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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
• +3 more

Dr Peninah Murage is an Assistant Professor at the London School of Hygiene & Tropical Medicine in the Department of Public Health, Environments and Society under the Faculty of Public Health and Policy. She specializes in environmental epidemiology with a PhD in Health Geography and focuses on health impacts of environmental changes, particularly climate change mitigation and adaptation strategies. Affiliation: Centre on Climate Change and Planetary Health Her research explores climate change effects on health outcomes like heat-related mortality, cardiovascular diseases, and cognitive development in children. She integrates GIS/spatial analysis with public health and policy frameworks to identify nature-based solutions for sustainable development. Current work examines systemic inequalities in heat risk exposure and interventions such as tree-based strategies in low-income settings. Key grants include: Health Protection Research Unit on Climate Change and Health Security (2025-2030, NIHR) Climate Change and Non-Communicable Diseases in Senegal (2024-2027) Pathfinder 2: Accelerating Climate Action for Health (2023-2026) She actively contributes to the Lancet Pathfinder Commission and serves on the Executive Committee of the International Society of Environmental Epidemiology (African Chapter).

• Environmental Epidemiology
• Climate Change
• Health Geography
• +5 more

Alexis Battle is an Associate Professor at Johns Hopkins University with appointments in Biomedical Engineering , Computer Science , and Genetic Medicine (secondary). She directs the Malone Center for Engineering in Healthcare and serves as Deputy Director of the Data Science and AI Institute . Educated at Stanford University (PhD in Computer Science, 2013), Battle transitioned to academia after leadership roles at Google. Research Focus: Battle’s work bridges genomics and machine learning , emphasizing the impact of genetic variation on human health. Her lab develops tools like Watershed to predict functional effects of rare variants, aiming to enhance rare disease diagnosis. Key themes include non-coding DNA analysis , personalized genomics , and systems biology , with applications in cardiovascular disease and neurodegenerative disorders . Publications & Awards: Over 60 peer-reviewed articles in journals like Nature , Science , and Genome Biology , with recent emphasis on single-cell transcriptomics , multiomics integration , and telomere biology . Recipient of the President’s Frontier Award (2022), Microsoft Investigator Fellowship (2019), and Searle Scholar (2016). Scientific Awards: 2022 President’s Frontier Award 2019 Microsoft Investigator Fellowship 2019 Johns Hopkins Discovery Award 2017 Johns Hopkins Catalyst Award 2016 Searle Scholar Advising & Funding: Mentors 11 PhD students, 3 undergraduates, and postdoctoral fellows. Her research is funded by NIH, Searle Scholars, and institutional grants. The Battle Lab collaborates on projects like the GTEx Consortium , focusing on gene regulation and clinical genomics .

• Genomics
• Machine Learning
• Computational Biology
• +3 more

Ji Zhu is the Susan A. Murphy Collegiate Professor of Statistics at the University of Michigan, Department of Statistics. He holds affiliations with the Michigan Institute for Data Science (MIDAS) and the Michigan Integrated Center for Health Analytics and Medical Prediction (MiCHAMP). His research focuses on statistical machine learning, network analysis, and health science applications. Education: B.Sc. in Physics (Peking University, 1996), M.Sc. and Ph.D. in Statistics (Stanford University, 2000 and 2003). Notable awards include the NSF CAREER Award (2008), Fellowships from the ASA (2013) and IMS (2015), and recognition as a Web of Science Highly Cited Researcher (2014–2020). Research interests span statistical methodologies for networks, survival analysis, and high-dimensional data. He co-authored influential papers on community detection, network cross-validation, and latent space models. Current editorial roles include Editor-in-Chief of the Annals of Applied Statistics and Action Editor for the Journal of Machine Learning Research. Advising: Supervised over 50 students and postdocs, many now in academia and industry. Notable former advisees include Tianxi Li (University of Minnesota), Yuan Zhang (Ohio State University), and Weijing Tang (Carnegie Mellon University). Labs/Teams: Active in interdisciplinary projects at MIDAS and MiCHAMP, focusing on healthcare analytics and predictive modeling for diseases like hepatitis and cardiovascular outcomes.

• Statistical Machine Learning
• Statistical Network Analysis
• Health Sciences
• +3 more

Dr. Winnie Yip is a Professor of the Practice of Global Health Policy and Economics at the Harvard T.H. Chan School of Public Health. She serves as Faculty Director of the China Health Partnership and recently concluded her role as Acting Director at Harvard's Fairbank Center for Chinese Studies. Previously, she was a Professor at the University of Oxford and led the Global Health Policy Program. She holds a PhD in Economics from MIT and a BA from UC Berkeley. Her research focuses on systemic healthcare interventions, policy design, and aging populations' impact on health systems. She collaborates closely with governments and international agencies like the World Bank and WHO, advising on reforms in Asia. Her work emphasizes equitable access, health system efficiency, and innovative eldercare solutions. Dr. Yip’s academic leadership includes roles as past President of the International Health Economics Association and editorial positions at journals like Social Science & Medicine . Her grants include funding from NSF, Bill & Melinda Gates Foundation, and EU Commission. Key areas of study include telemedicine, long-term care financing, and healthcare delivery in low-income regions.

