جست‌وجوی استاد و پژوهشگر

Pei Fen Kuanمشاهده پروفایل

استاد

• Statistical Genomics
• Computational Biology
• Bioinformatics
• +۳ مورد دیگر

Pei Fen Kuan is a Professor in the Department of Applied Mathematics and Statistics at Stony Brook University. She holds a Ph.D. in Statistical Genomics from the University of Wisconsin-Madison. Her research focuses on developing statistical methodologies for analyzing high-throughput omics data, particularly in genome biology and psychiatric/cancer-related studies. She leads projects on ChIP-Seq, RNA-Seq, and DNA methylation analysis, with significant contributions to the WTC Wellness Program studying trauma-related disorders. Education: Ph.D. in Statistics (2009), University of Wisconsin-Madison; B.S. (details not specified). Research interests include computational biology, epigenetics, and integrative omics, with a focus on PTSD, cognitive aging, and melanoma genetics. She has developed R packages like methylGSA and RNAAgeCalc for bioinformatics analysis. Current grants include NIH/NIA and CDC/NIOSH funding for PTSD and aging studies. Lab involvement: Directs the WTC Wellness Program research team, focusing on gene-environment interactions in responders' health. Collaborates internationally via the InterMEL consortium for melanoma studies. Teaching: Courses in computational statistics and statistical genomics (details inferred from departmental role).

Sulekha Anandمشاهده پروفایل

استاد

• Biostatistics
• Neuroscience
• Human Physiology
• +۴ مورد دیگر

Sulekha Anand is a Professor in the Department of Biological Sciences at San José State University (SJSU) and a member of research teams at NASA-Ames Research Center. She earned her Ph.D. in Neuroscience from the University of California, Santa Cruz (1994) and B.S. in Biology from Santa Clara University (1990). At SJSU, she teaches courses in Experimental Design and Biostatistics , Scientific Communication , Human Physiology , and Statistical Methods in Clinical Trials . Education: Ph.D., University of California, Santa Cruz (1994) B.S., Santa Clara University (1990) Her research spans neuroscience , biostatistics , and space biology , focusing on visual-motor physiology, cognitive assessment, and spaceflight-induced physiological changes. Recent publications analyze opioid protocol adherence in hospitals, cognitive decline screening tools, and immune responses under simulated deep space conditions. She also investigates educational strategies in STEM, including active learning and peer-led team learning. Key collaborations include NASA's Life Sciences Division for spaceflight research and studies on hotel sustainability applications. Her methodological expertise includes transcranial magnetic stimulation (TMS) experiments, statistical modeling, and MemTrax cognitive assessment development.

David M. Quinnمشاهده پروفایل

دانشیار

• Educational inequality by race and class
• Teachers’ racial attitudes and biases
• Achievement gap discourse effects
• +۲ مورد دیگر

David M. Quinn is the Rodney S. Wallace Associate Professor for the Advancement of Teaching and Learning in the Department of Organizational Leadership, Policy, and Development at the University of Minnesota. His research focuses on measuring, explaining, and ending educational inequality by race, ethnicity, and class, with particular interests in students' seasonal learning patterns, teachers' racial attitudes, and the effects of issue frames related to educational equity. Education: Ed.D. in Education Policy, Leadership, and Instructional Practice, Harvard Graduate School of Education Ed.M. in Education Policy and Management, Harvard Graduate School of Education M.Ed. in Curriculum and Instruction, University of Nevada-Las Vegas B.S. in Film and Television, Boston University Research Interests: Quinn's work centers on educational inequality, specifically examining how race and class disparities manifest in academic achievement. His research investigates the impact of "achievement gap" versus "opportunity gap" discourse, teachers' implicit and explicit racial biases, and seasonal learning dynamics. He employs experimental and large-scale quantitative methods to inform policies aimed at promoting equity in education. Publication Trends: Quinn's recent publications (2016-2025) consistently address racial and socioeconomic disparities in education. Key themes include the effects of framing on public and teacher attitudes, the measurement of bias among educators, and the decomposition of achievement gaps. His work appears in top-tier journals such as Educational Researcher and Sociology of Education , reflecting interdisciplinary engagement with education policy, social psychology, and statistics. Scientific Awards: No scientific awards are listed in the provided information. Advising and Grants: The provided text does not specify current advisees or grant funding.

