جستجوی استاد راهنمای دانشگاهی

Rick Hoyleمشاهده پروفایل

استاد

• Self-Regulation
• Adolescent Development
• Goal Pursuit
• +۵ مورد دیگر

Rick Hoyle is a Professor of Psychology and Neuroscience at Duke University, where he serves as Associate Chair of the Department of Psychology and Neuroscience. He is also a Faculty Network Member of the Duke Institute for Brain Sciences. His academic career spans decades, with significant contributions to understanding self-regulation and adolescent development. Dr. Hoyle earned his B.A. from Appalachian State University (1983), followed by an M.A. (1986) and Ph.D. (1988) from the University of North Carolina, Chapel Hill. He progressed from Assistant to Associate to Full Professor at the University of Kentucky from 1989 to 2003 before joining Duke University. His research focuses on how adolescents and emerging adults manage goal pursuit through self-regulation, taking a broad view that accounts for personality, environment, cognition, emotion, and social influences. He employs longitudinal methods with repeated assessments, sometimes spanning years with data collection multiple times per year, or intensive studies with assessments several times daily. His lab develops innovative measurement tools including self-report measures of self-control and grit, as well as unobtrusive approaches using mobile phones and wearable devices to track goal pursuit in natural settings. His recent publications reveal a strong focus on self-regulation in digital contexts, adolescent substance use, socioeconomic influences on development, and innovative measurement approaches. His work increasingly integrates technology (social media analysis, wearable devices) with traditional psychological research methods to understand real-world behavior. Fellow, Association for Psychological Science (2013) Dr. Hoyle has secured numerous research grants totaling millions of dollars, including the current Real-Time and Randomized Tests of Social Media and Mental Health Links in Early Adolescence (2024-2029), NCCU Duke - Substance Use Research & Education (2024-2029), and Mid-Life Health Inequalities in the Rural South: Risk and Resilience (2023-2028). His grant portfolio demonstrates sustained funding for research on adolescent development, substance use, self-regulation, and health disparities. He teaches advanced courses including Applied Structural Equation Modeling and Psychology and Neuroscience Grant Writing, mentoring the next generation of researchers in quantitative methods and research design. His work through the Center for the Study of Adolescent Risk and Resilience (2008-2025) has established a significant research infrastructure for longitudinal studies of adolescent development. Current projects examine social media effects on mental health, substance use patterns, and the impact of environmental factors on adolescent well-being using innovative digital tracking methods.

Catherine Pollingمشاهده پروفایل

مدرس

• Psychiatric Epidemiology
• Self-harm
• Health Inequalities
• +۵ مورد دیگر

Catherine Polling is an NIHR Clinical Lecturer in General Psychiatry at King’s College London (KCL), affiliated with the Institute of Psychiatry, Psychology & Neuroscience (IoPPN) and the Health Inequalities Research Group . Her work focuses on mental health inequities, self-harm epidemiology, and mixed-methods research, particularly in urban and marginalized communities. Education: MBBS from University College London, MSc in Epidemiology from the London School of Hygiene and Tropical Medicine, PhD from KCL's Department of Psychological Medicine Research Interests: Catherine investigates health disparities in mental health services using advanced statistical methods (multi-level modeling, Bayesian disease mapping) and GIS-based data visualization. Her clinical work with the South London and Maudsley NHS Foundation Trust complements her academic focus on systemic racism and mental health outcomes. Teaching & Engagement: She lectures on urban mental health for KCL’s Urban Informatics MSc and co-leads training on racism in mental health services. She also facilitates reflective practice groups accredited by the Balint Society and contributes to curriculum reform via the Maudsley Cultural Psychiatry Group. Scientific Awards: NIHR Clinical Lecturer Fellowship Wellcome Training Fellowship Research Trends: Her publications emphasize self-harm risk factors, pandemic impacts on healthcare workers, ethnic disparities in mental health services, and the intersection of urban environments with mental health outcomes. She integrates large-scale clinical datasets, qualitative interviews, and spatial analysis to address systemic inequities.

Bärbel Finkenstädt Randمشاهده پروفایل

مربی

• Statistical Methodology
• Machine Learning
• Bayesian Inference
• +۶ 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.

