جست‌وجوی استاد و پژوهشگر

• Epidemiology
• Population Health
• Healthy Aging
• +۷ مورد دیگر

Susan Kirkland, PhD, is a Research Professor and University Research Professor at Dalhousie University's Faculty of Medicine, Department of Community Health and Epidemiology. She leads major initiatives like the Canadian Longitudinal Study on Aging (CLSA) and focuses on chronic diseases, healthy aging, and frailty. Her research integrates social, physical, and genetic factors influencing aging and chronic conditions. Dr. Kirkland holds affiliations with Dalhousie's Centre for Clinical Research and collaborates with institutions like the Northwood Group and AGE-WELL National Centre of Excellence. Education: PhD (University of Toronto), MSc & BSc Honours (University of Waterloo). Her research spans population health, longitudinal cohort studies, and older adults' engagement in technology and healthcare. Awards include Dalhousie's University Research Professorship (2018–2023) and the Decade Club Award (2013). Research emphasizes aging populations, including HIV and aging, cognitive impairment, and technology for aging in place. She leads studies on frailty indices, dementia risk factors, and pandemic impacts on older adults' health. Key contributions include co-editing the Canadian Longitudinal Study on Aging and developing gerontechnology engagement frameworks like OA-INVOLVE. Grants and service roles include membership in the Canadian Institutes of Health Research's Institute of Aging Advisory Board and leadership in interdisciplinary HIV/AIDS research networks. Her work bridges clinical, epidemiological, and public health domains, addressing both individual and systemic factors affecting aging populations. Labs/Teams: Principal investigator for CLSA, Director of the Atlantic Interdisciplinary Research Network for Social and Behavioural Issues in Hepatitis C and HIV/AIDS, and collaborator in the OA-INVOLVE initiative promoting older adult involvement in research.

Jianhong Wuمشاهده پروفایل

استاد

• Applied Mathematics
• Disease Modeling
• Dynamical Systems
• +۳ مورد دیگر

Professor Jianhong Wu is a Full Professor and University Distinguished Research Professor at York University's Department of Mathematics and Statistics, holding a York Research Chair in industrial and applied mathematics. He previously served as the NSERC Industrial Research Chair in vaccine mathematics, modeling, and manufacturing (2017–2022) and Canada Research Chair in Industrial and Applied Mathematics (2001–2022). His research focuses on dynamical systems, delay differential equations, neural networks, and disease modeling, with notable contributions to global health through pandemic preparedness strategies. Research Interests: Delay Differential Equations Neural Networks Public Health Modeling Global Health Dynamics His work since the 2003 SARS outbreak has involved leading national teams to develop mathematical tools for addressing emerging infectious diseases like influenza, antimicrobial resistance, and monkeypox. He is a Fellow of the Royal Society of Canada and Canadian Academy of Health Sciences. Awards: Fellow of the Royal Society of Canada Fellow of the Canadian Academy of Health Sciences His recent publications emphasize pandemic dynamics, vaccine strategies, and interdisciplinary approaches to public health challenges, often leveraging machine learning and real-time data analytics.

• Counseling Psychology
• LGBTQIA+ Health Disparities
• Immigration and Acculturation
• +۳ مورد دیگر

Frank Dillon is a Professor at the CISA - School of Counseling and Counseling Psychology at Arizona State University. His research focuses on marginalized populations, particularly LGBTQIA+ communities and recent Latino/Latina immigrants. He examines intersections between acculturation, mental health, substance use, and healthcare access. His work integrates social ecological frameworks to address health disparities and advocate for culturally competent practices in counseling and healthcare. Key research areas include sexual identity development among sexual minority men, PrEP adherence barriers, and the impact of cultural beliefs like machismo and marianismo on health outcomes. His studies often involve longitudinal designs and community-based methodologies to understand systemic inequities. Recent work has expanded into digital mental health interventions (e.g., AFFIRM online) targeting LGBTQQA+ youth. Publications consistently highlight structural determinants of health, such as neighborhood collective efficacy and religious coping mechanisms. He advocates for queer-inclusive curricula in health professions and has developed assessment tools like the Sexual Minority Affirmative Practice Scale to measure clinical competency. Though no awards are listed, his extensive publication record reflects sustained contributions to health equity research.

