جست‌وجوی استاد و پژوهشگر

• Psychometrics
• Cognitive Psychology
• Developmental Disorders
• +۵ مورد دیگر

Sara Giovagnoli is an Associate Professor at the University of Bologna's Department of Psychology 'Renzo Canestrari', specializing in psychometrics and cognitive psychology. Her research focuses on developmental disorders, sleep science, and educational technology. Key areas include emotion regulation in learning disabilities, motor sleep inertia mechanisms, and cognitive assessment tools like Bayesian networks for intelligence testing. Her work integrates behavioral neuroscience with digital innovation, exemplified by projects such as the PsycAssist AI system for neuropsychological assessment and the Eye-Riders game for neurodiverse children. She explores the intersection of chronobiology and mental health, analyzing circadian rhythms in adolescents and neurodegenerative patients through actigraphy. Recent studies address repetitive negative thinking in university students and the role of social support in adolescent internet use. Methodologically, she advances statistical frameworks like Bayesian informative hypotheses and comparative dimensionality reduction techniques. Her contributions span clinical applications (e.g., Multiple Sclerosis motor activity analysis) to educational interventions targeting early literacy and executive function enhancement through adaptive technologies. Collaborations emphasize cross-disciplinary approaches, linking neurophysiological metrics to psychosocial outcomes in diverse populations including teachers, parents of preterm infants, and young carers. Her research bridges theoretical cognitive science with practical tool development for clinical and educational settings.

Arthur Bergمشاهده پروفایل

استاد

• Biostatistics
• Bioinformatics
• Clinical Trials Analysis
• +۳ مورد دیگر

Arthur Berg is a Professor in the Department of Public Health Sciences at Penn State, with affiliations in the Cancer Institute and multiple clinical departments. He holds concurrent professorships in Surgery, Neurosurgery, Family and Community Medicine, and Statistics. Berg earned his PhD in Mathematics from UCSD (2007) and has extensive expertise in biostatistics and bioinformatics, including computational tool development and methodological research. His research focuses on statistical methodologies for biostatistics, Bayesian analysis, and clinical trial design. Notable contributions include work on NIH-funded trials, spinal cord injury nutrition, and tumor heterogeneity in oncology. He serves as Director of the Biostatistics PhD Program since 2012 and teaches advanced courses like Bayesian Statistics and Asymptotic Tools. Berg collaborates across disciplines, with recent publications spanning spinal cord injury outcomes, cancer treatment dynamics, and diabetes care in immigrant populations. His computational methods emphasize robust statistical frameworks and interdisciplinary applications, reflecting his dual strengths in theoretical and applied statistics.

• Human Evolution
• Paleoanthropology
• Anatomical Morphology
• +۳ مورد دیگر

Dr. Karen Baab is a Professor of Anatomy at Midwestern University, holding cross-appointments across multiple colleges including the Arizona College of Optometry, College of Dental Medicine-Arizona, and Arizona College of Osteopathic Medicine. She specializes in paleoanthropology and anatomical morphology, with a focus on human evolution, craniofacial evolution, and hominin fossil analysis. Her research integrates geometric morphometrics to study evolutionary patterns and functional adaptations in extinct and modern humans. Education: Ph.D. in Anthropology, The Graduate Center, CUNY (2007) M.A. in Anthropology, Hunter College, CUNY (2003) B.A. in Anthropology, Muhlenberg College (2000) Research Interests: Dr. Baab explores topics such as hominin cranial variation, the evolutionary relationships between Homo erectus and modern humans, and biomechanical adaptations in the skull and larynx. Her work often involves reconstructing fossil specimens (e.g., Homo floresiensis pelvis, Gona hominin fossils) and analyzing their morphological and functional implications. Teaching: She teaches anatomy courses, including head and neck anatomy for dental and medical students, and serves as a course director for anatomical sciences programs. Outreach: Active in science education, she judges the Arizona State Science and Engineering Fair and contributes to public outreach initiatives.

