جست‌وجوی استاد و پژوهشگر

Eric Jutkowitzمشاهده پروفایل

دانشیار

• Aging
• cost effectiveness
• cost-effectiveness analysis
• +۱۰ مورد دیگر

Eric Jutkowitz is an Associate Professor in the Department of Health Services, Policy and Practice at Brown University. His research focuses on evaluating the value and quality of care for vulnerable populations, particularly through analyzing long-term care systems for older adults and caregivers. He specializes in cost-effectiveness studies of non-drug interventions, Medicare expenditure impacts of dementia, and predictive modeling of dementia progression. His methodologies include systematic reviews, microsimulation, and Markov models. Education: PhD in Health Services Research, Policy, and Administration from the University of Minnesota, with a focus on health decision science. Key research areas include cost-effectiveness analysis, pharmacoeconomics, longitudinal data analysis, and observational research methods. He has developed innovative tools like a dementia progression microsimulation and conducted meta-analyses to assess interventions preventing cognitive decline. Grants and advising details are not explicitly listed in the provided text. His work is affiliated with Brown University’s Health Services, Policy and Practice department, with additional research visibility through platforms like Google Scholar and ResearchGate.

Abdus S. Wahedمشاهده پروفایل

استاد

• Personalized Medicine
• Dynamic Treatment Regimes
• Statistical Methodology
• +۵ مورد دیگر

Abdus S. Wahed is a Professor of Biostatistics and Associate Chair in the Department of Biostatistics and Computational Biology at the University of Rochester. His research focuses on developing statistical methods for dynamic treatment regimes (DTRs), particularly in Sequential Multiple Assignment Randomized Trials (SMARTs), and their applications in hepatitis B, cancer, and obesity. He also works on longitudinal data analysis, survival analysis, and causal inference. Key Roles: Associate Chair, Professor of Biostatistics Affiliations: University of Rochester Medical Center His research interests include: Personalized medicine and adaptive treatment strategies Methodologies for analyzing longitudinal and time-to-event data Clinical collaborations in hepatitis B, liver diseases, and cancer treatment Recent work emphasizes statistical innovations in SMART trials, including interim monitoring and sample size adjustments. His collaborations span virology, oncology, and public health, addressing issues like hepatitis B treatment discontinuation and arsenic exposure effects. Awards: No specific awards listed in provided text. Advising & Grants: Active in mentoring graduate students and leading research grants focused on biostatistical methodologies. Collaborates with organizations like the Hepatitis B Research Network and the Longitudinal Assessment of Bariatric Surgery study. Labs/Teams: Engaged in multidisciplinary teams addressing chronic diseases and statistical trial design.

Yu Chengمشاهده پروفایل

استاد

• Dynamic Treatment Regimes
• SMART (Sequential Multiple Assignment Randomized Trials)
• Causal Inference
• +۶ مورد دیگر

Yu Cheng is a Professor and Chair of the Department of Statistics at the University of Pittsburgh, affiliated with the Dietrich School. She holds secondary appointments in Biostatistics and Psychiatry. Her research focuses on dynamic treatment regimes, SMART trials, causal inference, and multiple endpoints analysis. She leads a PCORI-funded method grant on SMART studies and co-investigates projects on cardiovascular disease and maternal/child health outcomes. Her awards include ASA Fellow (2024) and Pittsburgh Chapter Statistician of the Year (2020). Dr. Cheng earned her PhD in Statistics from the University of Wisconsin-Madison (2006), following MS (National University of Singapore, 2001) and BS (University of Science and Technology of China, 1999) degrees. She has held leadership roles including ASA LiDS Section Treasurer (2021–2023), Department Chair (2014–present), and Director of Graduate Studies (2016). Her research integrates methodological innovation with clinical collaboration, addressing topics like HIV, smoking cessation, lupus, depression, and cystic fibrosis. Her 150+ publications span journals like Biometrics , Journal of the American Statistical Association , and Biostatistics . Teaching includes courses in Survival Analysis, Probability, and Statistical Consulting. She actively mentors students through supervised consulting programs.