• Global Health Policy
• Health Economics
• Health System Strengthening
• +5 more

Dr. Stan Ahalt serves as the inaugural Dean of the UNC School of Data Science and Society (SDSS) and holds a professorship in the Department of Computer Science at UNC-Chapel Hill. He previously directed the Renaissance Computing Institute (RENCI) and currently acts as its executive advisor. Additionally, he is the associate director of informatics and data science at NC TraCS, the translational research institute at UNC. His academic journey includes a 22-year tenure as professor of electrical and computer engineering at Ohio State University and leadership roles at the Ohio Supercomputer Center. Ahalt’s research focuses on applying data science to societal challenges such as healthcare, climate, and judicial reform. Key initiatives include the National Consortium for Data Science and the iRODS project, which advanced enterprise data management systems. Ahalt has secured over $34.5M in grants to lead high-impact projects like the NHLBI BioData Catalyst (unifying biomedical data), the NCATS Translator (accelerating clinical discovery), and the NIH HEAL Initiative (ensuring FAIR data standards). He mentors students across doctoral and master’s programs, teaching data science fundamentals in courses like COMP 116: Introduction to Scientific Programming. His work emphasizes interdisciplinary collaboration, evidenced by roles in RENCI, NC TraCS, and the SDSS. Ahalt’s contributions span cyberinfrastructure development, educational innovation, and translational research, positioning UNC as a national leader in data science.

• Data Science
• High-Performance Computing
• Biomedical Informatics
• +4 more

Jenna Wiens is an Associate Professor of Computer Science and Engineering at the University of Michigan's College of Engineering. She serves as Associate Director of the Artificial Intelligence Lab and co-Director of AI & Digital Health Innovation. Leading the MLD3 research group, her work focuses on machine learning and AI applications for healthcare data. PhD from MIT (2014) under John Guttag NSF CAREER Award recipient (2016) Humboldt Foundation Carl Friedrich von Siemens Award (2024) Her research addresses four key technical thrusts: Time-series analysis for predicting clinical outcomes Robust machine learning against spurious correlations Decision-making with causal inference and offline reinforcement learning Human-AI collaboration frameworks Notable methodological contributions include the FIDDLE preprocessing pipeline for clinical time-series data, foundational work on survival analysis, and novel approaches to model selection in healthcare reinforcement learning. Her work has led to real-world AI deployments in infection prevention and patient risk stratification. Scientific honors include: Forbes 30 Under 30 (2015) MIT Tech Review 35 Innovators Under 35 (2017) Sloan Research Fellowship in Computer Science (2020) Sarah Goddard Power Award (2023) Wiens collaborates with clinicians across disciplines, emphasizing clinician-in-the-loop AI systems and ethical implementation in healthcare workflows.

• Machine Learning
• Artificial Intelligence
• Healthcare Data Analytics
• +5 more

Dr. Kristen M George serves as an Assistant Professor of Epidemiology in the Department of Public Health Sciences at the University of California, Davis, School of Medicine. Her academic journey includes a BA in Political Science with minors in Public Health and Anthropology from Washington University in St. Louis, followed by an MPH and PhD in Epidemiology with a minor in Biostatistics from the University of Minnesota (completed in 2015 and 2019 respectively). Dr. George's research program focuses on lifecourse vascular contributions to dementia and cognitive aging, with particular emphasis on race and sex disparities. She investigates how social determinants lead to inequities in cardiovascular risk factors and disease, which subsequently contribute to disparities in cognitive aging and dementia outcomes. Her work bridges epidemiology, neurology, and social determinants of health to address critical gaps in understanding dementia disparities. Analysis of her recent publications reveals a strong focus on African American health, life course epidemiology, and structural determinants of cognitive aging. Her research frequently examines how historical and contemporary social factors impact neurological outcomes in diverse populations, with particular attention to cardiovascular pathways to dementia. Professional recognition includes: Center for the Advancement of Multicultural Perspectives on Science (CAMPOS) Scholar, UC Davis (2021) NIH Travel Award (2020) JB Hawley Student Research Award, University of Minnesota (2016) Dr. George is an active member of the Alzheimer's Association International Society to Advance Alzheimer's Research and Treatment and the Methods in Longitudinal Dementia Research community, contributing to both national and international efforts to understand and address dementia disparities through rigorous epidemiological approaches.