• Time Series Analysis
• Monetary Policy
• Fiscal Policy
• +۳ مورد دیگر

Fabio Gómez-Rodríguez is an Assistant Professor in the Department of Economics at Lehigh University since 2021. Originally from Costa Rica, he holds a Ph.D. in Economics from Indiana University (2021), an MA in Economics from Indiana University (2018), and a Dipl.-Wirt.-Math. from Technische Universität Darmstadt (2011). His research focuses on time series analysis with applications to monetary and fiscal policy, particularly exploring non-stationarities and their effects on inflation expectations and economic shocks. His teaching spans multiple institutions, including Lehigh University (courses: Econometrics I, Statistical Methods II) and Indiana University (Introduction to Microeconomics, Empirical Econometrics). He has also taught at the Universidad de Costa Rica in mathematics and statistics courses. His research interests emphasize regime-dependent effects of policy, exchange rate pass-through mechanisms, and econometric methodologies for testing unit roots and regime shifts. His working papers address topics such as the impact of U.S. government decisions on borrowing costs and distributional effects of inflation expectations under different policy regimes. While his current profile does not explicitly list scientific awards or grants, his extensive publication record reflects active engagement with cutting-edge econometric techniques and macroeconomic policy analysis.

• Statistical Machine Learning
• Bayesian Statistical Inference
• Statistical Ecology
• +۷ مورد دیگر

Jabed Tomal is an Associate Professor in Statistics and Data Science at Thompson Rivers University (TRU), Canada. Previously, he held positions as an Assistant Professor at TRU (2018–2023) and the University of Toronto Scarborough (2014–2018), and a Postdoctoral Fellow at the University of British Columbia (2014). He earned a Ph.D. in Statistics (2013) from UBC, specializing in statistical machine learning, and dual M.Sc. degrees in Statistics (University of Windsor, 2007) and Biostatistics (University of Dhaka, Bangladesh). His research focuses on ensemble methods, Bayesian inference, and statistical ecology, with applications in drug discovery, protein homology, and environmental modeling. Key research interests include developing ensemble models for high-dimensional data, Bayesian methods for breakpoints detection in housing markets and ecological systems, and statistical approaches in healthcare. Notable contributions include work on QSAR studies, Bayesian hierarchical modeling of pandemic impacts, and ecological threshold detection. Tomal has secured grants such as the NSERC Discovery Grant ($102,500) and TRU internal funds for projects in big data and environmental thresholds. He has advised numerous graduate and undergraduate students on topics ranging from machine learning in healthcare to single-cell RNA sequencing analysis. His teaching spans courses like Bayesian Machine Learning, Multivariate Statistics, and Theoretical Machine Learning at the graduate level, alongside foundational statistics and calculus courses at TRU and the University of Dhaka. Administrative roles include Chair of the Award and Scholarship Committee for TRU’s Master of Data Science program and membership in Senate Research Committee. Education: Ph.D., Statistics (2013), UBC Vancouver M.Sc., Statistics (2007), University of Windsor M.Sc., Biostatistics (2005), University of Dhaka Awards: NSERC Discovery Grant (2021–2026) Research Training Recognition Fund (TRU,多次) SSC 2013 Talk Honourable Mention Labs/Teams: Active in interdisciplinary projects at TRU’s Department of Mathematics and Statistics, focusing on data science applications in ecology, healthcare, and genetics.

Daniel Pressnitzerمشاهده پروفایل

استاد پژوهشی

• Auditory Perception
• Cognitive Neuroscience
• Psychophysics
• +۶ مورد دیگر

Daniel Pressnitzer is a CNRS Director of Research and Deputy Manager of the Laboratoire des Systèmes Perceptifs (LSP) at École normale supérieure in Paris. He leads the Audition team within LSP, conducting research at the intersection of auditory perception, cognitive neuroscience, and psychophysics. His work spans from fundamental auditory mechanisms to applied research in hearing impairment and audio processing. Pressnitzer's research focuses on experimental studies of audition, integrating multiple levels of analysis from acoustic signals to non-verbal auditory cognition. His work employs diverse methodological tools including psychophysics, modeling, and physiology. A central hypothesis driving his research is the existence of 'mid-level audition' processes critical to real-world listening that can be systematically tested through psychophysical methods. Current projects investigate auditory memory, perceptual bistability, multi-modal comparisons, music perception, and natural sound recognition. Analysis of Pressnitzer's recent publications reveals a strong emphasis on auditory memory mechanisms, cross-modal perception, and the neural correlates of conscious processing. His work increasingly incorporates machine learning approaches to analyze complex auditory phenomena while maintaining rigorous psychophysical methodologies. Notable recent contributions include discoveries about sleep deprivation detection through voice analysis and the relationship between auditory perception and conscious processing. Fyssen Fellowship Wellcome Trust Postdoctoral Fellowship Pressnitzer teaches in several prestigious programs including the masters of cognitive sciences from École Normale Supérieure, EHESS, and Universités Paris 5, where he coordinates the Auditory Perception course. He also teaches in the ATIAM and IMA masters programs. As the leader of the Audition team at LSP since 2008, he co-manages the Neuroscience track of the Cogmaster, recruiting students annually. His laboratory investigates fundamental auditory processes with potential applications in hearing impairment and audio processing technologies.

