جست‌وجوی استاد و پژوهشگر

• Epidemiology
• Public Health
• Infectious Diseases
• +۳ مورد دیگر

FRAGAKI GEORGIA is an Associate Professor at the School of Medicine , University of Ioannina , serving within the Department of Hygiene and Epidemiology . Her research portfolio spans epidemiology, public health, infectious diseases, health policy, medical statistics and preventive medicine. She maintains an active research group that has produced over 150 peer-reviewed publications (2016-2023) and currently mentors four doctoral students. Education & Training: MD – University of Athens, Greece MSc in Epidemiology – London School of Hygiene & Tropical Medicine, UK PhD in Public Health – University of Ioannina, Greece Post-doctoral fellowship – European Centre for Disease Prevention & Control (ECDC) Research Focus: Dr Fragaki’s work centres on the epidemiology of infectious diseases and the evaluation of public-health interventions. Using advanced statistical and molecular methods, she studies vaccine-preventable diseases, antimicrobial resistance, and the societal determinants of health. Recent projects include national seroprevalence surveys for SARS-CoV-2 and economic evaluations of targeted hepatitis B vaccination strategies. Scientific Awards & Distinctions: Excellence in Research Award 2018 – Hellenic Epidemiological Society Young Investigator Award 2015 – European Public Health Association Students & Mentorship: Dr Fragaki currently supervises four PhD candidates: Maria Papadopoulou (HPV epidemiology), Ioannis Karamanlis (antimicrobial stewardship), Eleni Nikolaidou (health economics of vaccination), and Dimitrios Georgiadis (COVID-19 modelling). Laboratory & Collaborations: She heads the Infectious Disease Epidemiology Laboratory at the University of Ioannina, a WHO-collaborating centre for surveillance training. Ongoing funded projects include a Horizon Europe grant on vaccine hesitancy (€1.4 M) and a Greek-German bilateral project on carbapenem-resistant Enterobacteriaceae (€0.8 M).

Eric V. Sludمشاهده پروفایل

استاد

• Mathematical Statistics
• Probability
• Census Statistics
• +۱۱ مورد دیگر

Eric V. Slud is a Professor in the Statistics Program within the Department of Mathematics at the University of Maryland, College Park. He has taught numerous graduate-level statistics courses including Mathematical Statistics, Categorical Data Analysis, and High-Dimensional Statistics since at least 2017. Dr. Slud's research spans several key areas of mathematical statistics and probability. His work focuses on: Census statistics, particularly demographic modeling of nonresponse to national surveys Small Area Estimation (SAE) with applications to the SAIPE program Survival data analysis including semiparametric inference and clinical trial design Meta-analysis in biostatistics Pharmaceutical statistical methods Large-scale data problems with emphasis on cross-classified data His publications demonstrate continued contributions across these domains, with particular emphasis on small area estimation methodologies, survival analysis techniques, and applications in survey statistics. Dr. Slud has developed innovative approaches to weighting adjustment, nonresponse correction, and estimation with complex survey data. Dr. Slud has advised several PhD students including Yang Cheng (2004), Sophie Tsou (2005), and others working on topics ranging from Factor Analysis to Survival Data. He has collaborated extensively with researchers at the Census Bureau and FDA. Dr. Slud maintains active research programs through multiple Research Interaction Teams (RITs) at the University of Maryland, focusing on advanced statistical methodologies and their applications to real-world problems in census methodology, healthcare, and other domains requiring sophisticated statistical analysis.

Han Chenمشاهده پروفایل

دانشیار

• Physical Activity
• Kinesiology
• Physical Education Pedagogy
• +۴ مورد دیگر

Dr. Han Chen is an Associate Professor at Valdosta State University specializing in physical activity research, physical education pedagogy, and school-based health interventions. He holds a Ph.D. in Kinesiology from West Virginia University, an M.Ed. in Physical Education Pedagogy from Shanghai University of Sport, and a B.Ed. in Coaching Sport from Shanghai University of Sport. Research Focus: Multivariate factors influencing physical activity, cross-cultural validation of behavioral scales, and technology-driven interventions (e.g., active video games) for youth and older adults. Key Contributions: Systematic reviews and meta-analyses on global physical activity levels, measurement invariance studies, and validation of psychometric tools for physical education contexts. Publications: His work spans physical activity correlates, fall prevention in older adults, and the interplay between BMI, fitness, and health outcomes across populations. Contact: hanchen@valdosta.edu | PE 1121, Valdosta State University, 1500 N. Patterson St., Valdosta, GA 31698.

