جست‌وجوی استاد و پژوهشگر

• Diabetes Management
• e-Health Technologies
• Health Services and Systems
• +۳ مورد دیگر

Dr. Diana Sherifali is an Associate Professor at McMaster University's School of Nursing and Joint Faculty in Health Research Methods, Evidence and Impact . She serves as a Clinical Nurse Specialist in the Diabetes Care and Research Program at Hamilton Health Sciences and an Associate Researcher at the Population Health Research Institute. Her scholarship focuses on designing, implementing, and evaluating diabetes self-management strategies across patient, provider, and population levels, with particular emphasis on e-health technologies , health services research , and integrated care models . Co-Lead, McMaster Evidence Review and Synthesis Team Co-Director, Health Coach Institute at York University As Deputy Editor of the Canadian Journal of Diabetes , she shapes knowledge dissemination in diabetes care. Her research has produced over 200 publications in the last decade, including clinical practice guidelines and innovative programs like the ADAPT-M trial for postpartum diabetes prevention. She has contributed extensively to technology-enabled care models, systematic reviews on diabetes remission, and health equity studies for immigrant populations. Dr. Sherifali's academic work spans diabetes technology implementation, cardiovascular comorbidity management, and mental health integration in diabetes care, with recent studies examining Reddit-based qualitative analysis of patient experiences during the COVID-19 pandemic. She has also developed co-designed interventions for elderly diabetes patients with frailty and multimorbidity, and leads national efforts in diabetes health coaching standardization.

Daniel Huttenlocherمشاهده پروفایل

استاد

• Artificial Intelligence + Machine Learning
• AI and Society
• Graphics and Vision
• +۳ مورد دیگر

Daniel Huttenlocher is the Dean of the MIT Stephen A. Schwarzman College of Computing and holds the Henry Ellis Warren (1894) Professorship in Computer Science and Artificial Intelligence + Decision-making (AI+D). He leads the interdisciplinary College of Computing while maintaining academic ties to the Electrical Engineering & Computer Science Department. His research focuses on AI ethics, societal impact of technology, machine learning applications, and vision systems. Key research areas include AI governance frameworks, adaptive public health strategies, and large-scale computer vision algorithms. He has pioneered work on decentralized collaboration systems, social media dynamics, and generative AI's societal implications. Huttenlocher’s recent publications address challenges in epidemic testing optimization and the evolving role of AI in knowledge ecosystems like Wikipedia. His leadership roles include steering MIT’s computing initiatives and fostering industry partnerships, such as the MIT Generative AI Impact Consortium. Despite no explicitly listed awards, his contributions to AI ethics and technical systems reflect significant academic influence. Advising and grant activities remain unspecified in available records. His work bridges technical innovation with societal challenges, emphasizing the ethical deployment of AI across healthcare, education, and digital economies.

Paul Gustafsonمشاهده پروفایل

استاد

• Biostatistics
• Epidemiology
• Bayesian Analysis
• +۳ مورد دیگر

Paul Gustafson is a Professor and Head of the Department of Statistics at the University of British Columbia's Faculty of Science. He holds a faculty position at the Vancouver Campus and can be contacted via gustaf@stat.ubc.ca. His research focuses on advanced statistical methodologies with applications in epidemiology, public health, and clinical research. Key interests include Bayesian analysis, causal inference, measurement error correction, and meta-analysis. Dr. Gustafson's work emphasizes methodological innovations in handling complex data challenges such as exposure misclassification, missing data, and observational study biases. He collaborates on projects addressing opioid use disorder treatment efficacy, infectious disease epidemiology, and health policy. Current advisees include Nathaniel Wu Dyrkton, Daniel Daly Grafstein, Seren Lee, Yuan Xia, and Mallory J Flynn. His research outputs span statistical theory, applied public health studies, and computational methods. Recent work highlights include Bayesian approaches to sample size determination, probabilistic bias analysis in diagnostic studies, and frameworks for evaluating treatment benefit predictors using observational data. Dr. Gustafson is also involved in global initiatives such as the Zika Virus Individual Participant Data Consortium. Notable methodological contributions include developing techniques for partially identified models, correcting measurement errors in health surveys, and advancing causal inference methodologies. He has contributed to R packages like rtestim for epidemic modeling and CRTpowerdist for cluster randomized trial analysis.