• Data Science
• Information Systems
• Applied Computer Science
• +۳ مورد دیگر

Michael Heiss is an Honorary Professor affiliated with the Data Science department at Vienna University of Technology (Technische Universität Wien). His research focuses on practical applications of data science in enterprise systems, environmental monitoring, and entrepreneurship. 2023 publication on metaverse business trips 2016 case study on enterprise social networks (Siemens TechnoWeb) 2016 feasibility study for forest monitoring drones 2015 work on hypothesis-driven entrepreneurship His work demonstrates strong industry collaboration through case studies with organizations like Siemens. Key research areas include: Enterprise social network implementation Drone-based acoustic surveillance Entrepreneurship methodology Metaverse applications He has supervised multiple student theses on these topics, indicating active academic mentorship.

• Rheumatology
• Infectious Disease Arthritis
• Autoimmune Disorders
• +۳ مورد دیگر

Robert Schoen, MD, MBA, is a Clinical Professor in the Department of Internal Medicine at Yale School of Medicine, specializing in Rheumatology. His clinical expertise includes rheumatoid arthritis, psoriatic arthritis, and Lyme disease. With a career spanning over four decades, he holds an MD from Columbia University (1976), an AB in Biochemical Sciences from Harvard (1972), and an MBA from the University of Connecticut (2001). His research focuses on viral arthritis (particularly chikungunya and Lyme disease), postinfectious inflammatory conditions, and therapeutic interventions for chronic arthritic conditions. Dr. Schoen’s research has produced over 30 peer-reviewed publications, including seminal works on chikungunya arthritis pathogenesis, Lyme disease management, and methotrexate efficacy. Notable contributions include a 2025 systematic review linking chikungunya fever to rheumatoid arthritis and a 2024 randomized trial evaluating methotrexate/dexamethasone treatment for chikungunya arthritis. His work bridges clinical practice and translational research, emphasizing patient-centered care and global health implications. Recognitions include designation as a Master of the American College of Rheumatology (2023) and inclusion in multiple ‘Top Doctors’ lists. His academic leadership includes roles in residency training at Yale New Haven Hospital and fellowships at Brigham and Women’s Hospital (1981). Ongoing efforts focus on improving diagnostic accuracy and therapeutic strategies for emerging and chronic rheumatologic conditions. Education: AB Harvard (1972), MD Columbia (1976), MBA UConn (2001) Board Certifications: Rheumatology and Internal Medicine (ABIM) Awardees: Master of the American College of Rheumatology, 2023 ‘Top Doctors’ (Yale Medicine)

Nolan Coleمشاهده پروفایل

استاد

• Biostatistics
• Statistical Genetics
• High-Dimensional Data Analysis
• +۶ مورد دیگر

Nolan Cole holds the position of Professor and Chair in the Department of Biostatistics at the University of Washington. His research focuses on developing statistical methods for high-dimensional data, selective inference, and addressing measurement error in compositional datasets, with applications in genomics and epidemiology. He collaborates with Dr. Daniela Witten and Dr. Arkajyoti Saha on hypothesis testing methodologies in feature-selected datasets. Education includes a PhD in Biostatistics from the University of Washington and a Bachelor’s in Statistics from Brigham Young University. His prior research spans meta-analysis methodologies for zero-event clinical trials, mediation analysis in breast cancer genetics, and spatial transcriptomics simulations during his time at Harvard Medical School. Key projects include investigating distal non-coding RNA regulation in breast cancer using eQTLs, analyzing electronic health records for multiple myeloma patients, and studying epigenetic differences in monocytes based on sex. His work bridges statistical theory with biomedical applications, aiming to improve disease understanding through advanced data analysis techniques.