John Bartonمشاهده پروفایل

دانشیار

• Virology
• Immunology
• Evolutionary Biology
• +۶ مورد دیگر

John Barton, PhD, is an Associate Professor in the Department of Computational and Systems Biology at the University of Pittsburgh School of Medicine. His research integrates statistical physics , machine learning , and population genetics to study viral evolution and immunity, with a focus on HIV and SARS-CoV-2. His lab develops computational tools like popDMS for analyzing viral fitness landscapes and has contributed to understanding mechanisms of viral escape from immune responses and vaccine design strategies. Education: PhD in Physics from Rutgers University Research Interests: Barton’s work addresses fundamental questions about viral adaptation, clonal heterogeneity in viral reservoirs, and the interplay between chronic infections and evolutionary dynamics. He applies advanced mathematical frameworks such as Ising/Potts models and covariance factorization to decode genetic data from large-scale surveillance efforts. Key Contributions: Recent studies include modeling SARS-CoV-2 transmission via genomic data, analyzing HIV evolutionary trajectories in humans and macaques, and developing methods to infer mutation effects from deep mutational scans. His lab also explores innate immune adaptation and the design of broadly neutralizing antibody-based therapies. Awards & Recognition: No specific awards listed, though his work has been supported by NIH-funded initiatives in computational virology. Labs/Teams: Leads the Barton Lab, part of the School of Medicine’s Computational and Systems Biology program, collaborating with global networks in infectious disease research and public health.

M. Barton Lawsمشاهده پروفایل

دانشیار مدعو

• chronic disease care
• clinical practice
• health behavior
• +۵ مورد دیگر

M. Barton Laws is an Adjunct Associate Professor in the Department of Health Services, Policy and Practice at Brown University's School of Public Health. His research focuses on patient-provider communication dynamics, particularly in HIV care, and the sociological aspects of chronic illness management. He holds a PhD from Brandeis University (1997) and has extensive experience in qualitative and quantitative research methodologies. Key research areas include the Generalized Medical Interaction Analysis System (GMIAS), which evaluates clinical communication, and the Comprehensive Assessment of Clinical Encounters System (CASES). He has led/co-investigated numerous NIH-funded studies, including interventions to improve motivational interviewing skills in HIV providers and analyses of adherence-related dialogue in healthcare settings. Laws has collaborated with institutions like Johns Hopkins University and the CDC, publishing over 40 peer-reviewed articles. His work bridges communication theory and clinical practice, emphasizing patient-centered care and reducing health disparities. Teaching responsibilities include public health design and intervention evaluation courses. Current projects explore explanatory models of illness among HIV patients and the impact of near-highway pollution on cardiovascular health through community participatory research. He maintains affiliations with the Academy of Communication in Healthcare and Academy Health.

Xing Qiuمشاهده پروفایل

استاد

• Biostatistics
• Computational Biology
• Big Data Analytics
• +۵ مورد دیگر

Xing Qiu, PhD, is a Professor in the Department of Biostatistics and Computational Biology at the University of Rochester Medical Center (URMC), School of Medicine and Dentistry (SMD). He holds leadership roles in the Respiratory Pathogens Research Center (RPRC) and Center for AIDS Research (CFAR). His expertise spans biostatistics, computational biology, and big data analytics, with a focus on omics data integration and medical imaging analysis. Education: PhD in Mathematics (2004, University of Rochester), MA in Mathematics (2000, UR), ME in Civil Engineering (1996, South China University of Technology). His postdoctoral training was in Biostatistics at UR (2004–2007). Research Interests: Developing statistical methods for omics data (gene/protein expression, microbiota), medical imaging (MRI/DTI), and network analysis. Key projects include multi-omics integration pipelines, diffusion tensor imaging analysis, and HIV-related neuroimaging studies. Collaborations focus on infectious diseases (RSV, influenza, HIV) and environmental health. Awards: 9 recognized awards including the University Research Award (2022–2023), Best Mentor Award (2017), and grants supporting computational infrastructure. His work bridges statistical theory and translational research, with over 100 peer-reviewed publications. Grants & Collaborations: Active in 20+ NIH-funded projects. Serves as Core Leader for the RPRC Data Management team and Unit Leader for CFAR’s Bioinformatics core. Research teams include interdisciplinary groups in immunology, neurology, and environmental health. Labs/Teams: Leads URMC’s biostatistics computational biology unit, collaborating with clinical and basic science researchers. His lab develops open-source tools like MatchMixeR and Super-delta for omics data analysis.