Yi Fengمشاهده پروفایل

استادیار

• Structural Equation Modeling
• Latent Growth Models
• Random Variability Modeling
• +۵ مورد دیگر

Yi Feng is an Assistant Professor in Quantitative Psychology at the University of California, Los Angeles (UCLA). With expertise in advanced statistical methodologies, Feng contributes to both theoretical and applied research in psychology and education, focusing on structural equation modeling (SEM), latent growth models, and causal graphical frameworks. They teach graduate-level SEM courses (Psych M257) and undergraduate statistics (Psych 100A). Research Focus: Causal inference, variability modeling, and power analysis with interdisciplinary applications in education, developmental psychology, and healthcare. Key Collaborations: Regularly works with researchers like Gregory R. Hancock and Jeffrey R. Harring on methodological innovations. Feng’s methodological work appears in high-impact journals such as Psychological Methods (Impact Factor: 14.738) and JAMA Internal Medicine (Impact Factor: 44.41). Their applied research spans topics like socioeconomic disparities in science achievement, cognitive trajectories post-surgery, and mental health service delivery. Feng also explores synthetic data applications for longitudinal educational research.

John M. Colford Jr.مشاهده پروفایل

استاد

• Waterborne Infectious Diseases
• Clinical Trial Design
• Epidemiology
• +۳ مورد دیگر

John M. Colford Jr. is a Professor of Epidemiology at the University of California, Berkeley's School of Public Health. He holds an MD from Johns Hopkins University, an MPH and PhD from UC Berkeley, and completed medical training at Stanford and UCSF. His research focuses on waterborne infectious diseases and clinical trial design, with a global emphasis on improving water, sanitation, and hygiene (WASH) interventions in low-resource settings. He has led randomized trials in countries like Bangladesh, Kenya, and India, evaluating the impact of WASH on child health outcomes. Dr. Colford teaches courses on epidemiologic methods and randomized controlled trials at UC Berkeley and serves as an attending physician in Infectious Diseases at the UCSF/VA Medical Center. His work spans environmental health, global health equity, and the integration of machine learning into public health research. Major themes in his publications include climate change impacts on disease transmission, the role of WASH in reducing antibiotic use, and addressing social determinants of child growth and development. His scientific contributions include pioneering studies on household sanitation effectiveness and the long-term health implications of early childhood growth faltering. Dr. Colford's trials often involve interdisciplinary collaborations, combining epidemiology, environmental engineering, and behavioral science to address systemic health challenges in marginalized populations.

• Developmental Psychopathology
• Child Mental Health
• Early Life Stress
• +۵ مورد دیگر

Lucy Bowes is a Professor of Developmental Psychopathology and Fellow of Magdalen College at the University of Oxford. Her research focuses on the impact of early life stress, bullying, and maltreatment on children's mental health, integrating methods from social epidemiology, developmental psychology, and behavioral genetics. She leads the Risk & Resilience research group, examining resilience-promoting factors to inform interventions. Key affiliations include the Department of Psychiatry (University of Oxford) and Magdalen College. Her work emphasizes translational research, with a strong focus on school-based anti-bullying programs (e.g., KiVa) and parenting interventions (e.g., Incredible Years). Recent studies explore dimensions of childhood adversity, bullying trajectories, and the long-term mental health impacts of victimization. She collaborates internationally, including projects in Indonesia and Lebanon focusing on refugee populations and low-resource settings. Research themes include: Genetic and environmental influences on resilience Socioeconomic determinants of mental health Adverse childhood experiences (ACEs) classification Cyberbullying and digital health literacy Post-pandemic mental health trends in youth Her publications emphasize intervention efficacy, cost-effectiveness analyses, and policy-relevant findings. Collaborative projects include large-scale randomized controlled trials and mixed-methods studies with marginalized populations.

• Cardiovascular Physiology
• Exercise Physiology
• Chronic Disease Prevention
• +۳ مورد دیگر

Winthrop Professor Daniel Green is a leading academic in cardiovascular exercise physiology at the University of Western Australia (UWA), based in the School of Human Sciences. He holds a PhD from UWA and has been a NHMRC Principal Research Fellow (2015-2021). His work focuses on preventing chronic diseases like atherosclerosis, diabetes, and heart failure through exercise interventions, with a focus on translational research and technological innovations such as optical computed tomography for vascular assessment. Prof Green has supervised over 90 thesis students and leads the Cardiovascular Research Group at UWA, collaborating internationally with institutions like Mayo Clinic and the University of Oregon. He has secured $14.9 million in competitive grants and pioneered initiatives like the International Summer School for Ultrasound in Cardiovascular Science and Medicine. His awards include the Vice-Chancellor’s Senior Research Award (2022). Research interests include exercise training effects on vascular health, imaging techniques for disease assessment, and personalized interventions for chronic disease prevention. His lab develops tools to detect early-stage chronic diseases and optimize lifestyle interventions.