Benjamin C. Pierceمشاهده پروفایل

استاد

• Programming Languages
• Type Systems
• Formal Verification
• +۳ مورد دیگر

Benjamin C. Pierce is Henry Salvatori Professor of Computer and Information Science at the University of Pennsylvania, with appointments in the School of Engineering and Applied Science. A Fellow of the ACM, his research spans programming languages, formal verification, and security-privacy technologies. He directs the DeepSpec project on verified systems infrastructure and leads climate computing initiatives. Research interests focus on: Formal methods for reliable software via proof assistants like Coq Bidirectional programming and data synchronization Language-based security and differential privacy Publication trends show consistent contributions to type theory foundations, with recent emphasis on property-based testing methodologies and real-world verification. Articles frequently appear in top PL/SEC venues with practical applications in compilers and secure systems. Scientific Awards: ACM Fellow (systems verification) SIGPLAN Distinguished Educator Award (textbook innovations) Advises graduate students through the Penn PL Club. PI for NSF Expeditions in Sustainable Computing. Leads the VERSE project for verified C code and Unison file synchronizer. Directs the Penn Programming Languages Research Group collaborating with industry partners including Amazon and Microsoft Research.

• Quantum Cognition
• Cognitive Psychology
• Decision Making
• +۷ مورد دیگر

Emmanuel M. Pothos is a Professor in the Department of Psychology at City, University of London, within the School of Arts and Social Sciences. He has held prior academic positions as Senior Lecturer at City, Reader at Swansea University, and Lecturer at both the University of Edinburgh and Bangor University, reflecting a sustained and progressive academic career in cognitive psychology. PhD in Psychology, University of Oxford (1995–1998) BSc in Physics, Imperial College London (1992–1995) His research primarily focuses on quantum cognition, where he applies the mathematical formalism of quantum theory to model cognitive phenomena such as decision-making, judgment, and similarity perception. He investigates violations of classical probability in human cognition, context effects, and the role of ambiguity and conflict in choices. His interdisciplinary work draws from psychology, physics, and computational modeling. The recent trend in his publications reveals a strong emphasis on formal modeling of cognitive processes using quantum probability, with applications extending into behavioral health, financial systems, and foundational questions in decision theory. His work frequently appears in high-impact journals across psychology, physics, and interdisciplinary sciences, indicating a broad scholarly impact. While no formal awards are listed in the provided data, his extensive publication record in top-tier journals and frequent peer-review activities for leading outlets such as Nature , Psychological Review , and PNAS reflect significant academic recognition and service. Dr. Pothos actively collaborates with researchers internationally and has contributed to theoretical advances in understanding how quantum-like structures can explain human cognitive biases and complexities. Although no direct mention of student supervision is made, his role as a professor and prolific researcher implies involvement in mentoring graduate students and leading research initiatives. He has not indicated any lab or research group name, but his work clearly involves collaborative projects in cognitive modeling and decision science.

• Network Analysis
• Random Graph Theory
• High-Dimensional Statistics
• +۵ مورد دیگر

Can M. Le is an Associate Professor in the Department of Statistics at the University of California, Davis, within the College of Letters and Science. His research lies at the intersection of statistics, network science, and high-dimensional data analysis, with a focus on theoretical and applied aspects of network modeling and inference. Ph.D. in Statistics, University of Michigan, Ann Arbor His research interests include network analysis, random graph theory, community detection, high-dimensional statistical inference, and regularization of network data. He develops methods for analyzing noisy, complex network structures and has contributed significantly to spectral methods and low-rank approximations in network science. His work bridges theoretical statistics with practical applications in social and biological networks. The recent publications demonstrate a strong trend in modeling and inference for network-linked data, with emphasis on robustness, adaptivity, and concentration properties of random graphs. His work combines deep probabilistic analysis with statistical methodology, particularly in community detection and network estimation under noise and heterogeneity. His research is supported by the National Science Foundation (NSF) grant DMS-2015134, indicating active funding and ongoing contributions to the field. While no formal list of advisees is provided, his collaborative work with leading statisticians such as Elizaveta Levina and Roman Vershynin suggests an active research group and mentoring role. He has no listed scientific awards in the provided text. However, his consistent publication record in top journals (JASA, JRSSB, Annals of Statistics, JMLR) underscores his scholarly impact. Dr. Le's work is closely tied to theoretical and applied statistical research on networks, likely involving a research lab or team focused on network data science, though specific lab names or team structures are not mentioned in the text.