Juilee Thakarمشاهده پروفایل

دانشیار

• Systems Biology
• Immunology
• Bioinformatics
• +۳ مورد دیگر

Juilee Thakar is an Associate Professor at the University of Rochester School of Medicine and Dentistry (SMD), holding joint appointments in the Department of Microbiology and Immunology and the Department of Biomedical Genetics. Her research focuses on systems biology approaches to study immune responses, integrating multi-omics data to predict outcomes of infections and vaccinations. She earned her PhD in Bioinformatics from the University of Würzburg, Germany, and has held postdoctoral positions at Yale School of Medicine and Pennsylvania State University. Dr. Thakar has received awards including the NBEM Award and PhRMA Informatics Award, and her work spans computational modeling, HIV vaccine research, and environmental exposure analysis. She leads the Thakar Lab, which develops tools like Boolean network models (BONITA) and WikiNetworks for pathway analysis.

• Mathematics Education
• Teacher Education
• STEM
• +۶ مورد دیگر

Dr Charisse Farr is a Senior Lecturer in Secondary Mathematics Education at Queensland University of Technology (QUT), based in the School of Education within the Faculty of Creative Industries, Education & Social Justice. Her research focuses on Mathematics Education, Teacher Education, and STEM, with expertise in Bayesian Networks and Applied Statistics. She holds a PhD and Bachelor of Applied Science (Mathematics) from QUT. Her work spans educational technologies, Bayesian network applications in airport wayfinding, disease modeling (e.g., HIV/AIDS, chlamydial infection), and teacher training. Key projects include developing student-centered frameworks for community engagement and exploring factors affecting PhD completion. She has received the 2014 QUT Vice Chancellor’s Performance Award for Teaching and Learning. Teaching areas include secondary mathematics pedagogy, STEM education, calculus, and statistics. She collaborates with industry and academia on complex systems research, such as airport navigation and public health interventions. Professional memberships include the Australian Teacher Education Association and the Statistical Society of Australia. Research Highlights: Combining expert opinions in Bayesian networks, HIV epidemiology modeling, and adaptive learning technologies. Teaching Contributions: Courses in education, mathematics, and STEM across undergraduate programs. Supervision: Current projects focus on digital inclusion among refugee students and TPACK integration in Maldives education systems.

Yanxun Xuمشاهده پروفایل

دانشیار

• Biostatistics
• Machine Learning
• Nonparametric Bayes
• +۴ مورد دیگر

Yanxun Xu is an Associate Professor of Applied Mathematics and Statistics at the Whiting School of Engineering , Johns Hopkins University, and an Adjunct Assistant Professor in the Division of Biostatistics and Bioinformatics at the Sidney Kimmel Comprehensive Cancer Center. She is also a member of the Data Science and Artificial Intelligence Institute . Her research focuses on developing Bayesian statistical methods and machine learning algorithms to address challenges in heterogeneous, large-scale datasets, particularly in clinical trials, electronic health records, cancer genomics, and HIV/AIDS studies. Key areas of expertise include nonparametric Bayes , reinforcement learning , and dynamic treatment regimes . Her work emphasizes precision medicine applications, such as optimizing antiretroviral therapies for HIV patients and analyzing cognitive outcomes in clinical trials. Funding sources include the National Science Foundation (NSF) , National Institutes of Health (NIH) , and industry partners like AstraZeneca. Xu has published over 80 peer-reviewed articles and received prestigious awards, including the 2016 Mitchell Prize from the International Society for Bayesian Analysis. Her research bridges statistical theory with real-world healthcare applications, addressing topics like hospital-level variations in COVID-19 treatment and the impact of inflammation biomarkers on neurocognitive functions in psychosis. PhD in Biostatistics (implied by academic rank) Recipient of JHU’s Center for AIDS Research Faculty Development Award Developed open-source software tools for causal inference and longitudinal data analysis