• Immunology
• Clinical Sciences
• Oncology and Carcinogenesis
• +۳ مورد دیگر

Dr. Jennifer Boer is a Postdoctoral Research Fellow at RMIT University's Research & Innovation Capability department in Bundoora West, Australia. Her research focuses on immunology, clinical sciences, oncology, nanotechnology, and medical health sciences, with a particular emphasis on vaccine development, nanomedicine, and infectious disease mechanisms. She is actively involved in supervising Masters and PhD students, including projects like 'Metagenetic Approach to Analyse Vaccine Immunomodulation in the Elderly' and 'Gold-based drugs for the effective treatment of ovarian cancer'. Her work spans interdisciplinary areas, such as vaccine delivery systems using liposomes and polymeric nanoparticles, and the study of SARS-CoV-2 mutations affecting protein flexibility. She also explores ethical and statistical aspects of animal experimentation design. Dr. Boer collaborates widely, contributing to fields like environmental microbiology, drug discovery pedagogy, and glaucoma immunotherapy. Her recent publications highlight advancements in vaccine adjuvants, anaerobic sewage sludge analysis, and the role of tumor necrosis factor receptors in disease. She is open to mentoring students in these and related areas.

• Economic Theory
• Asset Pricing
• Monetary Policy
• +۷ مورد دیگر

Jianjun Miao is a Professor recognized for his significant contributions to economic theory, evidenced by his 2025 election as Fellow of the Society for Advancement of Economic Theory. His academic work bridges theoretical economics with practical policy applications across multiple domains. His research spans economic theory, asset pricing, monetary and fiscal policy, rational inattention, and asset bubbles. Miao's work demonstrates particular expertise in modeling decision-making under uncertainty, financial market dynamics, and macroeconomic policy interactions. His research integrates advanced mathematical techniques with real-world economic phenomena, focusing on how information frictions and ambiguity affect market outcomes and policy effectiveness. Analysis of his 2022-2025 publications reveals three dominant research trajectories: (1) asset bubbles and their macroeconomic implications, (2) rational inattention frameworks in discrete choice and asset pricing, and (3) fiscal-monetary policy coordination in constrained environments. His work consistently addresses methodological challenges in modeling uncertainty while providing policy-relevant insights for financial stability and economic growth. Scientific Awards: Fellow of the Society for Advancement of Economic Theory (2025) Professor Miao maintains an active research program with substantial scholarly output. His work appears in leading economics journals and influences both academic discourse and policy discussions regarding financial stability, economic growth, and optimal policy design under uncertainty. He contributes significantly to academic knowledge through theoretical model development and empirical applications.

Marinho Bertanhaمشاهده پروفایل

دانشیار

• Econometrics
• Causal Inference
• Applied Microeconomics
• +۵ مورد دیگر

Marinho Bertanha is a tenured Associate Professor of Economics at the University of Notre Dame, serving as concurrent faculty in Statistics and a faculty fellow at the Kellogg Institute. His academic work bridges econometrics and applied microeconomics with significant contributions to causal inference methodologies. His educational background includes a Ph.D. in Economics from Stanford University (2015), an M.A. from Fundação Getúlio Vargas in Rio de Janeiro (2009), and a B.A. from Universidade de São Paulo (2006). Prior to his current position, he completed postdoctoral work at the University of Louvain and served as a visiting professor at the University of Chicago. Bertanha's research focuses on causal inference , resampling methods , and policy evaluation , with particular expertise in regression discontinuity designs, bunching estimation, and permutation testing. His methodological innovations address critical challenges in econometric identification and statistical inference, especially in contexts with strategic reporting and imperfect compliance. His publication record shows consistent high-impact output in top journals including the Journal of the American Statistical Association , Journal of Econometrics , and Review of Economics and Statistics . Recent work demonstrates increasing focus on practical implementation through software development (Stata and MATLAB packages) that has become standard in empirical economics research. Through his concurrent appointment in Statistics and faculty fellowship at the Kellogg Institute, Bertanha contributes to interdisciplinary research initiatives focusing on economic policy evaluation and statistical methodology development. His current work-in-progress examines causal effects in matching mechanisms, returns to education with strategic reporting, and tax elasticity estimation across multiple countries.