Jeremy Dawsonمشاهده پروفایل

استاد

• Health Management
• Organizational Behavior
• Healthcare Outcomes
• +۵ مورد دیگر

Jeremy Dawson is a Professor of Health Management at the University of Sheffield, jointly affiliated with the Institute of Work Psychology (within the Management School) and the School of Health and Related Research (ScHARR). He holds a PhD from Aston University (2011). His research focuses on NHS staff experience, team dynamics, healthcare outcomes, and statistical methodology. Key areas include staff retention, equality/diversity in healthcare, and the impact of organizational practices on patient outcomes. He advises the NHS on staff surveys and diversity initiatives, including roles in the NHS Staff Survey Advisory Group and the NHS Race and Health Observatory. He has led major projects such as the Retention of Mental Health Staff (RoMHS) study and the Multiple Symptoms Study 3 (MSS3), evaluating interventions for persistent physical symptoms. His statistical contributions include methodological work on interaction effects and team behavior analysis. Teaching responsibilities include advanced statistics modules for health science researchers and workshops on research methods. He supervises PhD students in areas like leadership wellbeing, healthcare staff wellbeing, and NHS board diversity. Publications span over 70 peer-reviewed articles in journals like Journal of Applied Psychology and Health Services and Delivery Research . He serves on editorial boards, including Organizational Research Methods . His work bridges organizational behavior and healthcare, emphasizing practical applications of statistical rigor.

Daniel Ierodiaconouمشاهده پروفایل

استاد

• Marine Ecology
• Environmental Management
• Geology
• +۶ مورد دیگر

Professor Daniel Ierodiaconou is a marine ecologist at Deakin University, where he serves as Professor in Marine Science and leads the Deakin Marine Mapping Group. He acts as Victorian Node Leader for the Integrated Marine Observing System (IMOS), Board Director for the Great Ocean Road Coast and Parks Authority, and Coastal Lead Scientist for the CoastRI Initiative. His work combines multi-disciplinary approaches to advance marine ecosystem-based management. Doctor of Philosophy, Deakin University Bachelor of Science (Aquatic Science), Deakin University Bachelor of Science (Fisheries Management & Aquaculture), Deakin University Daniel's research focuses on Benthic Habitat Mapping , Marine Protected Areas , and Coastal Process Monitoring . His work integrates Remote Sensing , Image Classification , and Change Detection techniques to inform marine conservation and climate adaptation strategies. Recent publications highlight advancements in Seafloor Habitat Classification , Coastal Erosion Modeling , and Seagrass Restoration . Scientific awards include: 2020 Eureka Prize for Innovation in Citizen Science 2020 Victorian Coastal Award for Innovative Applied Research 2018 Victorian Coastal Award for Partnership Research 2009 Tall Poppy Award Daniel supervises 10 current doctoral students and has advised 16 PhD completions. His grants portfolio exceeds $7 million, including a $5 million NCRIS-funded CoastRI Coastal Monitoring Network. He specializes in integrating Geospatial Technologies with Marine Conservation through his leadership in citizen science drone programs and Victoria's first wave buoy network.

Elmar Teuflمشاهده پروفایل

مدرس ارشد

• Random Walks on Graphs
• Combinatorics
• Probability Theory
• +۳ مورد دیگر

Elmar Teufl is a Senior Lecturer in the Department of Mathematics at Eberhard Karls Universität Tübingen. He holds a Doctorate (2002) and a Habilitation (2015) from Graz University of Technology and Tübingen University, respectively. His research focuses on random walks on graphs and groups, combinatorial problems on self-similar structures, asymptotic methods, and fractal geometry. His work bridges probability theory, combinatorics, and graph theory with applications to fractal networks and recursive systems. Teufl has held academic positions across Europe, including visiting professorships at the University of Stuttgart (2012–2013) and a Marie Curie Fellowship at Bielefeld University (2005–2006). His research has been supported by the Austrian Science Fund (FWF) and the EU. Key achievements include contributions to spanning tree enumeration on Sierpinski graphs and resistance scaling in self-similar lattices. His publications span topics like asymptotic enumeration, determinant identities for Laplacian matrices, and structural properties of nilpotent groups. He received the Austrian Mathematical Society's Studienpreis (2003) for his thesis on self-similar graphs and fractals. Teaching responsibilities include advanced courses in combinatorics and probability, with a full teaching record documented in alma.