• Lifecourse Epidemiology
• Dementia Research
• Cognitive Aging
• +5 more

Karin Allor Pfeiffer is a Professor in the Department of Kinesiology at Michigan State University (MSU) and Director of the Institute for the Study of Youth Sports. She holds additional membership in the Center for Physical Activity and Health. With a Ph.D. from MSU, her research focuses on physical activity measurement methodologies and population health interventions, particularly among children and adolescents. Her work addresses obesity prevention, environmental design impacts on activity levels, and sociocultural factors influencing youth sport participation. Education: Ph.D. in Kinesiology from Michigan State University Her research interests emphasize: - Quantitative methods for physical activity assessment - Schoolyard redesign strategies and their health impacts - Cardiometabolic risk factors in pediatric populations - Longitudinal tracking of physical fitness and health outcomes Recent work explores accelerometer fragmentation metrics, GPS-linked activity tracking, and disparities in sedentary behavior across demographic groups. She has pioneered interdisciplinary approaches integrating spatial analysis, wearable technology, and policy evaluation. Key contributions include developing the Observational System for Recording Physical Activity in Children and advancing consensus methods for accelerometer data interpretation. Her studies frequently highlight socioeconomic and environmental determinants of health behaviors. Dr. Pfeiffer collaborates with public health agencies and urban planners to translate research into actionable policies. Her lab focuses on scalable interventions for underserved communities, leveraging community-engaged methods to address greenspace accessibility and safety concerns.

• Physical Activity Measurement
• Childhood Obesity Prevention
• Exercise Physiology
• +3 more

Ruofan Yao serves as an Associate Professor in the Department of Gynecology and Obstetrics at Loma Linda University School of Medicine. Holding dual qualifications as an MD and MPH, Dr. Yao maintains an active research profile with 40 publications spanning 2013-2025, reflecting sustained scholarly productivity in maternal-fetal health. Dr. Yao's educational background combines clinical medicine (MD) with population health expertise (MPH), enabling interdisciplinary research at the intersection of obstetrics and environmental health. This foundation supports investigations into critical windows of vulnerability during pregnancy and population-level risk factors. Research focuses on environmental exposures (particularly wildfire proximity) and maternal health conditions (notably obesity) as determinants of birth outcomes. Key areas include congenital heart defects, neural tube defects, perinatal mortality, and cardiovascular complications in pregnancy. Methodologically, the work employs epidemiological approaches to analyze large datasets and identify modifiable risk factors. Analysis of 15 most recent publications (2023-2025) reveals a clear trajectory toward environmental obstetrics, with 60% examining wildfire impacts on congenital anomalies and 40% investigating obesity-related pregnancy complications. The research demonstrates increasing methodological sophistication in spatial epidemiology and temporal vulnerability assessment, primarily focused on U.S. populations. No scientific awards are documented in the available materials. Mentoring activities and grant funding details are not specified in the provided information. The research appears integrated within broader institutional maternal-fetal medicine initiatives at Loma Linda University, though specific lab structures or team compositions are not described.

• Maternal-Fetal Medicine
• Obstetrics
• Environmental Epidemiology
• +2 more

Professor Nicholas Buckley is a leading academic in Clinical Pharmacology at the University of Sydney and holds a Visiting Professor position at the University of Peradeniya, Sri Lanka. He serves as Research Director for the South Asian Clinical Toxicology Research Collaboration (SACTRC) and is a Consultant Clinical Pharmacologist & Toxicologist at the NSW Poisons Information Centre and Royal Prince Alfred Hospital. His work focuses on improving clinical toxicology practices, poison control policies, and understanding mechanisms of drug toxicity. Co-founder of SACTRC for agrochemical poisoning and snakebite research Chair of Australian Therapeutic Guidelines - Toxicology writing group Editorial roles in Clinical Toxicology, Drug Safety, and Australian Prescriber Research Interests include toxicovigilance, epidemiology of poisoning, acute kidney injury in poisoning/snakebite, pesticide safety interventions, antidote development, and pharmacoepidemiology of psychotropic drugs. His work combines clinical trials, population surveillance, and translational research. Scientific Contributions span 440+ peer-reviewed articles and 22 book chapters, with continuous funding since 2002. He has supervised over 20 higher degree students and leads international collaborations in low-and-middle-income countries through NIHR RIGHT4. Key Affiliations : Member of Charles Perkins Centre, Australian Medicines Handbook Editorial Advisory Board, and NIHR RIGHT4 programme.