Wolfgang Lutzمشاهده پروفایل

استاد

• Clinical Psychology
• Psychotherapy Research
• Precision Mental Health Care
• +۷ مورد دیگر

Prof. Dr. Wolfgang Lutz is a Full Professor and Head of the Department of Clinical Psychology and Psychotherapy at the Faculty of Psychology, University of Trier, Germany. He also serves as Director of the Outpatient Clinic and Postgraduate Clinical Training. Additionally, he holds an Adjunct Professor position at the University of Western Australia and is a Fellow of the Association for Psychological Science (APS). Dr. Lutz's research focuses on advancing clinical psychology and psychotherapy through precision mental health care, treatment personalization, and feedback-informed psychological therapy. His work emphasizes using data-driven approaches to optimize treatment outcomes, with particular attention to depression, anxiety disorders, and PTSD. He has pioneered the development of the Trier Treatment Navigator (TTN), a system for feedback-informed treatment that helps match patients to the most effective therapeutic approaches. His recent publications reveal a strong emphasis on integrating technology and artificial intelligence into psychotherapy research and practice. This includes developing algorithms for personalized therapy, using large language models to analyze therapy sessions, and implementing routine outcome monitoring systems. His research shows how temporal dynamics in therapy processes affect outcomes and how clinical microskills can predict therapeutic alliance and success. Fellow of the Association for Psychological Science (APS) Editor of Psychotherapy Research He leads initiatives to develop a European Psychotherapy Consortium (EPoC) to standardize outcome measurement across countries and promote cooperation in psychotherapy research. His laboratory focuses on precision mental health care, developing tools for treatment personalization, and investigating the mechanisms of change in psychotherapy.

Sinead Langanمشاهده پروفایل

استاد

• Clinical Epidemiology
• Immune-Mediated Inflammatory Diseases
• Atopic Eczema
• +۴ مورد دیگر

Professor Sinead Langan is a leading clinical epidemiologist at the London School of Hygiene & Tropical Medicine (School of Epidemiology and Population Health, Department of Non-communicable Disease Epidemiology). She maintains dual roles as a clinical dermatologist at St John's Institute of Dermatology, Guy's and St Thomas' Hospital, and as academic director for Health Data Research UK London. Queen's University Belfast (MD) - 2005 University of Nottingham (PhD) - 2011 University of Pennsylvania (Visiting Scholar) - Postdoctoral Her research spans two critical domains: Immune-Mediated Inflammatory Conditions : Leading groundbreaking work on atopic eczema and psoriasis using 17 million patient records through OpenSAFELY platform, revealing novel associations between severe eczema and cardiovascular outcomes Health Data Methodology : Co-founder of the RECORD initiative (www.record-statement.org) that establishes international standards for observational health data reporting Recent publications analyze: Gene-environment interactions in eczema Development of standardized protocols for routine health data analysis Cardiovascular risks in inflammatory skin diseases Long-term developmental impacts of atopic disease Pandemic effects on healthcare delivery Key awards include: Fellow of Association of Physicians (2025) National Clinical Impact Award (2022-2027) ONS Excellence & People's Choice Awards (2022) British Society Medical Dermatology Prize (2022) She directs: Coronavirus School Infection Survey (150 schools) NHS indirect effects monitoring during pandemic

Serkan Arıkanمشاهده پروفایل

دانشیار

• Educational Measurement and Evaluation
• Computerized Adaptive Testing
• Large-Scale Educational Assessments
• +۵ مورد دیگر

Assoc. Prof. Dr. Serkan Arıkan is a faculty member at Boğaziçi University's Faculty of Education, Department of Mathematics Education. His research focuses on educational measurement, computerized adaptive testing, non-routine problem solving, and large-scale assessment frameworks like PISA and TIMSS. He has developed psychometric tools for STEM competency evaluation and conducted bias detection studies in international exams. Education : PhD in Secondary Science and Mathematics Education (METU, 2010), Postdoc (Tilburg University, 2015) Awards : Outstanding Achievement in Teaching Award (2021-2022) Research Trends : His recent work includes psychometric validation of self-compassion scales, extending the Community of Inquiry framework for technology integration, and adaptive test design using multiple matrix sampling. He investigates how socioeconomic factors, item bias, and emotional skills intersect with academic performance. Projects : Leads TÜBİTAK-funded AI-based test design and computerized adaptive mathematics test initiatives. Conductor of Boğaziçi University Adaptive Testing Laboratory.