David Luitzمشاهده پروفایل

استاد

• Quantum Many-Body Systems
• Condensed Matter Physics
• Theoretical Physics
• +۳ مورد دیگر

David Luitz is a Professor of Theoretical Physics at Bonn University, specializing in quantum many-body systems. His research focuses on fundamental aspects of quantum dynamics, including many-body localization, quantum information spreading, and non-equilibrium thermodynamics. He develops advanced numerical methods and software tools such as the DanceQ library to tackle complex many-body problems. His work bridges theoretical physics with computational techniques, addressing topics like entanglement entropy, out-of-time-order correlators, and phase transitions in interacting quantum systems. Key research areas include the interplay between disorder and thermalization, quantum chaos, and the application of quantum Monte Carlo methods to study correlated electron systems. His contributions have advanced understanding of eigenstate thermalization, dissipative dynamics, and topological phenomena in condensed matter systems. Dr. Luitz’s publications highlight innovations in numerical algorithms for many-body systems and experimental predictions for quantum phase transitions. His work often explores the boundaries between localized and thermalizing regimes, with applications to both theoretical and computational physics.

Bryan Wardمشاهده پروفایل

استادیار

• Real-Time Systems
• Embedded Systems Security
• Cyber-Physical Systems
• +۳ مورد دیگر

Bryan Ward is an Assistant Professor of Computer Science and Electrical and Computer Engineering at Vanderbilt University's School of Engineering. His research focuses on enhancing the security and resilience of real-time and embedded systems in critical domains such as industrial control systems and space systems. Ward holds a Ph.D. in Computer Science from the University of North Carolina at Chapel Hill, along with dual bachelor's degrees in Computer Science and Engineering and Mathematics from Bucknell University. His academic contributions span multiple areas including operating system security, real-time scheduling, and hardware-software co-design for safety-critical systems. Key research themes include control-flow integrity, secure resource management in multi-core environments, and mitigating timing-based attacks in real-time embedded systems. Ward's work has explored advanced defense mechanisms like dynamic address space randomization, tagged architecture implementations, and retry-free transactional memory models. He has also investigated vulnerabilities in kernel scheduling and cache-sharing behaviors in multi-core platforms, proposing novel solutions to ensure predictability and security. Current projects emphasize securing cyber-physical systems through adaptive defenses that maintain strict timing guarantees required for safety-critical applications.

Xiaofeng Zhuمشاهده پروفایل

استاد

• Genetic Epidemiology
• Statistical Genetics
• Genetic Association Analysis
• +۵ مورد دیگر

Xiaofeng Zhu, PhD is a Professor in the Department of Population and Quantitative Health Sciences at Case Western Reserve University School of Medicine. He also serves as faculty at the Cleveland Institute for Computational Biology. His research focuses on developing statistical methods and computational tools for analyzing genetic and genomic data, particularly in the context of association analysis, admixture mapping, and rare variant identification. He leads the Continental Origins and Genetic Epidemiology Network (COGENT) consortium and has identified multiple genetic loci associated with blood pressure, sleep disorders, and Alzheimer's disease. Education: Ph.D. in Biostatistics, Epidemiology and Biostatistics, Case Western Reserve University (1998) M.S. in Statistics, University of Cincinnati (1994) M.S. and B.Sc. in Mathematics, Peking University (1989, 1986) Research Interests: Dr. Zhu's work emphasizes statistical genetics, including the development of methods to control population stratification, admixture mapping in admixed populations, and cross-phenotype association analyses. His lab integrates deep learning and bioinformatics to study complex traits such as cardiovascular disease, obesity, and sleep disorders. Recent efforts include analyzing whole-genome sequencing data to uncover rare variants influencing phenotypic variation. Publications Trends: His recent work spans Mendelian randomization methods (e.g., MRBEE), gene-sleep interaction studies, and multi-ancestry genomic analyses. Key themes include causal inference, pleiotropy analysis, and leveraging diverse genetic datasets to improve polygenic risk scores. Awards & Memberships: Fellow of the Royal Statistical Society Member, American Society of Human Genetics Member, International Genetic Epidemiology Society Advising & Grants: He has mentored 3 Master’s students, 9/10 PhD graduates, and 11/12 postdoctoral researchers. Notable mentees hold positions at Harvard, Mayo Clinic, and NIH. Active grants include studies on sleep health metrics, lipid loci discovery, and cardiovascular disease genetics. Labs & Teams: Leads COGENT consortium and collaborates with the NHLBI Trans-Omics for Precision Medicine (TOPMed) program. His lab develops software tools for ancestry inference, rare variant analysis, and epigenetic association studies.