• Clinical Toxicology
• Pharmacoepidemiology
• Poisoning
• +3 more

Brooke Hudspeth, PharmD, is an Associate Professor and Chief Practice Officer at the University of Kentucky (UK) College of Pharmacy. She oversees community pharmacy initiatives and serves as acting President of the Kentucky Pharmacists Association (KPhA). Her roles include mentoring pharmacy students and residents as a preceptor, and leading collaborative projects with organizations like the American Pharmacists Association Foundation, Kroger Co., and the CDC. Educationally, she holds a Doctor of Pharmacy from the UK College of Pharmacy, alongside PGY1/PGY2 Community-based Pharmacy Practice Residencies from the same institution. Her research focuses on diabetes prevention, obesity, and pharmacist-driven clinical services, particularly through expanding the National Diabetes Prevention Program (NDPP) to five U.S. states via a $7.5M CDC grant. Research interests emphasize health disparities, vaccine accessibility, and optimizing pharmacist roles in self-care conditions. Notable projects include influenza point-of-care testing and pharmacy partnerships during the pandemic. Her work bridges academic innovation with real-world healthcare challenges, advocating for policy changes to enhance pharmacist payment for clinical services. Despite no explicitly listed awards, her impactful grant-funded projects reflect significant contributions to public health. She advises students and residents while leading residency expansion initiatives. Collaborations with major institutions underscore her role in advancing pharmacy practice and education nationally. Hudspeth’s lab/team is embedded within UK’s College of Pharmacy, focusing on translational research to improve patient care through pharmacist-led interventions. Future work includes expanding telehealth pharmacy services and addressing healthcare workforce shortages.

• Diabetes
• Obesity
• COVID-19
• +4 more

Itsik Pe'er is a Full Professor and Vice-Chair in the Department of Computer Science at Columbia University's Fu Foundation School of Engineering & Applied Science, and holds a joint appointment as Professor of Systems Biology at the Vagelos College of Physicians and Surgeons. His research focuses on computational methods in human genetics, including genetic variation analysis, disease association studies, and algorithm development for genomic data. He leads the Itsik Pe'er Lab of Computational Genomics, which develops tools like Xplorigin, Germline, and SEACells to address challenges in genomics and medical research. His work spans machine learning applications in healthcare, microbiome analysis, and cancer genomics. Notable contributions include studies on hypertensive disorders in pregnancy, bias correction in predictive models, and the development of non-Euclidean learning libraries like Manify. Pe'er has advised students including Vladimir Vacic, Anat Kreimer, and Arthi Ramachandran, and collaborates on grants addressing genetic epidemiology and computational biology. His lab's location is in the Computer Science Building at Columbia's Morningside Campus.

• Human Genetics
• Computational Biology
• Genomics
• +3 more

Dr. Ahmed Mahrous Abouzaid is an Adjunct Professor affiliated with the School of Cardiovascular & Metabolic Health at the University of Glasgow . His research focuses on cardiovascular disease, particularly angina management, myocardial infarction pathophysiology, and clinical trial methodologies. He specializes in advanced diagnostic techniques like electrocardiography stress testing, cardiovascular magnetic resonance (CMR), and fractional flow reserve (FFR) analysis. His work emphasizes translating clinical research into improved patient outcomes, with a focus on non-obstructive coronary artery disease, left ventricular remodeling, and optimizing treatment strategies for non-ST elevation myocardial infarction (NSTEMI). He has contributed to high-impact studies published in journals such as European Heart Journal and Circulation . Recent research highlights include a 2024 randomized controlled trial evaluating invasive endotyping in angina patients and a 2025 study on electrocardiography stress testing for diagnostic accuracy. While no awards are explicitly listed, his publications reflect a strong commitment to advancing cardiovascular diagnostics and clinical practice. No grants or advising details are provided in the available text. His affiliation suggests active participation in collaborative research within the School's cardiovascular health initiatives.

• Cardiology
• Cardiovascular Medicine
• Heart Disease
• +3 more

Susan A. Murphy is the Mallinckrodt Professor of Statistics and of Computer Science at Harvard University, with affiliations to the Kempner Institute. She leads the Statistical Reinforcement Learning Lab, focusing on developing algorithms to inform sequential decision-making in health, particularly for Just-in-Time Adaptive Interventions (JITAIs) and micro-randomized trials (MRTs). Her work is funded by NIH institutes, including NIDA, NHLBI, and NIBIB. Dr. Murphy has been awarded a MacArthur Fellowship (2013) and is a member of the National Academy of Medicine (2014) and the National Academy of Sciences (2016). Her research integrates statistical methods with computer science techniques to optimize mobile health interventions. She collaborates with d3Lab and mDOT on projects like HeartSteps and Sense2Stop, evaluating real-time treatment policies. Notable contributions include advancing MRT designs, sample size calculations, and reinforcement learning algorithms for personalized healthcare. Dr. Murphy advises a large team of postdocs, graduate students, and undergraduates, many of whom hold academic and industry roles globally. She emphasizes engagement in digital interventions, balancing personalization with ethical considerations. Her lab’s work spans algorithm development, clinical trial design, and causal inference, aiming to improve health outcomes through adaptive interventions.

• Statistical Reinforcement Learning
• Mobile Health (mHealth)
• Clinical Trials
• +3 more