Nadine Scholtenمشاهده پروفایل

استاد

• Organizational health services research
• Implementation of innovations in healthcare
• Patient and provider perspectives in care
• +۳ مورد دیگر

Prof. Dr. Nadine Scholten is a faculty member at the University Hospital Bonn , leading the Health Communication and Health Services Research (CHSR) center since 2024. She works within the Clinic for Psychosomatic Medicine and Psychotherapy under Prof. Geiser, affiliated with the Medical Faculty of the University of Cologne , where she earned her doctorate and habilitation and leads the LiVe working group . Research focus: Organizational health services research in hospital settings, implementation of therapies/innovations, secondary data analysis, patient/provider perspectives, cross-sectoral healthcare coordination, and regional health services. Current projects include Neo-Milk (donor milk banks in NICUs), Neo-CamCare (webcam use in NICUs), CoRe-Net (regional health development), and studies on outpatient antimicrobial therapy and pandemic impacts on healthcare. Teaching: Leads health communication skills training in medicine. Memberships: DNVF e.V., DGMS, AGENS (secondary data working group). Recent article trends: Focus on data linkage, patient experience, pandemic-era care adaptations, and cross-sectoral healthcare integration, with methodologies spanning qualitative/quantitative analysis of routine data (statutory insurance, DRG statistics).

Julian Matthewmanمشاهده پروفایل

پژوهشگر ارشد

• Electronic health records
• Epidemiology
• Pharmacoepidemiology
• +۷ مورد دیگر

Dr. Julian Matthewman is a Research Fellow in the Department of Non-communicable Disease Epidemiology within the Faculty of Epidemiology and Population Health at the London School of Hygiene & Tropical Medicine (LSHTM). He is also an academic liaison for the Alan Turing Institute, the UK's national institute for data science and artificial intelligence, and serves as a theme lead for LSHTM's Centre for Data and Statistical Science for Health (DASH). Dr. Matthewman completed his medical degree at the Medical University of Vienna, followed by an MSc and PhD in Epidemiology at LSHTM. His educational background reflects a strong foundation in both clinical medicine and epidemiological research methods. As a clinically-trained epidemiologist, Dr. Matthewman focuses on electronic health records research related to non-communicable diseases, with particular emphasis on skin and inflammatory conditions including eczema and psoriasis. His work spans multiple areas including pharmacoepidemiology, mental health comorbidities in dermatological conditions, and methodological research for electronic health record analysis. His research often involves large-scale population studies using UK primary care data. His publication record demonstrates a consistent focus on methodological rigor in electronic health record research, with recent work examining comorbidities in atopic eczema, developing codelists for routine health data research, and investigating medication safety. His articles frequently address the intersection of dermatology, epidemiology, and data science, with notable contributions to understanding the broader health implications of skin conditions. Dr. Matthewman actively contributes to education by organizing the short course "Introduction to Pharmacoepidemiology" and teaching on courses including "Analysis of Electronic Health Records" and "Data Challenge". He supervises summer projects for MSc Epidemiology and MSc Health Data Science students and organizes LSHTM's R user group, supporting computational skills development within the institution. His work spans multiple collaborative projects, particularly those involving the Alan Turing Institute and LSHTM's Centre for Data and Statistical Science for Health. He has developed numerous codelists and computational tools that support reproducible research in electronic health records, contributing significantly to methodological standards in the field.

Andreas Stadlbauerمشاهده پروفایل

استاد مدعو

• Biomedical Imaging
• Medical Physics
• Artificial Intelligence in Medicine
• +۷ مورد دیگر