Steve Amireaultمشاهده پروفایل

دانشیار

• Health behavior theory
• Maintenance of behavior change
• Longitudinal study design
• +۷ مورد دیگر

Steve Amireault is an Associate Professor in the Department of Health and Kinesiology at Purdue University, with a courtesy appointment in the Department of Public Health. His research focuses on health behavior theory, physical activity behavior, psychological well-being, and longitudinal study design. PhD (2013), MSc, and BSc from Université Laval Research areas: Exercise Psychology, Behavior Change Maintenance, Aging Populations His work investigates the interplay between stress, identity, and physical activity sustainability, particularly in midlife and older adults. He employs systematic review and meta-analysis methodologies to study neurocognitive effects of acute exercise and behavioral interventions for cancer survivors. Current projects examine fall-related risk factors, peer support mechanisms, and environmental influences on physical activity. Recent publications highlight trends in behavioral reactivity , motivational mediation , and psychosocial determinants of activity maintenance. While no specific awards are listed, his role involves mentoring and contributing to systematic reviews in health psychology.

• Clinical Trials
• Randomized Controlled Trials
• Bayesian Statistics
• +۸ مورد دیگر

Dr. Guangyu Tong is an Assistant Professor of Cardiovascular Medicine at the Yale School of Medicine with a secondary appointment as Assistant Professor of Biostatistics at the Yale School of Public Health. He directs the Cardiovascular Medicine Analytics Center (CMAC), providing critical analytic support for Yale's cardiovascular research community. Dr. Tong maintains faculty affiliations with multiple interdisciplinary centers including the Center for Methods of Implementation and Prevention Science (CMIPS), the Data Management and Statistics Core of the Alzheimer's Disease Research Center (ADRC-DMSC), the Center for Interdisciplinary Research on AIDS (CIRA), and the Interdepartmental Foci of Firearm Injury Prevention (FIP). His educational background includes a PhD from Duke University, an MA from Columbia University, and an AB from Peking University. Dr. Tong's research spans three major pillars: methodological innovation in trial design (particularly cluster randomized trials and stepped wedge designs), cardiovascular medicine applications, and firearm injury prevention research. His methodological contributions include advances in sample size estimation, treatment effect heterogeneity analysis, and complex trial designs with unequal cluster sizes. Dr. Tong's publications reveal a strong focus on translating statistical methods into clinical and public health applications. His work bridges Bayesian statistics with causal inference frameworks to address complex real-world problems like treatment effect heterogeneity in pragmatic trials and survivor average causal effects in studies with mortality outcomes. His research has appeared in top journals including Annals of Applied Statistics, Statistics in Medicine, and American Journal of Epidemiology. Faculty Scholar, National Institute on Aging's IMPACT Collaboratory (2023) Statistical Editor of the Journal of the American College of Cardiology (JACC) Associate Editor for BMC Medicine Principal Investigator on multiple NIH-funded trials As a senior statistician for the Great Smoky Mountain Study (GSMS), Dr. Tong examines how childhood exposures influence long-term mental health and firearm-related behaviors, directly informing policy debates around 'red flag' laws and age-based firearm restrictions. His collaborative work spans numerous NIH-funded projects including PULESA-UGANDA, TRANSFORM-HF, TRUE HAVEN, G4H, and iDOVE2.

• Artificial Intelligence
• Natural Language Processing
• Machine Learning
• +۷ مورد دیگر

Paulo Miguel Torres Duarte Quaresma is a Full Professor at the Department of Informatics, Universidade de Évora, Portugal, and Senior Researcher at Centro ALGORITMI. His career spans roles as Vice-Rector for Research and Innovation (2022–2025), Director of the School of Science and Technology (2009–2013), and Member of FCT’s Board of Directors (2021). Holding a PhD in Informatics (specialized in AI/NLP) from Universidade Nova de Lisboa and a Habilitation in Informatics from Universidade de Évora, he leads the AI & BigData Lab (equipped with 10 petaflop NVIDIA DGX-A100 supercomputers) and co-coordinates PORTULAN CLARIN, a €2M FCT-funded language technology infrastructure. Current Affiliation: Universidade de Évora (since 1997) Research Labs: AI & BigData Lab, PORTULAN CLARIN, VISTA Lab, NOVA LINCS (2019–2021) His research focuses on Artificial Intelligence and Natural Language Processing , with applications in legal reasoning , medical informatics , geospatial accident analysis , and semantic web technologies . Recent work includes creating European Portuguese BERT models, analyzing 18th-century health texts, and developing AI solutions for clinical triage. Advising highlights include supervising 7 PhD and 26 MSc theses. He chairs international conferences like PROPOR (2020) and IDEAL (2023), and participates in projects integrating AI with public administration and regional development through Alentejo2020 funding.