Jared Fletcherمشاهده پروفایل

دانشیار

• Exercise Physiology
• Biomechanics
• Muscle-Tendon Interaction
• +۳ مورد دیگر

Jared Fletcher, PhD, is an Associate Professor at Mount Royal University (MRU), currently on sabbatical from July 2024 to July 2025. He holds a PhD in Applied Muscle Physiology from the University of Calgary, an MSc from the same institution, and a Bachelor of Exercise and Sport Science (BESS) from the University of Manitoba. His teaching focuses on Biomechanics, Exercise Physiology, and Statistics. Dr. Fletcher’s research integrates physiology and biomechanics to study muscle-tendon interactions, exercise-related fatigue across the lifespan, and the application of exercise in clinical and elite athletic contexts. His work has explored topics such as the role of Achilles tendon stiffness in running economy, the effects of footwear design on running biomechanics, and the physiological adaptations to concentrated training periods. Before joining MRU, he served as a Sport Physiologist for the Canadian National Para-swimming team, supporting Paralympic athletes at major competitions. His postdoctoral research at MRU involved assessing novel methods for evaluating exercise fatigue in elite athletes and leading hospital-based health initiatives. His publications emphasize biomechanical and physiological insights, with a focus on translating findings into practical applications for improving athletic performance and clinical rehabilitation. He contributes to research through institutions like the Institute for Community Prosperity and the Institute for Innovation and Entrepreneurship at MRU.

• Geotechnical Engineering
• Computational Mechanics
• Soil Mechanics
• +۴ مورد دیگر

James Doherty is an Associate Professor in the Department of Civil, Environmental and Mining Engineering at The University of Western Australia (UWA), affiliated with the UWA Oceans Institute. His work focuses on geotechnical engineering and cloud computing technologies, emphasizing automation of data interpretation and optimization of engineering design workflows. He leads research in numerical methods, soil-structure interaction, and offshore wind infrastructure, with over 80 peer-reviewed publications. Doherty founded the open-access geocalcs.com platform, serving 1,000+ users globally with engineering design tools derived from his research. He has developed cloud-based platforms for companies like Fugro, achieving significant computational efficiency gains. His expertise aligns with UN Sustainable Development Goals related to infrastructure and sustainable energy.

Britton Sauerbreiمشاهده پروفایل

استادیار

• Motor Control
• Neural Circuits
• Neurodegenerative Diseases
• +۳ مورد دیگر

Britton Sauerbrei is an Assistant Professor in the Department of Neurosciences at Case Western Reserve University's School of Medicine. Their research focuses on understanding the neural circuits governing skilled motor control, particularly how distributed neural networks enable adaptive movement and how these dynamics are disrupted in neurodegenerative diseases. They employ high-density electrophysiological recordings, optogenetic manipulation, and computational modeling to study neural ensemble activity during natural behaviors. Education: Bachelor of Arts in Mathematics, University of Chicago (2009) PhD in Computation and Neural Systems, California Institute of Technology (2015) Research Interests: The lab investigates principles underlying neural activity flow in motor control circuits, with emphasis on cerebellar-cortical interactions and disease-related alterations. Techniques include Neuropixels recording probes, optogenetics, and computational methods like adaptive functional PCA. Key Findings: Recent work demonstrates the cerebellum's role in discontinuous movement control and reveals input-driven cortical dynamics during dexterous tasks. Innovations include the development of high-density neural probes ( Neuropixels 2.0 ) and novel motor unit recording devices. Lab & Collaborations: The Sauerbrei Lab actively explores neurodegenerative disease models and sensorimotor integration mechanisms. Collaborative projects focus on translating findings to understand movement disorders and developing computational tools for neural data analysis.

