جست‌وجوی استاد و پژوهشگر

Mathias Géryمشاهده پروفایل

مدرس

• Structured Information Retrieval
• Social Information Retrieval
• Multimedia Information Retrieval
• +۱ مورد دیگر

Mathias Géry is a Lecturer in Computer Science at Jean Monnet University, affiliated with the Computer Science Department within the Faculty of Science and Technology. He conducts research as a member of the Data Intelligence Group at the H. Curien Laboratory (UMR CNRS 5516) in Saint-Étienne, France. Research Focus: His work centers on advanced Information Retrieval systems, with four core pillars: Structured IR (specializing in textual IR, XML, hypertexts, and structured documents), Social IR (analyzing social networks and relationships), Multimedia IR (developing text-image fusion models and representation frameworks), and Web Mining (including usage analysis, corpus collection, and web analytics). His methodologies consistently integrate user profiles and social context to enhance personalized information access. Publication Trends: Recent publications (2015-2024) reveal a strong trajectory in personalized and social IR, with significant contributions to query expansion, language modeling, and social bookmarking systems. His interdisciplinary reach extends to health informatics (2024 RCT on sedentary adults), sports science (2023 gender-based endurance analysis), quantum physics (2021 turbulence study), and literary analysis (2019 Russian literature), demonstrating exceptional versatility across computational and humanities domains. Collaborative Environment: As an active researcher within the CNRS-affiliated H. Curien Laboratory, he contributes to the Data Intelligence Group's mission of advancing data-driven methodologies through structured, social, and multimodal approaches.

Keith S. Goldfeldمشاهده پروفایل

دانشیار

• Biostatistics
• Data Analysis
• Public Health
• +۸ مورد دیگر

Keith S. Goldfeld is an Associate Professor at the Department of Population Health, Grossman School of Medicine, New York University. His research focuses on biostatistics, data analysis, public health, and palliative care, with a strong emphasis on improving outcomes for older adults with serious illnesses. DrPH, Columbia University Research Highlights: Keith’s work spans emergency medicine, geriatrics, and chronic disease management, leveraging advanced statistical methods to evaluate healthcare interventions, including integrated kidney palliative care and emergency department-based palliative care trials. His recent studies address acute care usage, loneliness in serious illnesses, and telehealth training efficacy. Selected Publications: His 2025 work includes analyses of prognosis in older cancer patients, stepped wedge trial models, and innovative approaches to opioid overdose prevention training. These studies reflect his commitment to applying biostatistics to real-world healthcare challenges.

• Stochastic Analysis
• Mathematical Finance
• Financial Mathematics
• +۴ مورد دیگر

Dörte Kreher is an Assistant Professor (Junior Professor) for Applied Stochastic Analysis at the Institute of Mathematics, Humboldt University of Berlin, within the Faculty of Mathematics and Natural Sciences. She has held this position since August 2017 and maintains an active research program in stochastic analysis and mathematical finance, with significant contributions to energy market modeling and market microstructure theory. Her educational background includes: Dr. sc. nat. in Mathematics (University of Zurich, 2014) Diplom in Mathematics (Humboldt University of Berlin, 2009) B.Sc. in Economics (Humboldt University of Berlin, 2009) Professor Kreher's research centers on stochastic modeling of financial and energy markets, with expertise in limit order book dynamics, rough volatility, and stochastic partial differential equations. Her work bridges theoretical stochastic analysis with practical applications in electricity markets and high-frequency trading, developing novel diffusion approximations and second-order models that capture complex market behaviors. She investigates phenomena such as asset price bubbles, non-negative martingale solutions, and cross-border transmission constraints in energy systems. Her recent publications reveal a strong trajectory in applying advanced stochastic methods to real-world market problems, with increasing focus on electricity market modeling and rough volatility foundations. The research demonstrates sophisticated mathematical techniques applied to intraday price dynamics, market microstructure, and optimal control for energy storage systems, reflecting both theoretical depth and practical relevance. She actively supervises PhD students and secures competitive research funding through multiple collaborative projects: MATH+ Project AA4-4: Stochastic modeling of intraday electricity markets (with Markus Reiß) MATH+ Project AA4-9: Volatile Electricity Markets and Battery Storage (with Christian Bayer and Manuel Landstorfer) Berlin-Oxford IRTG 2544: Stochastic Analysis in Interaction SFB/TRR 388 Project B02: Microstructural Foundations of Rough Volatility Models (with Christian Bayer and Ulrich Horst) As a core member of the Applied Stochastic Analysis group, she contributes to Berlin's vibrant quantitative finance ecosystem through teaching, workshop organization (including multiple Junior Female Researchers in Probability workshops), and collaboration with the Berlin Mathematical School and MATH+ cluster.