Kathleen Raquel Pageمشاهده پروفایل

استاد

• Infectious Diseases
• HIV/AIDS
• Migrant Health
• +۲ مورد دیگر

Kathleen Page is a Professor of Medicine at Johns Hopkins University School of Medicine with clinical expertise in infectious diseases, HIV/AIDS, and substance use disorder. She completed her undergraduate degree at Johns Hopkins, earned her MD from Washington University School of Medicine, and trained at the Hospital of the University of Pennsylvania and Johns Hopkins. She joined the faculty in 2006. Page's work focuses on improving healthcare access for underserved communities, including migrants and individuals with HIV or substance use disorders. Her research spans migrant health, mobile health interventions, health disparities, and implementation science. As principal investigator of multiple grants, she develops integrated care models and digital health tools for HIV management. She co-directs the Center for Community and Global Health in Infectious Diseases (CCGHE-ID), which promotes health equity through research, training, and service initiatives in infectious disease management locally and internationally.

• Global Mental Health
• Health-Related Stigma
• Implementation Science
• +۳ مورد دیگر

Lawrence H Yang is a Professor and Chair of the Department of Social and Behavioral Sciences at New York University (NYU). He also serves as Associate Director of the Global Center for Implementation Science and Founding Director of NYU’s Global Mental Health and Stigma Program. His work focuses on stigma reduction , global mental health , and cultural anthropology , with significant contributions to understanding stigma related to mental illness, HIV, and migration. Dr. Yang has pioneered frameworks like the ‘What Matters Most’ approach to culturally tailored interventions. He leads NIH-funded grants, including studies on untreated psychosis in China, stigma in Botswana, and implementation science for task-sharing mental health strategies globally. Education: B.A., Wesleyan University Ph.D., Boston University Clinical Fellowship, Harvard Medical School Postdoctoral Fellowship, Columbia University Mailman School of Public Health His research spans epidemiology , psychiatry , and health policy , with over 175 peer-reviewed publications in journals like JAMA , British Journal of Psychiatry , and American Journal of Public Health . He has received six national awards for stigma research, including the Maltz Prize (2021) . Dr. Yang’s grants include three NIH R01 grants on untreated psychosis, task-sharing mental health strategies, and HIV stigma interventions. He co-leads a D43 Training Grant in Vietnam and collaborates globally on stigma reduction frameworks. Recent work addresses migration stigma , culminating in a MIT Press book and JAMA publications. Awards: Maltz Prize for Schizophrenia Research (2021) NIH Implementation Science Fellowship (2019) APA Emerging Leadership Award (2012) Labs/Teams: Global Mental Health and Stigma Program; Ernst Strüngmann Forum Collaborations.

Fatma Aziza Merzoukiمشاهده پروفایل

پژوهشگر

• Data Science
• Epidemiology
• Public Health
• +۳ مورد دیگر

Dr. Fatma Aziza Merzouki is a Data Scientist and Postdoc Researcher at the University of Geneva's Faculty of Medicine, affiliated with the Institute of Global Health. She holds a PhD in Computer Science (2018) and completed her BSc (2010) and MSc (2012) in Computer Science at UNIGE. Previously, she served as a research and teaching assistant in the Scientific and Parallel Computing group (SPC), focusing on cell-based numerical models of epithelial tissues. Her current research investigates socio-behavioral drivers of HIV prevalence and incidence in Sub-Saharan Africa, leveraging data science, machine learning, and mathematical modeling. Education : BSc in Computer Science, University of Geneva (2010) MSc in Computer Science, University of Geneva (2012) PhD in Computer Science, University of Geneva (2018) Research Interests : Aziza's work combines computational methods with epidemiology to address global health challenges. Key areas include: Machine learning for HIV prediction and intervention design Mathematical modeling of infectious disease spread Data-driven analysis of socio-behavioral factors in public health Collaborative projects with biologists and biophysicists Publications : Her research spans tuberculosis treatment outcomes in Haiti, spatial HIV modeling in Malawi, and automated literature review tools using NLP. Recent work emphasizes scalable epidemiological platforms like EpiGraphHub and predictive analytics for HIV status determination. Awards : No awards explicitly mentioned in the text. Grants & Advising : No grants or formal advisees listed. However, her research involves collaborations with institutions like the WHO and field partners in Sub-Saharan Africa. Labs & Teams : Active member of the Institute of Global Health's HIV research team and previously contributed to the Scientific and Parallel Computing group's biophysical modeling efforts.