Prof. Dr. Andreas Stadlbauer is a medical physicist affiliated with the Clinical Institute for Diagnostic and Interventional Radiology at St. Pölten University Hospital and the Department of Neurosurgery at Friedrich-Alexander University Erlangen-Nuremberg. He holds an adjunct professorship at the University of Erlangen-Nuremberg and contributes to both clinical and academic research in biomedical imaging and AI applications in oncology. University: Friedrich-Alexander University Erlangen-Nuremberg Hospital Affiliation: St. Pölten University Hospital Department: Department of Neurosurgery Academic Rank: Adjunct Professor His research focuses on advanced MRI techniques, particularly physio-metabolic imaging of brain tumors, oxygen metabolism, and the integration of artificial intelligence in clinical diagnostics. He has led research on glioma classification, tumor microenvironment characterization, and deep learning models for radiomic analysis. The recent publications highlight a strong trend toward AI-driven diagnostic tools in neuro-oncology, particularly in differentiating glioblastomas from metastases and predicting genetic mutations using machine learning. His work emphasizes the clinical translation of complex imaging data into actionable insights. Artificial Intelligence in Oncology Medical Imaging and Radiomics Brain Tumor Metabolism Deep Learning for MRI Analysis Oxygen Metabolism Imaging Clinical Decision Support Systems Prof. Stadlbauer has been involved in seed-funded research projects developing deep learning algorithms for clinical integration. He collaborates extensively with neurosurgeons, radiologists, and oncologists across institutions, contributing to multidisciplinary tumor boards and translational research initiatives. He completed his doctorate in medical physics in 2004, habilitation in 2008, and an MBA in Health Management in 2010. His academic journey reflects a blend of technical expertise and leadership in healthcare innovation.

• Chiral Recognition
• Enantiomeric Separations
• Ionic Liquids
• +۵ مورد دیگر

Daniel W Armstrong is a Professor at the University of Texas at Arlington in the Department of Chemistry and Biochemistry. With over 35 years of experience, he is a pioneering figure in chiral recognition, enantiomeric separations, and the biological relevance of D-amino acids. His work has led to over 740 publications, 35 patents, and 560 invited seminars worldwide. Developed first chiral recognition mechanism by cyclodextrins First to use macrocyclic antibiotics as chiral selectors Synthesized most new ionic liquids (ILs) globally Created ultra-fast separation techniques now standard in analytical chemistry Contributed to FDA 1992 guidelines on chiral drug separation His research focuses on chiral separations, ionic liquids, and the role of D-amino acids in biological systems. He has commercialized over 30 HPLC and GC columns, transforming analytical chemistry and pharmaceutical analysis. Recent publications demonstrate continued innovation in chiral chromatography, biomarker analysis, and AI-driven separation optimization. His grants include industry collaborations with Merck, Alcon, and Sigma-Aldrich, emphasizing practical applications of his work. Scientific honors include multiple lifetime achievement awards, fellowships in the Royal Society of Chemistry and American Chemical Society, the Chirality Medal, and induction into the National Academy of Inventors. He has mentored over 100 PhD students, many from first-generation college backgrounds.

• Epidemiology
• Biostatistics
• Rheumatology
• +۳ مورد دیگر

Dr Sara Muller is a Reader in Epidemiology and Statistics at the School of Medicine, Keele University. She holds a Master’s in Biometry and a PhD in epidemiology, focusing on locomotor disability measurement using Rasch Analysis. Her research emphasizes primary care rheumatology (polymyalgia rheumatica, gout, inflammatory arthritis) and methodological innovations in healthcare data analysis. She is the Academic Career Development Lead for the NIHR Applied Research Collaboration West Midlands and actively promotes researcher development. Her teaching includes leading the Research and Analytical Skills module for undergraduates. Education: MSc Biometry, PhD (Epidemiology) Awards: Fellow of the Royal Statistical Society Dr Muller’s research spans epidemiological methodology, routinely collected healthcare data, and ordinal regression models. Her work often addresses patient-reported outcomes in rheumatology, with over 200 publications in journals like *Rheumatology* and *BMJ Open*. She collaborates with the Society for Academic Primary Care and serves as a former Associate Editor for *Family Practice*. Her recent articles highlight trends in Parkinson’s disease mortality, gabapentinoid risks in arthritis patients, and healthcare utilization patterns in fibromyalgia. She also explores digital health equity and public health implications of chronic conditions. Key Projects: PMR Cohort Study, ICEPAC survey on rheumatic disease impact Grants: NIHR-funded collaborations Dr Muller’s work bridges clinical and public health perspectives, with a focus on improving patient outcomes through evidence-based practices and data-driven solutions.