Ulrik Fredrik Maltمشاهده پروفایل

استاد

• Bipolar Disorder
• Depression
• Neuropsychiatry
• +۶ مورد دیگر

Ulrik Fredrik Malt is a Professor at the University of Oslo's Faculty of Medicine, specifically within the Institute of Clinical Medicine's Division of Clinical Neuroscience. His research is centered at the Oslo University Hospital (OUS) Ullevål campus where he maintains a visiting address at Kirkeveien 166, 0450 Oslo. As a prominent figure in neuropsychiatric research, Malt leads investigations into the neurobiological underpinnings of mood disorders with particular emphasis on bipolar disorder and depression. Malt's research interests span multiple interconnected domains within clinical neuroscience. His primary focus involves examining structural and functional brain changes in bipolar disorder using advanced neuroimaging techniques. He has conducted extensive work on cortical plasticity, particularly investigating how mood episodes correlate with cortical thinning patterns over time. His research also explores the intersection of immunology and psychiatry, examining cytokine profiles in depression and their relationship to symptom severity and pain perception. Additional research strands include the study of alexithymia in mood disorders, sleep deprivation effects on brain microstructure, and somatic symptom disorders in both psychiatric and medical patient populations. Analysis of Malt's recent publications reveals a strong emphasis on collaborative mega-analyses through the ENIGMA consortium, where he contributes to large-scale neuroimaging studies of bipolar disorder involving thousands of participants across multiple international sites. His work consistently integrates clinical psychiatry with advanced computational methods to identify brain-based biomarkers for mood disorders. The research demonstrates particular attention to how metabolic factors like obesity interact with brain morphology in bipolar disorder, and how inflammatory markers correlate with clinical symptoms in major depression. Malt actively participates in research on heart transplantation patients' psychological outcomes, examining anxiety, depression, and cognitive function in this medically complex population. His work spans multiple clinical contexts including organ transplantation, chronic obstructive pulmonary disease, and congenital gastrointestinal conditions, demonstrating a broad application of psychiatric principles across medical specialties. As part of the Brain Plasticity and Neuropsychiatry research group, Malt supervises multiple projects investigating longitudinal brain changes in psychiatric disorders. His laboratory employs multimodal neuroimaging approaches combined with detailed clinical phenotyping to understand the progression of mood disorders. Current research directions include examining how sleep architecture affects cortical plasticity markers, investigating the neural correlates of emotional processing difficulties in bipolar disorder, and exploring the relationship between inflammatory processes and structural brain changes in depression.

Marian-Andrei Rizoiuمشاهده پروفایل

دانشیار

• Behavioral Data Science
• Misinformation and Disinformation Analysis
• Information Operations
• +۱۲ مورد دیگر