Bethany A. Bellمشاهده پروفایل

دانشیار

• Health Equity
• Statistical Methods
• Nutrition-related Inequities
• +۳ مورد دیگر

Bethany A. Bell is an Associate Professor in the Department of Education Leadership, Foundations & Policy at the University of Virginia’s School of Education and Human Development. Her work focuses on advancing health and education equity through complex statistical methodologies and addressing social determinants of health, particularly among marginalized populations. She is affiliated with the Youth-Nex Center and contributes to programs like the Research, Statistics & Evaluation Ph.D. and Quantitative Analytics in Education M.Ed. Education : Ph.D., University of South Florida (2008) M.P.H., University of Oklahoma Health Sciences Center (2002) B.A., Mary Washington College (1997) Research Interests : Dr. Bell combines Monte Carlo simulations, SAS macro development, and mixed-methods approaches to study nutrition inequities, race-based health disparities, and education policy. Her recent work develops survey tools to measure racial experiences and their embodiment, aiming to clarify mechanisms linking race to health outcomes. Publications Trends : Her articles span health disparities, food systems, and autism spectrum disorder interventions, emphasizing quantitative rigor and real-world policy applications. Recent work explores racial discrimination trajectories and food security dynamics in African American communities. Awards : AERA Division D Early Career Award (Quantitative Methods) NIH Loan Repayment Program Award (Health Disparities Research) Labs/Initiatives : She contributes to the Race and Public Education in the South project and co-authored Multilevel Modeling Methods , a seminal text in quantitative research.

Michail Papathomasمشاهده پروفایل

مدرس ارشد

• Bayesian Statistics
• Biostatistics
• Ecological Statistics
• +۷ مورد دیگر

Dr Michail Papathomas is a Senior Lecturer in Statistics at the School of Mathematics and Statistics, University of St Andrews. He is affiliated with the Centre for Research into Ecological & Environmental Modelling. His research focuses on Bayesian statistical methodology, mixture modeling, and applications in ecology, public health, and genomics. He has supervised PhD students including Chao Gao, Thu Nguyen, and Hanyu Wang. His work bridges theoretical developments with practical applications in areas like spatial capture-recapture techniques and antibiotic resistance epidemiology. Recent projects include analysis of multidrug-resistant infections in East Africa and chemical evolution studies of galaxies. Education: PhD in Statistics (inferred from academic role) Research interests span Bayesian nonparametrics, Dirichlet process mixtures, and statistical methods for ecological and biomedical data. He collaborates internationally on projects addressing global health challenges and environmental monitoring. His publications often integrate advanced computational methods with real-world datasets. Key research trends include: (1) Developing flexible statistical frameworks for complex ecological systems; (2) Addressing parameter identifiability in log-linear models; (3) Applying mixture models to genomic and epidemiological datasets. Grants: Received funding for a cancer research studentship from The Melville Trust, and Scottish Funding Council support for blockchain applications in irrigation governance. Led development of spatial capture-recapture methodologies and contributed to tools for galaxy spectral analysis. Active in interdisciplinary collaborations across medicine, ecology, and astrophysics.

Hao Wuمشاهده پروفایل

مدرس ارشد

• Commercial Property Markets
• Urban Economics
• Valuation and Price Theory
• +۷ مورد دیگر

Dr. Hao Wu is a Senior Lecturer in Property at the University of Melbourne's Melbourne School of Design. He holds dual affiliations with Ormond College (Senior Common Room member) and has served on professional committees for organizations like the Royal Institution of Chartered Surveyors (RICS) and the Australian Property Institute (API). His academic journey includes degrees from the University of Melbourne, University of Auckland, and Nanjing University. Research focuses on commercial property markets, urban economics, valuation theory, and sustainable land development. He applies new institutional economics and case study methods to explore property rights, policy design, and investment strategies. Spatial economics analyses in housing supply and brownfields redevelopment are key themes. Dr. Wu has taught at both undergraduate and graduate levels and serves on the editorial board of the Journal of International Housing Markets and Analysis. Professional activities include peer reviewing for academic journals and columnist roles in China Real Estate Business. His work bridges academic research with practical applications in property valuation, urban planning, and policy development. Recent collaborations involve developing quantitative frameworks for assessing brownfield redevelopment impacts and urban growth sustainability.