Davide La Vecchiaمشاهده پروفایل

استاد

• Time series analysis
• Robust and semiparametric inference
• Financial econometrics
• +۳ مورد دیگر

Davide La Vecchia is a Full Professor at the Research Institute for Statistics and Information Science (RISIS) at the University of Geneva, Switzerland. He holds dual PhDs in Statistics from Bocconi University (2007) and Economics from Università della Svizzera italiana (2011). His academic journey includes roles as an Assistant Professor at the University of St. Gallen and Monash University, and he has held visiting positions at Princeton University, the University of Copenhagen, and CREST (Paris). His expertise spans time series analysis, robust and semiparametric inference, financial econometrics, and spatial statistics. Key research contributions include work on saddlepoint approximations, optimal transportation methods, and latent variable models. Davide has led multiple grants, including from the Swiss National Science Foundation and the Australian Research Council. He serves as a referee for top-tier journals in statistics and econometrics. Teaching focuses on advanced statistical methods, including probability theory, time series analysis, and multivariate inference. His recent work emphasizes high-dimensional data modeling, spatio-temporal factor models, and applications to commodities trading networks. He has been honored with editorial roles and speaker invitations at global conferences, reflecting his leadership in statistical methodology.

Sami Bensassiمشاهده پروفایل

دانشیار

• International Trade
• Development Economics
• Informal Trade
• +۷ مورد دیگر

Dr. Sami Bensassi is a Reader in Managerial Economics at the University of Birmingham, affiliated with the Birmingham Business School and the Department of Management. He serves as Head of the Business, Economics and Policy Group and is a member of the Centre for Crime, Justice and Policing. He has been at the university since January 2013 and holds a PhD in Economics from the University of Paris-Nanterre. BA in Economics, Université Toulouse I MA in Development Economics and International Trade, Université Panthéon Sorbonne (Paris I) PhD in Economics, Université Paris X Nanterre His research lies at the intersection of trade, development, and institutions, with a strong focus on informal trade, smuggling, corruption, and conflict zones. He also investigates return migration and trade-related fraud. His work combines empirical analysis with policy relevance, often drawing on data from Africa and the Middle East. His recent publications span topics such as informal trade measurement, trade policy effectiveness, climate impacts on historical trade, and public health interventions in developing countries. These reflect a consistent interdisciplinary and policy-oriented approach, often in collaboration with international organizations. He has received the University of Birmingham's Outstanding International Impact Award for his research on smuggling at Tunisian borders. Research funding from FCDO, European Union, Economic Research Forum, IFPRI Collaborations with World Bank, Food and Agriculture Organisation (FAO) Supervision of PhD and Master’s students (specific names not listed) He is actively involved in research dissemination through his personal website, Google Scholar, and other academic platforms.

Cesar Ruizمشاهده پروفایل

استادیار

• Metal Additive Manufacturing
• Process-Informed Machine Learning
• Quality Control
• +۳ مورد دیگر

Cesar Ruiz is an Assistant Professor in the Department of Industrial & Systems Engineering at The University of Oklahoma. His research focuses on integrating domain knowledge with machine learning and stochastic modeling for engineering applications, particularly in metal additive manufacturing, predictive maintenance, and quality control. He holds a Ph.D. and M.S. in Industrial Engineering from the University of Arkansas and a B.A. in Business Engineering from the Higher School of Economics and Business in El Salvador. His research domains include metal additive manufacturing processes, process-informed machine learning frameworks, and reliability evaluation in complex systems. Notable works address challenges in layer segmentation for quality assessment, predictive maintenance strategies, and degradation-based reliability analysis. Ruiz has received prestigious awards such as the RAMS Golomski Award (2020, 2022), ASQ Best Reliability Paper (2021), and IEEE CASE Best Conference Paper (2021). His affiliations include SRE, INFORMS, and ASME. His research spans aerospace and defense systems, with recent publications emphasizing advanced manufacturing techniques, functional data analysis, and Bayesian modeling for reliability growth. He collaborates on projects involving biosensor optimization and large-scale system maintenance frameworks.