Ammar Hooriمشاهده پروفایل

دانشگاهی

• Cardiac Imaging
• Data Science
• Artificial Intelligence
• +۷ مورد دیگر

Ammar Hoori, PhD, is a Research Assistant Professor in the Department of Biomedical Engineering at Case Western Reserve University, affiliated with both the Case School of Engineering and School of Medicine. His research focuses on cardiac image analysis, leveraging advanced techniques like image registration, deep learning, and survival analysis. He leads NIH-funded projects involving CT calcium scoring, IVOCT, and chest CT imaging, collaborating with cardiologists from University Hospitals Cleveland and engineers from CWRU. His work emphasizes developing calcium-omics and fat-omics features to improve cardiovascular disease prediction. His research team employs cutting-edge methods such as deep learning segmentation for epicardial adipose tissue analysis, aiming to optimize patient care through AI-driven risk stratification. Hoori’s contributions include the development of the DeepFat algorithm for automated fat quantification and collaborations on stent under-expansion prediction using OCT imaging. He is also involved in the Biomedical Imaging Laboratory (BMIL), contributing to advancements in cryo-imaging and 3D visualization techniques. Key areas of innovation include AI-enabled risk prediction for heart failure, MACE (Major Adverse Cardiovascular Events), and coronary artery disease using opportunistic data from routine CT scans. His work bridges clinical and engineering expertise to advance non-invasive diagnostic tools and personalized medicine strategies.

• Substance misuse prevention
• Polysubstance use
• Alcohol epidemiology
• +۷ مورد دیگر

Dr. Gary C.K. Chan is an NHMRC Emerging Leadership Fellow at the National Centre for Youth Substance Use Research within the School of Psychology at the University of Queensland. As a statistical advisor, he provides methodological guidance to academic staff and research higher degree students. His collaborative work spans major international research institutions including the University of Washington, Murdoch Children's Research Institute, University of Melbourne, and University College London, with significant policy impact through consultation with the United Nations Office of Drugs and Crime. Dr. Chan's principal research focuses on substance misuse prevention and advanced statistical methods for longitudinal analysis. His work examines polysubstance use patterns (particularly alcohol, tobacco, and cannabis) among adolescent populations, urban-rural disparities in substance use, and the epidemiology of various substances. He applies sophisticated statistical modeling to understand complex relationships between substance use, mental health, and sociodemographic factors, with particular attention to methodological innovations in addiction research. Dr. Chan's prolific publication record demonstrates a strong focus on contemporary substance use issues, particularly cannabis and vaping trends among youth. His research employs diverse methodologies including longitudinal analysis, systematic reviews, and wastewater-based epidemiology. There's a clear emphasis on policy-relevant research that examines the impact of regulatory changes on substance use patterns, with significant contributions to understanding cannabis use for medicinal purposes and the relationship between social media exposure and substance use behaviors. Scientific Awards: NHMRC Emerging Leadership Fellowship As a statistical advisor at the School of Psychology, Dr. Chan provides methodological support to academic staff and research higher degree students. Since 2016, he has conducted advanced statistical workshops on R programming and multilevel modeling. His research is supported through the NHMRC fellowship and numerous collaborations with major national and international institutes that facilitate large-scale epidemiological studies and policy-relevant analyses. Dr. Chan is affiliated with the National Centre for Youth Substance Use Research at the University of Queensland. His collaborative network spans multiple research teams across continents, enabling comprehensive investigations of substance use patterns and their determinants in diverse populations and settings.

Emily McFaddenمشاهده پروفایل

مدرس

• Statistical Epidemiology
• Routine Healthcare Data Analysis
• Medical Research Design
• +۴ مورد دیگر