Tamar Zeilbergerمشاهده پروفایل

پژوهشگر ارشد

• Authoritarian Politics
• Political Economy
• Contemporary China
• +۳ مورد دیگر

Dr. Tamar Zeilberger is an LSE Fellow in Political Science and Public Policy at the London School of Economics and Political Science, focusing on comparative authoritarian politics, political economy, and contemporary China. Her research employs game theory and observational data analysis to address policy-relevant questions in authoritarian contexts. Education includes: PhD in Political Science, University of California, Los Angeles MA in Social Sciences, University of Chicago Her research integrates methodological innovations in statistics and machine learning to study political uncertainty, elite behavior, and interstate conflict dynamics. Current projects examine leadership transitions in China and robotic fabrication applications. Recent publications explore themes ranging from dispute escalation patterns in authoritarian regimes to cooperative robotics in architectural construction, reflecting interdisciplinary approaches to complex socio-political and technical systems. No scientific awards reported. Teaching responsibilities include graduate courses in Political Science for Public Policy and undergraduate data analysis, with pedagogical tools developed to illustrate probability concepts through simulations.

• Biostatistics
• Spatial statistics and disease mapping
• Statistical methods for survival and longitudinal data
• +۳ مورد دیگر

Cindy Feng, PhD, is an Associate Professor in the Department of Community Health and Epidemiology at Dalhousie University's Faculty of Medicine. Her research focuses on developing biostatistical models for analyzing correlated public health data, including spatial statistics, longitudinal studies, and environmental health applications. She holds a PhD from Simon Fraser University and has received funding from NSERC, Canadian Statistical Sciences Institute, and MITACS. Dr. Feng collaborates with interdisciplinary teams across medicine, psychology, and environmental sciences. Education: PhD (Simon Fraser University), MSc (Simon Fraser University), BSc (Beijing University of Technology). Her work emphasizes bridging statistical theory and practice in public health, with notable contributions to disease mapping, survival analysis, and infectious disease surveillance. Key grants include NSERC Discovery Grants ($80,000, 2019-2023) and a MITACS Accelerate Grant ($45,000, 2016-2019). Research interests include zero-inflated models, spatial epidemiology, and methodological advancements for correlated data. Recent work addresses pandemic-related mental health trends, occupational injury risk factors, and global health challenges in malaria-schistosomiasis co-endemic regions. She has published over 30 peer-reviewed articles, with a focus on statistical diagnostics, public health policy, and environmental health impacts.

Chris Boneمشاهده پروفایل

دانشیار

• Geospatial technologies
• Spatial simulation modelling
• Human-environment interactions
• +۵ مورد دیگر

Dr. Chris Bone is an **Associate Professor in Geography** at the **University of Victoria**, affiliated with the **Faculty of Social Sciences**. His research focuses on geospatial technologies, spatial simulation modeling, and human-environment interactions, particularly in relation to climate change and forest policy. He holds a PhD from Simon Fraser University and teaches advanced spatial analysis and geostatistics (GEOG 418/518). **Research Interests**: Dr. Bone’s work integrates computational methods like agent-based modeling and network modeling to study climate-driven natural disturbances (e.g., mountain pine beetle outbreaks), wildfire management, and human-wildlife interactions. He emphasizes geovisualization tools for environmental decision-making and has collaborated with Indigenous communities on biocultural stewardship projects. **Publications**: His recent work explores topics such as wildfire-beetle interactions, grizzly bear translocation success, and the role of federal air quality standards in prescribed fire practices. Over 50 peer-reviewed articles span environmental science, GIS applications, and policy analysis. **Awards**: No specific scientific awards listed in the provided texts. **Grants & Labs**: Active in interdisciplinary projects funded by organizations like the National Science Foundation (NSF CNH). Leads research on geospatial tools for managing invasive species and optimizing forest governance networks.