Karun Adusumilliمشاهده پروفایل

استادیار

• Econometrics
• Causal Inference
• Missing Data
• +۶ مورد دیگر

Karun Adusumilli is an Assistant Professor of Economics at the University of Pennsylvania, affiliated with the Department of Economics within the School of Arts and Sciences. He holds a PhD from the London School of Economics (2018), an MSc in Econometrics and Mathematical Economics (2013), and a B.Tech in Engineering Physics from the Indian Institute of Technology, Delhi (2011). His research focuses on advanced econometric methodologies, including causal inference, missing data analysis, dynamic treatment allocation, and reinforcement learning applications in economics. Education: PhD in Economics, LSE (2018) MSc Econometrics and Mathematical Economics, LSE (2013) B.Tech in Engineering Physics, IIT Delhi (2011) Adusumilli’s research interests span Econometrics , Causal Inference , Dynamic Treatment Regimes , and Statistical Learning . He has pioneered work on optimal policy design in bandit experiments, minimax allocation strategies, and addressing unobserved heterogeneity in econometric models. His contributions bridge theoretical econometrics with practical applications in healthcare, education policy, and sequential decision-making frameworks. He has received notable awards, including the Kravis Award for Teaching Excellence (2021) and the John Hicks Prize for his doctoral research (2019). His publications appear in top-tier journals like Econometrica and Review of Economic Studies . Adusumilli teaches graduate and undergraduate courses in econometrics and statistical learning, including Econometrics I and Econometric Machine Learning . He has served on scientific committees for major conferences such as the NBER-NSF Time Series Conference and the AEA-ASSA Annual Meetings .

Livia A. Carvalhoمشاهده پروفایل

مدرس ارشد

• Neuropsychopharmacology
• Psychoneuroimmunology
• Precision Medicine
• +۷ مورد دیگر

Dr. Livia A. Carvalho is a Senior Lecturer in Neuropsychopharmacology at Queen Mary University of London's Faculty of Medicine and Dentistry, within the Clinical Pharmacology and Precision Medicine department at the William Harvey Research Institute. She holds an honorary Senior Lecturer position at the University of Malaga's Department of Psychobiology and is a Fellow of both the Institute of Clinical Research and the Higher Education Academy. Education: BSc in Pharmacology and Biochemistry from University of São Paulo, Brazil MSc in Neurosciences from University of São Paulo PhD in Pharmacology from University of São Paulo Postdoctoral training at King's College London (with Prof. Carmine Pariante) and University College London (with Prof. Andrew Steptoe) Research Interests: Her work focuses on immunophenotyping depression to improve disease stratification and identify novel drug targets. This involves laboratory-based experiments, clinical trials, and epidemiological studies. Key themes include inflammation-driven mental health pathways, precision medicine for mental illnesses, and translational approaches linking molecular and clinical data. Teaching & Mentoring: Dr. Carvalho leads the 'Brain Behaviour and Immunity' module and co-leads 'Clinical Pharmacology and Drug Safety Assessment'. She advises MBBS and Biomedical Sciences students and has mentored over 20 researchers, many of whom have achieved academic or industry success. Notable trainees include Daisy Fancourt (UCL) and Ann Liljn (University Hospital of Northern Sweden). Awards & Recognition: Young Investigator Awards from NARSAD, ECNP, and the British Association for Psychopharmacology American Psychosomatic Society Award Fellowships in Clinical Research and Higher Education Collaborations & Funding: Her collaborations include Prof. Magdi Yaqoob and Prof. Helen Warren (internal) and Prof. Glyn Lewis (external). Sponsors include Barts Charity. She reviews for journals like Brain, Behavior, and Immunity and evaluates grants for the Medical Research Council and National Institute of Health Research. Labs & Teams: Active in the Psychobiology Group at UCL and the Clinical Pharmacology team at Queen Mary. Her research group includes members like Luis de Souza Teodoro and Christopher Clesse.