Lyndsay O'Haraمشاهده پروفایل

دانشیار

• Hospital epidemiology and infection control
• Epidemiologic methods in infectious diseases
• Transmission of multidrug-resistant organisms
• +۳ مورد دیگر

Lyndsay O'Hara is an Associate Professor in the Department of Epidemiology & Public Health at the University of Maryland School of Medicine. Her research focuses on hospital epidemiology, infection control, and epidemiologic methods in infectious diseases, with particular attention to multidrug-resistant organisms and healthcare worker safety. Education: B.Sc. in Cell Biology and Anatomy from University of Western Ontario (2006) M.P.H. in Global Health from University of British Columbia (2011) Certificate in Infection Prevention and Control from UBC Department of Pathology and Laboratory Medicine (2012) Ph.D. in Population and Public Health (Epidemiology) from University of British Columbia (2016) Postdoctoral Fellowship in Infectious Disease Epidemiology at University of Maryland School of Medicine (2018) Her research spans transmission dynamics of multidrug-resistant pathogens , emerging infectious diseases , and health systems interventions to improve infection control. Publications highlight environmental contamination, contact precautions, and healthcare-associated infection mitigation. Recent articles examine Acinetobacter baumannii and Candida auris prevalence in ICU settings, disinfectant efficacy, and comorbidities influencing COVID-19 readmissions . Methodologically, she explores standardization techniques for infection reporting and cluster-randomized trial designs. Scientific Recognition: Canadian Institutes for Health Research Banting Postdoctoral Fellowship Recipient She contributes to global health through tuberculosis risk assessments in South African healthcare facilities and evaluates correlations between infection control and hospital quality metrics.

Emma Radovichمشاهده پروفایل

پژوهشگر ارشد

• Evaluation
• Maternal health
• Quality improvement
• +۸ مورد دیگر

Emma Radovich is a Research Fellow in the Department of Health Services Research and Policy within the Faculty of Public Health and Policy at the London School of Hygiene & Tropical Medicine (LSHTM). She has been at LSHTM since 2014-15, initially joining to complete her MSc in Demography & Health, and has progressed through roles from Research Assistant to her current position as Research Fellow. Her educational background includes a PhD in Epidemiology and Population Health from LSHTM (completed in 2024), an MSc in Demography & Health from LSHTM (2014-2015), and a BA in History of Art from the University of California, Berkeley (2004-2008). As a mixed-methods researcher, Dr. Radovich specializes in evaluations of complex interventions, with particular expertise in realist evaluation approaches to examine healthcare service design and quality improvement interventions. Her research primarily focuses on maternal health services, especially in Southern Asia, with significant work in Nepal, India, Nigeria, Egypt, and the United Kingdom. She has led studies on measuring and improving care coverage and quality in maternal health services, including an exploratory study in Nepal on maternity service hygiene infrastructure and facility design funded by the LSHTM Health and Hygiene Seed Grant 2023. Her recent publications demonstrate a strong focus on electronic decision support systems to improve antenatal care quality in South Asia, with multiple studies examining implementation, impact on workflow, and effects on care quality. She has also conducted significant work using Demographic and Health Surveys to analyze maternal healthcare utilization and quality across multiple countries. LSHTM Health and Hygiene Seed Grant 2023 for "Hygiene preparedness of maternity services: lessons from routine screening tests in Nepal" 2019-20 Doctoral Project Travelling Scholarship for "Impact of an Electronic Decision Support System on workflow in antenatal care" MRC-funded research on "A cluster randomized trial of an mHealth integrated model of hypertension diabltes & antenatal care in primary care settings in India & Nepal" Dr. Radovich is actively involved in teaching and supervision at LSHTM. She is co-module organiser for PHM219 Evaluation of Public Health Interventions (distance learning) and supervises MSc summer projects for both intensive and distance learning students. Previously, she has taught on Health Systems, Basic Epidemiology, Statistics for Epidemiology and Population Health, and Analysing Survey and Population Data courses. She has also coached PhD and MSc students on DHS data analysis at the Institute of Tropical Medicine in Antwerp. She is a member of the Maternal and Newborn Health Group (MNHG) and the Centre for Evaluation at LSHTM, and is currently part of the NIHR Policy Innovation and Evaluation Policy Research Unit (PIRU), where she evaluates UK public health interventions and the implementation of health and social care services.