Emily McFadden is a Departmental Lecturer and Senior Statistical Epidemiologist at the University of Oxford's Nuffield Department of Primary Care Health Sciences, where she serves as a Faculty Member. She is concurrently a Fellow of Kellogg College and an active contributor to the Centre for Evidence-Based Medicine and Medical Statistics Group. Her role involves coordinating the Big Data Epidemiology module within the Evidence-Based Health Care MSc Programme and deputy-coordinating the Medical Statistics for Big Data short course (launching July 2026), alongside prior coordination of the Introduction to Study Design module and Evidence-Based Medicine theme for medical students. Education: MA from University of Cambridge PhD from University of Cambridge MSc from London School of Hygiene and Tropical Medicine Her research centers on statistical epidemiology using large routine healthcare databases to address critical gaps in medical research design. Key projects include REDUCE-HF (an NIHR SPCR-funded initiative leveraging machine learning and electronic health records to reduce heart failure diagnosis inequalities) and a breastfeeding support study examining nipple shields through community co-production. This work spans vulnerable populations like women with disabilities in sub-Saharan Africa and UK primary care settings, focusing on health service utilization patterns and intervention safety. Analysis of her 2018-2024 publications reveals consistent methodological innovation in CPRD and survey-based epidemiology, with dominant themes in heart failure diagnosis, surgical mesh complications, disability health outcomes, and breast cancer risk factors. Her cohort studies, systematic reviews, and metaanalyses emphasize reducing health inequalities through data-driven primary care improvements. Scientific awards: None explicitly documented in the provided texts. Dr. McFadden supervises DPhil and MSc students in statistical epidemiology and routinely collected data methods, actively seeking prospective students for her research areas. She has secured NIHR SPCR funding as co-Principal Investigator for two major projects: REDUCE-HF (focused on heart failure diagnosis equity) and the nipple shields breastfeeding intervention study, demonstrating her grant leadership in applied health research. Her laboratory and team affiliations include the Centre for Evidence-Based Medicine and Medical Statistics Group within the Nuffield Department, with dedicated work through the Heart Failure research stream. She maintains a decade-long governance role at CPRD as Chair of an Expert Review Committee and Central Advisory Committee (CAC) member, directly shaping research data standards for UK primary care databases.

• Behavioral Science
• Epidemiology
• Digital Interventions
• +۷ مورد دیگر

Dr. Marc A. Adams serves as the Assistant Dean of Education and Interim Program Director of the MPH in the School of Technology for Public Health at Arizona State University, while also holding a Professor position in the College of Health Solutions. He maintains additional affiliations with the Institute for Social Science Research as both a faculty member and Affiliated Faculty, and serves as a Senior Global Futures Scientist within the Global Futures Scientists and Scholars program. His academic leadership spans multiple institutional units focused on public health innovation and research. Dr. Adams' educational background includes a PhD in Public Health from the University of California, San Diego and San Diego State University (2009), an MPH in Public Health from San Diego State University (2003), a BA in Psychology from San Diego State University (2001), and postdoctoral training in Cardiovascular Epidemiology and Prevention at the University of California, San Diego (2011). As a behavioral scientist and epidemiologist, Dr. Adams' research spans the intersection of digital health interventions, physical activity promotion, and behavioral nutrition within diverse neighborhood contexts. His work integrates advanced AI and deep learning techniques to map pedestrian environment features across thousands of US neighborhoods, revealing critical inequities in built environments. He develops and tests interventions that consider how urban planning features interact with behavior change strategies to increase physical activity and healthy eating, particularly among underserved populations. His methodological expertise includes epidemiologic methodology, clinical trial design, and the development of ecological models for understanding behavior-environment interactions. Dr. Adams is an active member of the International Physical Activity and Environment Network (IPEN), contributing to international comparative research on how city design influences physical activity levels across 14 global cities. Dr. Adams' recent publications reveal a strong focus on neighborhood walkability, digital health interventions, and the use of AI to analyze built environments for public health purposes. His research consistently examines how environmental features moderate the effectiveness of physical activity interventions, with particular attention to socioeconomic disparities. The methodological approaches in his work span from traditional epidemiological studies to cutting-edge computer vision applications for analyzing street-level imagery at scale. Dr. Adams has secured substantial research funding from multiple sources including NIH, American Heart Association, and Robert Wood Johnson Foundation. His current projects include "Developing AI-measures of Pedestrian Environment Features for Physical Activity and Cancer Prevention in Rural Communities" (NIH/NCI, $413,673), "PED-PHAM: An Automated and Scalable Spatial Tool" (NIH/NHLBI SBIR, $275,000), and "WalkIT Arizona: Neighborhood walkability and moderation of adaptive interventions for physical activity" (NIH/NCI, $2,620,000). He serves as Principal Investigator on multiple projects while also collaborating as Co-Investigator on large-scale international studies through IPEN. His grant portfolio demonstrates expertise in both intervention development and environmental measurement, with a consistent focus on translating research findings into practical applications for public health practice. Dr. Adams leads research teams focused on developing and validating AI tools for assessing pedestrian environments and testing how these environmental features interact with digital health interventions. His work with the International Physical Activity and Environment Network connects him to a global consortium of researchers examining built environment influences on physical activity across diverse cultural contexts. His laboratory work bridges computer science, public health, and urban planning disciplines to create innovative approaches for measuring and improving neighborhood environments that support healthy behaviors.