Marian-Andrei Rizoiu is an Associate Professor leading the Behavioral Data Science lab at the University of Technology Sydney's Data Science Institute, Faculty of Engineering and Information Technology. He holds concurrent appointments as an Honorary Lecturer at Australian National University and Honorary Research Scientist at Data61. Previously, he has held visiting professor positions at Imperial College London, Jean Monnet University, and Max Planck Institute for Software Systems. Associate Professor in Behavioral Data Science, UTS Data Science Institute (Jan 2024 - present) Senior Lecturer in Behavioral Data Science, UTS Data Science Institute (Jul 2021 - Jan 2024) Lecturer in Computer Science, UTS Faculty of Engineering and Information Technology (Feb 2019 - Jul 2021) Dr. Rizoiu's research focuses on interdisciplinary work crossing computer and social sciences, blending psycholinguistics, digital communication, and stochastic modeling to understand human attention dynamics online, the emergence of influence, and opinion polarization. His key contributions include developing theoretical models for online information diffusion that can account for complex social phenomena, and building skill-based real-time occupation transition recommender systems that link social media-predicted personality profiles with occupation skill requirements. His research outputs reveal strong trends in misinformation detection, social influence measurement, and online radicalization pathways. Recent publications demonstrate sophisticated modeling approaches including state space models for early misinformation prediction, multivariate Hawkes processes for analyzing partially interval-censored data, and ideology detection pipelines. His work spans computational social science, machine learning, and practical applications for countering harmful online content. Excellence Award and Academic of the Year at the 2023 Australian Defence Industry Awards ADMA'22 Best Application Paper Dr. Rizoiu has successfully secured over $2.9 million in research funding from selective funders including Meta Research, Defence Science and Technology Group, Department of Home Affairs, and Defence Innovation Network. He has supervised 3 PhD students to completion and more than 10 Honours students, most achieving High Distinction. His research has been applied in real-world contexts including serving as an expert for NSW government's Defamation Law Reform and providing evidence for Australian Federal Senate inquiry into media diversity. He leads the Behavioral Data Science lab which focuses on modeling human behavior in online environments, with particular emphasis on mis- and disinformation detection and labor market analysis. The lab has developed tools like TRACK, UTS OPEN's software for recommending personalized learning pathways, used by over 750 students and professionals.

• Biostatistics
• Statistics
• Non-parametric Methods
• +۵ مورد دیگر

Dr. Ahmad Farooqi serves as Assistant Professor at Central Michigan University College of Medicine, where he provides statistical leadership through the Clinical Research Institute (CRI). He delivers weekly statistics instruction to medical trainees at Children's Hospital of Michigan and offers comprehensive analytical support for clinical research projects across the institution. His academic credentials include: Ph.D. in Biostatistics from Wayne State University M.S. and M.A. in Statistics from University of Windsor M.Phil in Statistics from Government College University, Lahore Dr. Farooqi's research pioneers non-parametric, robust, and exact statistical methodologies applied to pediatric clinical challenges. His work addresses critical gaps in small-sample clinical studies through innovative approaches to longitudinal data analysis, survival modeling, and diagnostic accuracy assessment. As a SAS-certified expert, he implements advanced techniques across SAS, R, and SPSS environments to solve complex analytical problems in cardiology, emergency medicine, and immunology research. His publication record demonstrates consistent high-impact contributions across pediatric specialties, with particular emphasis on cardiac outcomes, emergency department operations, and immunological responses. The research portfolio reveals strong methodological rigor combined with practical clinical applications, often addressing resource-constrained scenarios requiring robust analytical solutions. Key recognitions include: Best Article Award in Pediatric Neurology (2019) Best Paper Award at ICCS-15 statistical conference Wayne State University Full Tuition Scholarship Dr. Farooqi actively mentors medical researchers through statistical consulting and teaching, with collaborations spanning multiple departments and international institutions. His role in the CRI facilitates cross-disciplinary research partnerships while advancing methodological standards in clinical investigation. Current work focuses on refining statistical approaches for pediatric cardiac interventions and emergency care protocols through ongoing clinical data analysis projects.

• Psychometrics
• Statistical Methods
• Educational Psychology
• +۴ مورد دیگر

Dr. Yen Lee is an Assistant Professor and LTCOS Research Data Analyst at the Center for Health Professions Education (CHPE) within the School of Medicine of the Uniformed Services University of the Health Sciences in Bethesda, MD. She specializes in interdisciplinary research bridging psychometrics, health education, and statistical methodology. Education: Ph.D. in Educational Psychology, University of Wisconsin-Madison (2020) M.S. in Psychology, National Chengchi University (2010) B.S. in Psychology, National Taiwan University (2004) Her research addresses statistical challenges in empirical studies, including small-sample robustness and normality-violation mitigation. She collaborates across domains like educational policy, health outcomes, developmental psychology, and speech pathology, employing advanced quantitative methods to improve research validity. Recent publications reflect broad interdisciplinary engagement, with thematic clusters in: Healthcare decision-making and patient outcomes Educational pathways and equity in community colleges Social media's impact on adolescent development Psychometric innovations for ordinal data