• Public Health
• Population Health
• Chronic disease prevention
• +۷ مورد دیگر

Professor John Wiggers is a Professorial Fellow at the School of Medicine and Public Health at the University of Newcastle, Australia. He also serves as Director of Hunter New England (HNE) Population Health, leading a team of over 100 staff serving 800,000 people across the region from Newcastle to the Queensland border. His work uniquely bridges research, policy, and practice in population health. Education: PhD in Behavioural Medicine, University of Newcastle (1997) Graduate Diploma in Health Social Science, University of Newcastle Bachelor of Arts (Honours), University of Newcastle Professor Wiggers focuses on population health research, particularly in re-orientating health and other agencies towards policies and practices that prevent chronic diseases and reduce health risks. His expertise spans chronic disease prevention, injury prevention, and harm reduction related to alcohol and tobacco. He has developed evidence-based models for implementing health promotion programs across multiple community settings including schools, childcare centers, sports clubs, and police stations. His research emphasizes a 'system' and 'capacity building' approach, working collaboratively with community organizations to ensure research is both informed by and translated into practice. His recent publications (2021-2023) demonstrate a strong focus on implementation science, particularly in translating evidence into practice across various settings. Key themes include antenatal care addressing alcohol consumption, obesity prevention in schools and childcare settings, mental health promotion, and improving preventive care for people with mental illness. His work frequently employs cluster randomized controlled trials and implementation frameworks to evaluate the effectiveness of practice change interventions. Scientific Awards: 2015 Excellence Award by the Collaboration of Community-based Obesity Prevention Sites for the Good for Kids Good for Life program Professor Wiggers has secured significant research funding, including NHMRC grants, to support his work on alcohol harm reduction, obesity prevention, and tobacco control. His research has directly informed policy and practice, with programs like Good for Kids Good for Life being adopted by NSW Health as the Healthy Children Initiative. He has established strong collaborations across health services, community organizations, and government bodies to build capacity for evidence-based practice. As Director of Hunter New England Population Health, Professor Wiggers oversees a substantial team implementing population health services across the region. His work with the NSW Police Force on alcohol-related crime reduction has served as a model adopted by police forces in New Zealand and South Australia. His 'virtuous cycle' approach emphasizes co-design, implementation, evaluation, and dissemination of evidence-based practices with service providers.

Jasmina Pivarمشاهده پروفایل

استادیار

• Business Informatics
• Big Data
• Machine Learning
• +۵ مورد دیگر

Jasmina Pivar is an Assistant Professor in the Department of Informatics at the Faculty of Economics - Zagreb (University of Zagreb). Her research focuses on business informatics, big data, machine learning, and smart cities, with applications in fraud detection, human resource management, and urban planning. Research Interests: She explores intersections of technology and economics, including patent analysis of emerging technologies, cluster-based financial strategies, and digital literacy trends. Her work addresses challenges in smart city development, churn management, and data-driven policy for the EU video game industry. Publications Trends: Over the past decade, her articles highlight big data adoption frameworks, fraud profiling techniques, and generational shifts in digital behavior. She frequently employs machine learning and cluster analysis for predictive modeling. Contact: Reach her at jpivar@efzg.hr or Room A507, Faculty of Economics - Zagreb.

• Neurosurgery
• Spine Surgery
• Brain Tumors
• +۳ مورد دیگر

Sasha Gulati is a Professor at the Norwegian University of Science and Technology and a Consultant Neurosurgeon at St. Olavs Hospital, specializing in Neurosurgery within the Department of Neuromedicine and Movement Science. Their work bridges clinical practice with extensive research in spinal and brain disorders. Research interests span spinal pathologies (degenerative cervical/lumbar diseases, radiculopathy, recurrent disc herniation), brain tumors (gliomas, meningiomas), cerebrovascular conditions (aneurysms, subarachnoid hemorrhage), and functional outcomes post-neurosurgery. Key themes include occupational rehabilitation , registry-based comparative studies , and pharmacoepidemiology in postoperative care. Recent publications (2020-2025) focus on spinal cord stimulation for chronic pain, shunt surgery complications , return-to-work outcomes after neurosurgical interventions, and demographic risk factors in aneurysm and glioma management. Collaborative work spans Scandinavia, utilizing national registries for large-scale clinical insights.