Igor Cialencoمشاهده پروفایل

استاد

• Quantitative Finance
• Statistical Inference for Stochastic PDEs
• Stochastic Control
• +۳ مورد دیگر

Igor Cialenco is a Full Professor in the Department of Applied Mathematics at Illinois Institute of Technology (College of Computing). He holds a Ph.D. in Applied Mathematics from the University of Southern California (2007). Research Interests : Quantitative Finance, Statistical Inference for Stochastic PDEs, Stochastic Control, Environmental Finance, and Functional Analysis. Professional Roles : Managing Editor for the International Journal of Theoretical and Applied Finance, and editorial board member of multiple journals including SIAM Journal on Financial Mathematics. Research Trends : His recent publications focus on stochastic modeling in environmental finance (e.g., groundwater markets), robust control under model uncertainty, and statistical inference for SPDEs. The keywords span Financial Mathematics, Stochastic Processes, Environmental Modeling, and Statistical Learning. Scientific Awards : 2024 Researcher to Know (ISTC), 2024 College of Computing Dean's Excellence Award for Research, multiple Dean's Excellence awards in teaching and research. Mentorship & Funding : Mentored numerous PhD and MS students in quantitative finance and SPDEs. Current NSF grant DMS-2407549 supports research on stochastic modeling for water rights management. Past NSF grants include DMS-1907568 and DMS-0908099.

George Karabatsosمشاهده پروفایل

استاد

• Bayesian Statistics
• Statistical Modeling
• Psychometrics
• +۶ مورد دیگر

George Karabatsos is a Professor at the University of Illinois at Chicago (UIC), affiliated with the Department of Educational Psychology. His research focuses on developing and applying Bayesian statistical models, computational methods, and psychometric frameworks for complex data analysis. He has contributed to areas such as Bayesian nonparametrics, meta-analysis, causal inference, and educational measurement. His work has been supported by grants from the National Science Foundation, the Spencer Foundation, and the National Institutes of Health. Karabatsos has authored a menu-based statistical software package for analyzing data using over 100 models and served as an Associate Editor for journals like Psychometrika and Computational Statistics and Data Analysis . Education: PhD in Measurement, Evaluation, and Statistical Analysis (MESA) from the University of Chicago, 1998. Research interests include Bayesian modeling, computational statistics, psychometrics, and applications in education and biostatistics. His recent work emphasizes Bayesian methods for addressing issues like hidden bias, sensitivity analysis, and local dependence in statistical inference. Publications span topics such as nonparametric mixture models, meta-analytic techniques, and software development. His articles reflect a focus on methodological advancements and their practical implementation in real-world problems. Grants and advising: Karabatsos has led numerous research projects funded by major institutions. While specific student advisees are not listed, his software contributions indicate involvement in training researchers through accessible tools. Labs/Teams: He is the lead developer of a Bayesian statistical software package, fostering collaboration in applied statistical research.

Arthur Kraftمشاهده پروفایل

دانشیار

• Financial Reporting
• Capital Markets
• Corporate Governance
• +۳ مورد دیگر

Arthur Kraft is an Associate Professor at Bayes Business School, City St George's, University of London. Previously, he held faculty positions at the University of Rochester and London Business School. His research focuses on financial reporting's impact on capital markets, corporate governance, and voluntary disclosure mechanisms. He holds a BBA and MAcc from the University of Michigan and a PhD from the University of Chicago. Key research areas include the relationship between accounting information and security prices, the credibility of voluntary disclosures, and managerial myopia induced by frequent reporting. Recent work explores how financial reporting frequency affects corporate innovation and equity costs. Professional Activities: Served as referee for major journals including Journal of Accounting Research, Journal of Accounting and Economics, and The Accounting Review. Media Engagement: Featured in Accountant Middle East and The Sunday Times discussing tax strategies and corporate governance. Editorial Roles: Former Editorial Board member of European Accounting Review and active referee for multiple top-tier journals. Supervises research students Yun Sun and Richard Blades. His work has been presented at international venues like INSEAD, ESADE, and WHU-Otto Beisheim School of Management.