Karen Shenمشاهده پروفایل

استادیار

• Health Economics
• Healthcare Labor Markets
• Long-Term Care
• +۷ مورد دیگر

Karen Shen is an Assistant Professor in the Department of Health Policy and Management at the Johns Hopkins Bloomberg School of Public Health. She is affiliated with the Roger and Flo Lipitz Center to Advance Policy in Aging and Disability, the Hopkins Economics of Alzheimer’s Disease & Services Center, and the Hopkins Business of Health Initiative. Her research focuses on healthcare labor markets and financing policies affecting aging populations and individuals with mental health and substance use disorders. PhD in Economics, Harvard University, 2021 MS in Statistics, Stanford University, 2013 BS in Mathematical and Computational Sciences, Stanford University, 2013 Dr. Shen's research lies at the intersection of health economics and public policy. Her work investigates how labor market dynamics, staffing policies, and public financing mechanisms impact care delivery and outcomes, particularly in long-term care and mental health settings. She employs rigorous econometric methods to analyze large-scale datasets and inform evidence-based policy. Her recent publications span topics such as healthcare worker shortages, Medicaid financing of home care, nursing home staffing and quality, opioid use disorder treatment access, and the impact of the pandemic on healthcare employment. The articles reflect a strong trend toward policy-relevant empirical research using quasi-experimental designs and administrative data to evaluate real-world interventions. Alleviating Worker Shortages Through Targeted Subsidies: Evidence from Incentive Payments in Healthcare (2024) Who benefits from public financing of home-based long term care? Evidence from Medicaid (2024) Health Care Staff Turnover and Quality of Care at Nursing Homes (2023) Do Policies to Increase Access to Treatment for Opioid Use Disorder Work? (2023) Job Flows Into and Out of Health Care Before and After the COVID-19 Pandemic (2024) Dr. Shen has not received any explicitly mentioned scientific awards in the provided texts. She advises students in health economics and policy, though specific advisees are not listed. She has been involved in research grants related to aging, Alzheimer’s disease, and healthcare policy through her center affiliations. Her work has been widely disseminated, with publications in top journals and attention from news outlets and social media. She is part of collaborative research networks focusing on aging, mental health, and healthcare systems.

Elizabeth Chinمشاهده پروفایل

استادیار

• Causal Inference
• Algorithmic Fairness
• Machine Learning
• +۱۲ مورد دیگر

Elizabeth Chin is an Assistant Professor in the Department of Biostatistics at the Bloomberg School of Public Health, Johns Hopkins University. Her work bridges biostatistics, causal inference, and public health, with a strong focus on equity and ethical decision-making systems. PhD in Biomedical Data Science, Stanford University (2022) BS in Applied Mathematics, UCLA (2017) Her research interests include causal inference, algorithmic fairness, machine learning, and their application to public health challenges such as health inequities, environmental justice, and policy evaluation. She develops statistical methodologies to improve the robustness and fairness of data-driven decisions, particularly in vulnerable populations including incarcerated individuals. Elizabeth Chin's recent publications span high-impact areas such as mental health care disparities, forensic statistics, environmental lead exposure, and pandemic response. Her work often appears in top journals like Nature Machine Intelligence , NEJM , JAMA Pediatrics , and PNAS . A key trend across her articles is the use of advanced statistical methods to address structural injustices and inform equitable policy. National Science Foundation Graduate Fellowship Stanford Graduate Fellowship She has advised and collaborated with leading researchers in biostatistics and public health. Her work has received significant media attention and has been referenced in policy discussions, indicating real-world impact. Elizabeth Chin is actively contributing to national conversations on data ethics, health equity, and scientific rigor in public health.