Peggy Cenac-Guesdonمشاهده پروفایل

مدرس

• Statistics
• Probability
• Random Walks
• +۳ مورد دیگر

Peggy Cenac-Guesdon is a Lecturer-Researcher at the University of Burgundy, affiliated with the Institute of Mathematics of Burgundy (IMB) and the UFR Sciences and Technology. Her research focuses on probability theory, stochastic processes, and their applications to biological sequence analysis. Education: PhD in Applied Mathematics (2006, Université Paul Sabatier Toulouse III), HDR (Habilitation à Diriger des Recherches). Research Interests: Cenac's work spans variable-length Markov chains, persistent random walks, and stochastic algorithms for analyzing multidimensional data. She applies these methods to biological sequences via Chaos Game Representation (CGR), enabling novel pattern detection and taxonomic classification. Her theoretical contributions include central limit theorems for martingales and optimization techniques for risk indicators. Key Publications: Recent papers address multidimensional persistent random walks, variable-length memory chains, and stochastic algorithms for geometric medians in Hilbert spaces. These works intersect probability theory, dynamical systems, and computational biology. Projects: She developed the MyCGR library in Objective-Caml for DNA sequence analysis using CGR, linking algorithmic design with statistical modeling. Her collaborations span mathematics, computer science, and actuarial risk modeling.

Matthew Bourkeمشاهده پروفایل

پژوهشگر ارشد

• Applied and developmental psychology
• Child and adolescent development
• Health Sciences
• +۳ مورد دیگر

Dr. Matthew Bourke is a Research Fellow at the School of Human Movement and Nutrition Sciences at the University of Queensland , associated with the Centre for Community Health and Wellbeing . His work focuses on contemporary techniques like Ecological Momentary Assessment and compositional data analysis to study 24-hour movement behaviors in children and youth, emphasizing their impact on developmental outcomes. Education: Bachelor of Sport and Recreation, Monash University Bachelor of Business, Monash University Bachelor (Honours) of Applied Science (Human Movement Studies), Victoria University Doctor of Philosophy (Human Movement), Victoria University Matthew’s research spans Applied and Developmental Psychology , Child and Adolescent Development , Sport and Exercise Psychology , and Health Sciences . He investigates how combinations of physical activity, sedentary behavior, and sleep affect children’s health and mental wellbeing, with a focus on interventions targeting multiple levels of influence . Recent publications analyze 24-hour movement behaviors in children, including meta-analyses of sedentary time , physical activity , and sleep associations with adiposity , mental health , and developmental outcomes . He employs compositional data analysis , ecological momentary assessment , and cluster randomized trials to evaluate interventions such as TEACH e-Learning courses for educators. Matthew collaborates with researchers like Professor John Cairney and Dr. Patricia Tucker on projects including the 360-Kids Community Network program , aligning with national strategies for children’s mental health and wellbeing. He is available for supervision in areas like physical activity and movement behavior research .

Junwen Chenمشاهده پروفایل

دانشیار

• Anxiety Disorders
• Social Anxiety Disorder
• Transdiagnostic Processes
• +۶ مورد دیگر