Erol Orelمشاهده پروفایل

پژوهشگر

• Machine Learning
• Data Science
• Infectious Disease Epidemiology
• +۵ مورد دیگر

Erol Orel is an econometrician and data scientist at the University of Geneva's Institute of Global Health, part of the Faculty of Medicine. He works in the Division of Infectious Diseases and Mathematical Modelling, focusing on applying machine learning and data science to global health challenges. Erol holds a Master of Science in Quantitative Economics, a D.E.A. in Econometrics, and a PhD in Biomedical Sciences (Global Health track) from the University of Geneva. Before transitioning to global health, he spent over a decade in finance as a quantitative analyst and risk manager, specializing in portfolio risk and alternative investments. He teaches statistics and epidemiology in the MAS en santé publique program at the Faculty of Medicine. His research emphasizes HIV epidemiology, including socio-behavioral risk prediction, disease surveillance, and machine learning applications. He contributed to WHO, FOPH, and HUG collaborations on pandemic modeling and developed LiteRev, an NLP-driven tool for automating literature reviews. Key projects include analyzing HIV viral suppression in Malawi, predicting antiretroviral treatment interruptions in South Africa, and assessing SARS-CoV-2 antibody prevalence in Cameroon. His work bridges econometric methods with public health, aiming to improve data-driven decision-making in global health systems.

• Virology
• Antiviral Drug Discovery
• HIV Maturation Inhibitors
• +۳ مورد دیگر

Dr. Catherine S Adamson is a Senior Lecturer in the School of Biology at the University of St Andrews, specializing in virology with a focus on antiviral drug discovery. Her research addresses critical challenges in viral diseases, including HIV maturation inhibitors and viral interferon (IFN) antagonists. Prior to her current role, she conducted postdoctoral research at the NIH, contributing to the understanding of HIV-1 maturation inhibitors like bevirimat. Her lab explores translational applications of viral IFN antagonists to develop novel antiviral drugs and improve virological techniques. Research Highlights : Development of antiviral drugs targeting HIV maturation and IFN antagonists. Investigation of Far-UVC and metal surface inactivation of pathogens like SARS-CoV-2. Collaboration with Prof. Rick Randall on high-throughput screening for viral IFN antagonist inhibitors. Awards & Recognition : NIH Federal Technology Transfer Award (2009) European Lonza Nucleofector Grant Award (2010) CytoSmart Equipment Award (2020) Grants & Funding : ISSF3 grants for antiviral research and pandemic preparedness (2018–2021). Wellcome Trust funding for lab infrastructure and collaborative projects. Labs & Teams : Her lab focuses on virology and antiviral drug development, with ongoing projects on HIV maturation inhibitors and interferon antagonist-based therapies.

Janne Estillمشاهده پروفایل

پژوهشگر

• Mathematical Modelling
• Epidemiology
• HIV Research
• +۳ مورد دیگر

Janne Estill is a Researcher at the Institute of Global Health (University of Geneva), affiliated with the Faculty of Medicine. He holds a MSc in Mathematics from the University of Helsinki (2008) and a PhD in Mathematical Modelling of HIV from the University of Bern (2013). His research focuses on developing mathematical models to evaluate disease progression and transmission, particularly for HIV, hepatitis C, and other infectious diseases, with an emphasis on cost-effectiveness analysis of health policies in resource-limited settings. Education: MSc in Mathematics, University of Helsinki, 2008 PhD in Mathematical Modelling of HIV, University of Bern (ISPM), 2013 Research Interests: Mathematical modelling, epidemiology, HIV/AIDS research, cost-effectiveness analysis, infectious disease transmission dynamics, and healthcare policy evaluation. His work applies quantitative methods to improve public health outcomes globally, particularly in sub-Saharan Africa. Publications Trends: Janne’s articles span mathematical modeling of HIV treatment strategies, cost-effectiveness of monitoring tools, and pandemic response (e.g., COVID-19). Recent work incorporates artificial intelligence for bias assessment in clinical trials, showcasing interdisciplinary innovation. Labs/Teams: Active within the Institute of Global Health, collaborating with global health networks and institutions like the Institute of Social and Preventive Medicine (ISPM), Geneva.