Eyal Lubetzkyمشاهده پروفایل

استاد

• Probability Theory
• Combinatorics
• Statistical Mechanics
• +۳ مورد دیگر

Eyal Lubetzky is a Professor of Mathematics at the Courant Institute of Mathematical Sciences, New York University. His research focuses on probability theory and combinatorics, with notable contributions to the study of Ising models, cutoff phenomena, and random graphs. He holds a Ph.D. in Mathematics from Tel-Aviv University (2007) and a B.Sc. in Mathematics and Computer Science from the same institution (2002). Education: Ph.D., Mathematics, Tel-Aviv University, Israel, 2007 B.Sc., Mathematics and Computer Science, Tel-Aviv University, Israel, 2002 His research interests span probability theory, combinatorics, and statistical mechanics, with a focus on phase transitions, stochastic processes, and the analysis of complex systems. Notable works include groundbreaking studies on the cutoff phenomenon in Ising models and the mixing times of Markov chains. He has authored numerous influential papers, including studies on the dynamics of SOS surfaces, critical wetting phenomena, and the mixing properties of spin systems. His work has been recognized in volumes like What's Happening in the Mathematical Sciences . Lubetzky serves as an Associate Editor for journals such as Probability and Mathematical Physics , Probability Theory and Related Fields , and Annals of Applied Probability . He has organized workshops on topics like Markov chain mixing times and probabilistic combinatorics.

Genevieve Dingleمشاهده پروفایل

استاد

• Mental Health Interventions
• Social Prescribing
• Music Therapy
• +۷ مورد دیگر

Professor Genevieve Dingle is a Professor in Clinical Psychology at the University of Queensland's School of Psychology within the Faculty of Health, Medicine and Behavioural Sciences. She also serves as an affiliate Professor at Nottingham Trent University (UK). Her academic leadership includes course convenor roles for PSYC7291 Cognitive Behaviour Therapies for Adults and PSYC3102 Psychopathology. Dingle holds significant professional roles as Associate Editor of Psychology of Music journal, Culture and the Arts on Prescription lead for the Australian Social Prescribing Institute for Research and Education (ASPIRE), and committee member of the Arts Health Network QLD (AHNQ). Professor Dingle's research centers on social (non-medical) interventions for mental health, with particular expertise in music, arts, and nature-based programs. Her work explores how these interventions can address loneliness, improve emotion regulation, and enhance wellbeing through social identity processes. She has developed notable interventions including the 'Tuned In' music emotion regulation program and 'Groups for Belonging' for loneliness reduction. Her research spans multiple populations including university students, people experiencing homelessness, and those in addiction treatment. Analysis of her recent publications (2023-2025) reveals a strong focus on social prescribing, music-based interventions, and university student mental health. Her work demonstrates consistent application of social identity theory to understand how group membership and community engagement contribute to mental wellbeing. Key themes include the therapeutic potential of choir singing, the development of evidence-based protocols for social prescribing, and the impact of the pandemic on student mental health. Professor Dingle leads several significant research projects including a $1.29M NHMRC-funded cluster randomized controlled trial of 'Groups for Belonging,' a $480K UQ-funded 'Sharper Minds' mental health prevention package for university students, and an Australian Research Council linkage grant evaluating social prescribing for loneliness. Her collaborative work involves interdisciplinary teams across multiple institutions and sectors. Her laboratory work focuses on the School of Psychology at UQ, with particular emphasis on the development and evaluation of group-based interventions. She maintains strong connections with community organizations through her roles with ASPIRE and AHNQ, ensuring her research has practical applications in real-world settings.

Cassandra Tellegenمشاهده پروفایل

مدرس

• Developmental disabilities
• Autism Spectrum Disorder
• Parenting programs
• +۵ مورد دیگر