Associate Professor Junwen Chen is a prominent researcher in the School of Medicine and Psychology at the Australian National University, where she serves as International Programs Coordinator. She also holds an Adjunct Senior Lecturer position at the University of Adelaide (2019-2027). With over two decades of academic experience across Japan and Australia, her career trajectory shows steady progression from Research Associate at Waseda University to her current leadership role at ANU. Dr. Chen's research program centers on anxiety disorders, with particular emphasis on Social Anxiety Disorder and transdiagnostic processes across anxiety and depression. Her work investigates three interconnected domains: (1) the cognitive mechanisms maintaining social anxiety through biased information processing; (2) development and evaluation of intervention programs targeting excessive worry using behavioral and emotion regulation approaches; and (3) cross-cultural manifestations of social anxiety. Her methodological approach combines experimental, clinical, and longitudinal designs with increasing incorporation of neuroscientific methods in recent work. Analysis of her recent publications (2023-2025) reveals a sophisticated research program expanding into school-based interventions, cross-cultural applications, and transdiagnostic approaches to anxiety disorders. Her work increasingly examines social identity factors, cognitive biases, and emotion regulation as both mechanisms and treatment targets. Notably, she has strengthened interdisciplinary collaborations, particularly with educational researchers and cross-cultural psychologists, while maintaining her core focus on social anxiety. Dr. Chen actively supervises research students and leads significant grant-funded projects including the development of mobile health interventions for perinatal mental health and the CHIME Australia project exploring social singing for perinatal mental health. Her research demonstrates consistent productivity with over 50 publications and an h-index of 18, reflecting substantial impact in clinical psychology and mental health research. Her laboratory work focuses on cognitive processes in anxiety, with particular expertise in interpretation bias, emotion regulation strategies, and cross-cultural manifestations of social anxiety. Recent projects indicate expansion into school-based interventions and digital mental health solutions, suggesting evolving research directions that maintain her core expertise while addressing contemporary mental health challenges.

Martin Wahlمشاهده پروفایل

استاد

• Mathematical Statistics
• High-Dimensional Statistics
• Probability Theory
• +۲ مورد دیگر

Martin Wahl is a Professor (W2) in the Faculty of Mathematics at Bielefeld University, appointed in 2023. He obtained his doctorate from Heidelberg University in 2015, followed by postdoctoral research at Humboldt University of Berlin (2015-2022) and a Feodor Lynen Research Fellowship at Georgia Tech. His research centers on mathematical statistics with emphasis on: High-dimensional statistics and probability theory Statistical learning theory and dimension reduction techniques Nonparametric estimation and minimax optimality Spectral methods for covariance operators and random matrices His recent articles (2020-2025) demonstrate strong focus on spectral methods, perturbation analysis, and error bounds in high-dimensional settings, with applications spanning manifold learning, PCA optimization, and stochastic PDEs. Theoretical developments in minimax estimation and concentration inequalities form consistent themes. Awards: Feodor Lynen Research Fellowship (Georgia Tech) He leads the project "Convexity and Grassmann Manifolds in Statistical Inference" (2027) under the Priority Program "Combinatorial Synergies". He is affiliated with the Bielefeld Graduate School in Theoretical Sciences and the Center for Statistics.

Tina Costacouمشاهده پروفایل

دانشیار

• Epidemiology
• Diabetes Research
• Cardiovascular Disease
• +۵ مورد دیگر

Tina Costacou serves as Associate Professor and Director of the Doctoral Degree Program in the Department of Epidemiology at the University of Pittsburgh School of Public Health. Her research investigates dietary influences on disease, oxidative stress mechanisms, and genetic determinants of diabetic complications, with particular focus on type 1 diabetes cardiovascular and renal outcomes. Her academic credentials include: BA in Business Administration from University of Massachusetts, Amherst (1993) MSc in Epidemiology and Biostatistics from University of Massachusetts, Amherst (1996) PhD in Epidemiology from University of South Carolina, Columbia (2001) Post-doctorate in Diabetes Epidemiology from University of Pittsburgh (2004) Dr. Costacou's research program spans three interconnected domains: dietary epidemiology (notably Mediterranean diet patterns and mortality relationships through EPIC study methodology development), oxidative stress pathophysiology in vascular disease, and haptoglobin genotype effects on diabetic complications. Her groundbreaking work has demonstrated the universality of kidney disease in long-duration type 1 diabetes and challenged assumptions about sex-based risk differences. Analysis of her 2013-2018 publications reveals consistent investigation into haptoglobin-mediated mechanisms, including kidney iron deposition, HDL dysfunction, and vitamin E intervention potential. These studies predominantly employ longitudinal cohort designs with genetic epidemiology approaches, frequently utilizing biomarker measurements and advanced statistical modeling to unravel gene-environment interactions in diabetic complications.

