: AI in emergency medicine, predictive modeling, NLP applications His recent work explores explainable AI models for patient pathway prediction, large language model ethics in medical contexts, and NLP-driven admission predictions using triage notes. A systematic review of emergency AI missing data strategies (2023) highlights his methodological rigor. Key article trends include: Emergency department workflow optimization Explainable AI for clinical transparency Missing data handling in health datasets NLP applications for triage automation Human-AI collaboration frameworks Ethical AI implementation in critical care While no formal awards are documented in the provided materials, his collaborations span AI development, healthcare operations, and pandemic response systems.

Fabienne Lambuschمشاهده پروفایل

پژوهشگر

• Human-centered information systems
• Mobile and wearable information systems
• Personal energy self-management
• +۵ مورد دیگر

Dr.-Ing. Fabienne Lambusch is a research associate at the Chair of Business Information Systems, University of Rostock, Germany. Since January 2017, she has focused on human-centered design of information systems that foster personal and organizational reflection, particularly in the domains of professional self-management, productivity, and well-being. Education: M.Sc. in Computer Science, University of Rostock (2016) Research Interests: Her core research revolves around mobile & wearable information systems , personalized feedback technologies , and IT-supported self-management . She leverages context-aware and persuasive approaches to help individuals understand and improve the interplay between energy, productivity, and health. Publications Overview: Across 2020-2024, Lambusch has published extensively on systems that combine sensing, self-tracking, and feedback to support workplace productivity and psychological well-being. Topics range from wearable recommendation architectures and webcam-based interventions to ecological momentary assessment of human energy and randomized controlled trials evaluating personalized feedback. Teaching: Basics of Business Informatics (Bachelor) Computer-aided Scientific Work (Bachelor) Project Study (Bachelor & Master) Contact: Konrad Zuse House, Albert Einstein Street 22, Room 351, 18059 Rostock, Germany. Phone: +49 381 498 7404 | Email: fabienne.lambusch@uni-rostock.de

Reidar Säfvenbomمشاهده پروفایل

استاد

• Human Development
• Positive Youth Development
• Physical Activity Contexts
• +۶ مورد دیگر

Dr. Reidar Säfvenbom serves as a Professor at the Department of Teacher Education and Outdoor Studies within the Norwegian School of Sport Sciences (NIH) . His academic focus centers on Human Development and Positive Youth Development , particularly examining how physical activity contexts influence adolescent growth. He has investigated the relationship between vulnerable youth groups and sports participation, advocating for policy changes to create equitable movement opportunities outside traditional organized sports systems. Research Interests: Relational Developmental Systems Theories, Self-Organized Lifestyle Sports, Motivational Climate Analysis Teaching: General educational theory, child/adolescent development, educational philosophy His NIH-based research group explores how physical education, organized sports, and self-organized activities shape adolescent experiences. Notably, he developed the Eagerness for Physical Activity Scale (EPAS) to measure motivational drivers. Recent publications analyze self-organized activity benefits for youth development, comparative studies of egalitarian vs. elitist sports systems, and longitudinal investigations of motivational climate effects. His work with the School in Motion project examines physical activity's impact on academic performance and health metrics.