Dr. Cassandra Tellegen is a Teaching Associate at the School of Psychology within the Faculty of Health, Medicine and Behavioural Sciences at the University of Queensland. She serves as Curriculum Development Leader at the Parenting and Family Support Centre (PFSC), where she is responsible for updating and creating Triple P training materials. As a clinical psychologist and board-approved clinical supervisor who completed her PhD in Clinical Psychology in 2013 at UQ, she has established herself as a significant contributor to the field of developmental psychology and evidence-based parenting interventions. Dr. Tellegen earned both her Bachelor (Honours) and Doctor of Philosophy degrees from the University of Queensland. Her doctoral research focused on parenting children with developmental disabilities, specifically evaluating the Stepping Stones Triple P-Positive Parenting Program for children with autism spectrum disorders. Her primary research interests center on developmental disabilities with a special emphasis on Autism Spectrum Disorder. Dr. Tellegen's work extensively explores behavioral family interventions, particularly the Triple P (Positive Parenting Program) system. She investigates parenting self-efficacy, implementation science of evidence-based parenting programs, and compassion-based interventions. Her research often employs meta-analytic approaches and examines how parenting programs can be effectively implemented across various contexts including educational settings and with diverse populations. A notable aspect of her work is the development and validation of measurement tools for assessing parental adjustment and self-regulation. Analysis of Dr. Tellegen's publication record reveals a strong trajectory focused on implementation science of parenting interventions, particularly examining factors that facilitate or hinder successful adoption of evidence-based programs in real-world settings. Her recent work has increasingly focused on parenting self-efficacy, home-school partnerships, and compassion-based interventions. Methodologically, she frequently employs meta-analysis, randomized controlled trials, and structural equation modeling to understand complex relationships in family systems and implementation contexts. Dr. Tellegen actively supervises doctoral students at the University of Queensland, serving as Principal Advisor for research on parent mental health symptoms and family adjustment outcomes, and as Associate Advisor for studies examining parental self-regulation in home-school partnerships. She has secured research funding, including a past grant from the Edmund Rice Overseas Aid Fund for a randomized controlled trial of a parenting program for Kenyan parents living in poverty. Her work bridges academic research with practical application through her role at the Parenting and Family Support Centre. As Curriculum Development Leader at the PFSC, Dr. Tellegen works closely with the Parenting and Family Support Centre team, contributing to the development and refinement of evidence-based parenting interventions. Her work bridges academic research with practical application, ensuring that parenting programs are both scientifically rigorous and accessible to practitioners and families. She regularly presents her findings at national and international conferences, including the Australian Association for Research in Education and the Helping Families Change Conference.

Koenraad Schalmمشاهده پروفایل

استاد

• String Theory
• Theoretical Physics
• Holographic Duality (AdS/CFT)
• +۷ مورد دیگر

Koenraad Schalm is a Professor of Theoretical Physics at Leiden University, affiliated with the Leiden Institute of Physics (LION) within the Faculty of Science. He leads the Schalm Group, which focuses on string theory and its applications in condensed matter and cosmology through holographic duality (AdS/CFT). His research interests include string theory, quantum critical systems, holographic models of superconductivity, black hole physics, and early universe cosmology. He explores how string-theoretic models can explain experimental observations in quantum materials and primordial fluctuations. The recent publications highlight a strong focus on applying holography to condensed matter phenomena, including strange metals, superconductivity, and non-equilibrium transport. There is also significant work on cosmological perturbations and inflation, showing interdisciplinary reach between high-energy theory and observational cosmology. Vici Innovation Research Incentives Award, NWO (2013) Vidi Innovation Research Incentives Award, NWO (2004) FOM Program group grant 'Observing the big bang: the quantum universe and its imprint on the sky' (2014) NWO Graduate Program Award 'de Sitter Program in Cosmology' (2011) FOM Project grant with J. Zaanen (2009) FOM Program group grant 'A String Theoretic Approach to Cosmology and Quantum Matter' (2009) NWO van Gogh Grant with P.S. Corasaniti (2007) FOM Project grant with E. Verlinde and J.P. van der Schaar (2007) Schalm has advised numerous PhD students and collaborators, including Aravindh Swaminathan, Shankar Aleksandar Bukva, Ludwig Hoffmann, and Petter Säterskog. He has been principal investigator on multiple NWO and FOM grants. He co-organized workshops such as 'Black Hole Answers for Condensed Matter Questions' and 'Effective Field Theory in Inflation', and is actively involved in academic service. He leads the Schalm Group, which investigates the interface between string theory and experiment, particularly through the AdS/CMT correspondence. The group aims to uncover quantum signatures of string theory in condensed matter systems and cosmological data.