• Global Health
• Health Transitions
• Public Health Nutrition
• +۷ مورد دیگر

Associate Professor Matthew Kelly is a prominent researcher at the National Centre for Epidemiology and Population Health (NCEPH) within The Australian National University. With over 15 years of research experience focused on the Asia-Pacific region, particularly Southeast Asia, he leads the Master of Public Health program at ANU and maintains close collaborations with universities and ministries of health in Indonesia, Thailand, Laos, and Cambodia. Department of Applied Epidemiology Building 62, Room 2.08 ORCID: 0000-0001-7963-2139 Dr. Kelly's research spans critical health challenges in the Asia-Pacific region, with special emphasis on Southeast Asia. His work addresses changing nutrition burdens, health information system strengthening (particularly for mortality surveillance), water, sanitation and hygiene (WASH) and related health burdens, and non-communicable disease and infection interactions, with a specific focus on tuberculosis-diabetes mellitus co-morbidity. His research methodology combines epidemiological approaches with spatial analysis and health systems strengthening. Analysis of his recent publications reveals a strong focus on tropical diseases, multimorbidity patterns, and health system interventions across Southeast Asia. His work increasingly incorporates spatial modeling techniques and addresses the intersection of infectious and non-communicable diseases, particularly in resource-limited settings. The research demonstrates a clear trajectory toward addressing complex health challenges through integrated, multi-sectoral approaches. Dr. Kelly actively supervises numerous graduate students and leads multiple research projects focusing on health resilience in Indonesia, mortality surveillance in Pacific nations, and combating health misinformation. His collaborative approach is evident in the extensive international partnerships reflected in his publications. His current research portfolio includes projects on environmental enteric dysfunction in Central Java, mortality surveillance models in Solomon Islands and Timor Leste, climate-resilient primary healthcare in Indonesia, and innovative approaches to health education in the Lower Mekong Basin.

Ulrich Meyerمشاهده پروفایل

استاد

• Algorithm Engineering
• Big Data
• High Performance Computing
• +۵ مورد دیگر

Prof. Dr. Ulrich Meyer is a full Professor of Computer Science at Goethe University Frankfurt, where he joined as a full professor in 2007 at the age of 35. He is also a Fellow at the Frankfurt Institute for Advanced Studies (FIAS) since 2020 and serves as the spokesperson for the DFG priority program "Algorithms for Big Data" (SPP 1736), which spans over 15 sites across Germany, Austria, and Switzerland. Professor Meyer received his Ph.D. in computer science from Saarland University in 2002. Following his doctorate, he worked as a postdoc and later as a senior researcher (W2) at the Max-Planck Institute for Computer Science in Saarbrücken before joining Goethe University Frankfurt. His research focuses on the design and engineering of algorithms and data structures for very large data sets, with particular emphasis on parallelism (Shared-Memory, clusters, GPUs), memory hierarchies (caches, SSDs, hard disks), and energy efficiency. His work spans the spectrum from theoretical worst-case results and average-case analyses to experimental evaluation of heuristics. A significant portion of his research involves graph algorithms, where his group has achieved more than a thousand-fold speed-up over state-of-the-art methods through algorithms with better access patterns. His recent work has focused on memory-efficient graph exploration in dynamically changing data, approximate solutions, and efficient generation of randomized graph test data. Professor Meyer has received numerous prestigious awards including the 2019 ESA Test of Time Award for the Delta-Stepping Algorithm, Best Paper Awards at ESA 2019 for research on Fragile Computing and Graph Generation, the 2011 Award Germany Land of Ideas for Ecosort, records in the JouleSort Competition in 2009/10, and the 2003 Best Dissertation Award from the University of Saarland. As spokesperson for the DFG priority program SPP 1736 "Algorithms for Big Data," Professor Meyer coordinates research across multiple institutions. His Algorithm Engineering group is also part of the DFG Research Unit FOR 2971 "Algorithms, Dynamics, and Information Flow in Networks" and the LOEWE Priority Programme CMMS. His research has been supported by various grants that have enabled significant contributions to parallel and external-memory graph algorithms, large-scale network generation, and energy-efficient computing. Professor Meyer's research group forms part of the Computer Sciences and AI Systems division at FIAS. They collaborate extensively with researchers across Europe through the DFG priority program and other initiatives. The group is particularly known for their work on memory-efficient graph algorithms, large-scale network generation, and contributions to understanding the algorithmic foundations of big data processing.