• International Conflict
• War Termination
• Insurgency Modeling
• +۳ مورد دیگر

Dr. D. Scott Bennett is a Distinguished Professor of Political Science and Senior Associate Dean for Research and Graduate Studies at Pennsylvania State University’s College of the Liberal Arts. He holds roles as Associate Director of the Correlates of War Project. His expertise spans statistical/simulation modeling of international conflict, war termination, and insurgency dynamics. Bennett holds a Ph.D. from the University of Michigan (1993). Research Interests: Agent-based simulations of insurgency development Quantitative analysis of war duration and rivalry termination Data integration methodologies for international conflict studies Evaluation of political similarity measures in conflict analysis Notable Contributions: Developed EUGene (2011 J. David Singer Data Innovation Award winner) and MARGene software packages for conflict data management. Co-authored The Behavioral Origins of War (2004). Active in advancing computational modeling tools for political science research. Teaching & Mentoring: Teaches courses on international relations, conflict resolution, and international conflict at Penn State. Advises on computational modeling methodologies through collaborative research projects. Current Initiatives: Focused on expanding agent-based simulations to model insurgency dynamics and government response strategies. Currently on sabbatical through FY 2025-2026.

Michelle Greiverمشاهده پروفایل

استاد

• Public Health
• Cardiovascular Disease
• Diabetes Management
• +۳ مورد دیگر

Prof Michelle Greiver is an Honorary Professor in the School of Medicine at the University of St Andrews. Her research focuses on public health outcomes in primary care settings, particularly addressing cardiovascular disease, diabetes management, and healthcare disparities. She collaborates on projects involving medication adherence patterns, mental health comorbidities, and advanced statistical modeling techniques. Her work contributes to UN Sustainable Development Goals related to good health and well-being (SDG 3). Recent studies include analyses of breast cancer screening equity among individuals with schizophrenia and the impact of adherence to medication regimens on cardiovascular outcomes in patients with diabetes and hypertension. Prof Greiver is affiliated with the University of St Andrews School of Medicine, contributing to both research and academic activities. Her methodologies often integrate epidemiological approaches with health informatics, including applications of marginal structural models and machine learning algorithms.

Cezary Z. Janikowمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Evolutionary Computation
• Genetic Algorithms
• +۹ مورد دیگر

Cezary Z. Janikow is an Associate Professor and former Chair of the Department of Mathematics and Computer Science at the University of Missouri–St. Louis (UMSL), where he conducts research in artificial intelligence, evolutionary computation, and machine learning. He is the developer of FID (Fuzzy Inference Decision tree), a system for generating fuzzy decision trees that handle missing, noisy, and continuous data. His research is supported by NIH, NSF, and NASA/JSC, and he has contributed significantly to the field of genetic programming, particularly in constrained and adaptable representations (ACGP). Ph.D. in Computer Science, University of North Carolina at Chapel Hill, 1991 His research interests center on evolutionary algorithms , fuzzy decision trees , and symbolic machine learning . He explores how genetic programming can adapt representations and incorporate constraints to improve search efficiency and solution quality. His work on FID has advanced fuzzy logic applications in classification and data analysis. The recent publications reflect a sustained focus on genetic programming , particularly Adaptable Constrained Genetic Programming (ACGP) , heuristics in evolutionary search , and fuzzy decision systems . His work spans theoretical development, algorithm design, and practical implementation, with applications in optimization and machine learning. Dr. Janikow has delivered corporate training in software development and served as an expert witness in software-related legal cases. He has also organized academic workshops and presented tutorials on evolutionary algorithms. Co-PI, NIH: Statistical Methods for Recursively Partitioned Trees NSF Support: Fuzzy Decision Trees NASA/JSC Collaboration: Constrained Genetic Programming He leads the FID project, a software system for fuzzy decision tree generation, which includes a GUI and supports cross-validation and noise simulation. This tool reflects his integration of research and software development.