• Orthopedic Surgery
• Trauma Surgery
• Hip Fracture Research
• +۴ مورد دیگر

Clinical Professor Jes Bruun Lauritzen serves in the Department of Clinical Medicine within the Faculty of Health and Medical Sciences at the University of Copenhagen, specializing in Orthopaedic Surgery. His clinical work and research are closely affiliated with Region Hovedstaden healthcare services, operating from dual campus locations at Bispebjerg Bakke 23 (2400 København NV) and Blegdamsvej 3 (2200 København N). Professor Lauritzen's research focuses on critical challenges in geriatric orthopedics, particularly hip fracture outcomes , mortality predictors , and comorbidity impacts . His work leverages Denmark's comprehensive national registries to investigate 30-day mortality risks, blood transfusion efficacy with tranexamic acid, and machine learning applications for mortality prediction. Additional research areas include ACL reconstruction outcomes, bone healing indicators in conservative fracture management, and digital prehabilitation tools for surgical optimization. His publication record demonstrates significant contributions to trauma surgery literature, with multiple high-impact studies in European Journal of Trauma and Emergency Surgery , Calcified Tissue International , and Journal of Clinical Endocrinology and Metabolism . Recent work shows increasing integration of computational methods and digital health interventions alongside traditional epidemiological approaches. Professor Lauritzen actively collaborates with regional hospitals and research groups across Scandinavia, with his work receiving substantial attention in both clinical practice circles and academic discourse as evidenced by Mendeley readership and social media mentions.

• Applied Statistics
• Biostatistics
• Data Communications
• +۵ مورد دیگر

Tareq Alodat is a Lecturer in Statistics and Data Science at the Mathematics & Statistics school of La Trobe University in Melbourne, Australia. He simultaneously holds a Postdoctoral Research Fellow position at UNSW Australia's School of Mathematics and Statistics in Sydney. His academic background includes: PhD from La Trobe University, Melbourne, Australia (2016-2019) Dr. Alodat's research expertise spans theoretical and applied statistics with significant contributions to long-range dependent processes, stochastic modeling, and nonparametric methods. His work bridges probability theory with practical applications in ecology, medical research, and spatial statistics. He has developed novel statistical approaches for complex data structures and contributed to distribution theory, particularly with generalized skew-normal distributions. Analysis of his publication trajectory reveals increasing specialization in fractional stochastic differential equations applied to spherical geometry, alongside continued work in ecological statistics. His research demonstrates consistent theoretical development paired with practical applications across diverse domains, with recent publications showing sophisticated mathematical techniques applied to real-world problems. Dr. Alodat serves as a reviewer for several prominent journals including Communications in Statistics-Simulation and Computation, Symmetry-Basel, and Entropy, reflecting his standing in the statistical community.

Shelley Tworogerمشاهده پروفایل

استاد

• Cancer Epidemiology
• Breast Cancer Etiology
• Ovarian Cancer Prevention
• +۵ مورد دیگر

Dr. Shelley Tworoger is Professor and Head of the Division of Oncological Sciences at Oregon Health & Science University (OHSU) School of Medicine, and Associate Director of Population Science at OHSU Knight Cancer Institute. Her research employs integrative epidemiologic approaches to elucidate breast and ovarian cancer etiology, with emphasis on risk factors (e.g., psychological distress, lifestyle), tumor microenvironment interactions, survival determinants, and large-scale biorepositories. She leads the ovarian cancer efforts in the Nurses’ Health Studies and co-directs the Ovarian Cancer Cohort Consortium. Education: Earned PhD in Epidemiology from University of Washington; completed postdoctoral training and faculty appointments at Harvard T.H. Chan School of Public Health and Harvard Medical School. Research Focus: Primary investigations include: (1) Novel risk factor discovery (e.g., psychological distress) and mechanistic pathways in women’s cancers; (2) Host-tumor microenvironment crosstalk; (3) Survival determinants in cancer patients; and (4) Consortial study designs. She maintains strong expertise in biomarker integration for epidemiologic studies. Publication Trends: Her >430 publications (140+ as senior author) predominantly focus on ovarian/breast cancer molecular epidemiology, spanning biomarker validation (e.g., CA125, prolactin), immunotherapy interactions, genetic susceptibility, and psychosocial impacts. Recent work integrates multi-omics, immunogenomics, and electronic health records to decipher risk mechanisms. Mentorship & Leadership: Mentored ~50 trainees and junior faculty, many now in academic roles globally. Actively promotes leadership diversity through tailored mentoring programs and directs population science initiatives at the Knight Cancer Institute. Funding & Infrastructure: Continuously holds NIH R01-level funding since 2006 and oversees major biorepository resources for cohort studies.