جست‌وجوی استاد و پژوهشگر

• Analytical Chemistry
• Elemental and Isotopic Analysis
• Inductively Coupled Plasma Mass Spectrometry (ICP-MS)
• +۷ مورد دیگر

Anastassiya Tchaikovsky is a postdoctoral researcher at the Institute of Analytical Chemistry, Department of Natural Sciences and Sustainable Resources, University of Natural Resources and Life Sciences, Vienna (BOKU). She holds a PhD in analytical chemistry and has an extensive research background in elemental and isotopic analysis, particularly using ICP-MS techniques. Her work spans food authentication, environmental forensics, and trace metal speciation. Her research interests include: Inductively Coupled Plasma Mass Spectrometry (ICP-MS) Chemometrics and multivariate data analysis Isotopic and elemental fingerprinting for provenance determination Metrology and method validation Separation techniques coupled to mass spectrometry Applications in food science, ecology, and human health Her recent publications demonstrate a strong trend toward interdisciplinary applications of analytical chemistry, particularly in verifying the geographical origin of food products (e.g., carrots, caviar, fish) using combined isotopic, elemental, and metabolomic fingerprints. She frequently employs chemometric modeling and data fusion techniques to enhance discrimination power. Her work also extends to biomedical applications, such as iron metabolism in neurodegenerative diseases and lead detoxification. She has received multiple scientific awards, including: Scholarship for a postdoc mentoring program (2019) Best talk award at DocDay, Tulln (2014) ESF-Studienabschluss scholarship (2013) Merkur scholarship from TU Vienna (2013) Best student lecture award at ICPMS Anwendertreffen (2012) Science scholarship from TU Vienna (2012) She has been involved in several research projects funded by the European Commission, Austrian federal and local governments, and private institutions. Her collaborative work includes advising on fish migration, caviar traceability, and citizen science initiatives like IsoPROTECT. She actively presents her research at international conferences and contributes to knowledge transfer in food safety and analytical methodology. She is affiliated with the Institute of Analytical Chemistry at BOKU and has no listed advisees, though she collaborates extensively with senior researchers and interdisciplinary teams.

Alan Pegnaمشاهده پروفایل

دانشیار

• Cognitive Neuroscience
• Clinical Neuropsychology
• Emotional Face Processing
• +۵ مورد دیگر

Associate Professor Alan Pegna is a neuropsychologist at the School of Psychology, University of Queensland, where he has been faculty since 2015. His research focuses on cognitive neuroscience and clinical neuropsychology, with particular expertise in visual and emotional processing using EEG methodologies. Dr. Pegna received his Masters in Psychology from the University of Geneva (Switzerland) followed by a second Masters in Human Physiology from University College London (UK). He completed his PhD at the University of Geneva, where he used brain imaging techniques to study spatial processing in both healthy controls and brain-damaged patients. His research interests center on the neural mechanisms underlying emotional face processing, particularly examining how the brain responds to different facial expressions and variations in perceived approachability and trustworthiness. He has extensive experience working with brain-damaged individuals to investigate the role of specific brain regions in visual and emotional processing. His work frequently employs EEG to measure early neural responses to emotional stimuli under various attentional conditions. Analysis of his recent publications reveals a consistent focus on emotional face processing using EEG methodologies. His work examines how spatial attention, visual awareness, and task relevance modulate neural responses to emotional faces. Key themes include the role of the amygdala in emotional processing, perspective taking in social cognition, blindsight phenomena, and the neural correlates of trustworthiness and dominance perceptions. Dr. Pegna has maintained an active research program since joining UQ in 2015, with over 150 journal articles and 30 conference papers to his name. His work demonstrates strong international collaboration, particularly with researchers in Switzerland and other European institutions. His laboratory specializes in EEG research on visual and emotional processing, with particular expertise in studying both healthy participants and individuals with neurological conditions. Current research focuses on how the brain processes emotional facial expressions under varying conditions of attention and awareness, with implications for understanding social cognition disorders.

• Statistics
• Machine Learning
• Financial Econometrics
• +۵ مورد دیگر

Jennifer Chan is a Professor in the Statistics Department at the University of Sydney's Faculty of Science. She earned her PhD from the University of New South Wales in 1997 and previously lectured at the University of Hong Kong before joining her current institution in 2006. Her research integrates statistical and machine learning models with applications in finance and insurance, including volatility modeling, Bayesian methods, and neural network applications. Her interdisciplinary research focuses on: Generalized linear mixed models and multivariate volatility measures Machine learning techniques for financial risk assessment Bayesian robustness and portfolio optimization Time-series analysis of cryptocurrencies and equity markets Recent publications demonstrate strong focus on Bayesian models in finance (42% of last 15 papers), machine learning applications (33%), and actuarial science (25%), with emerging emphasis on neural networks for financial forecasting. Awards & Honors: Second prize, Natural Science Award of China's Ministry of Education (2008) National Drug Strategy Research Scholarship (1994-1996) She supervises doctoral candidates working on machine learning applications in finance and insurance. Her international collaborations include institutions in Israel, Japan, Malaysia, and the United States.

• Statistical Problems in Marketing
• Functional Data Analysis
• Statistical Methodology
• +۲ مورد دیگر

Gareth James is the John H. Harland Dean and Professor of Information Systems & Operations Management at Emory University's Goizueta Business School, a position he assumed in July 2022. Prior to this, he held significant leadership roles at USC Marshall School of Business, including interim dean (2019-2020), vice dean of faculty, and deputy dean (2020-2022). James received his PhD in Statistics from Stanford University, complemented by a BComm in Finance and BS in Statistics from The University of Auckland. His academic journey reflects a strong foundation in both statistical methodology and business applications. James specializes in statistical problems in marketing, functional data analysis, statistical methodology, and high-dimensional regression. His research bridges theoretical statistics with practical business applications, particularly in the areas of machine learning, advertising optimization, and technology adoption. His work demonstrates a consistent focus on developing methodological innovations that address real-world business challenges. His research contributions have been widely recognized, with over 30,000 citations. James has led multiple National Science Foundation research grants and served as associate editor for five top research journals. His most notable scholarly contribution is co-authoring the highly successful textbook "An Introduction to Statistical Learning," which has become a standard reference in the field. Fellow of the American Statistical Association Fellow of the Institute of Mathematical Statistics Dean's Research Awards (two times) Evan C. Thompson Faculty Teaching and Learning Innovation Award Three-time winner of the Marshall School of Business' Golden Apple Award Dean's Ph.D. Advising Award USC Mellon Award Provost's Mentoring Award James is equally distinguished as a mentor and educator. His teaching excellence is evidenced by multiple Golden Apple Awards, while his mentoring impact is reflected in the Dean's Ph.D. Advising, USC Mellon, Evan C. Thompson, and Provost's Mentoring awards. As Dean, he leverages his expertise in data-informed decision making to strengthen Goizueta's mission of preparing principled leaders to have a positive influence on business and society.

Ralf Kellnerمشاهده پروفایل

استاد

• Economics
• Data Science
• Statistics
• +۲ مورد دیگر

Professor Ralf Kellner holds the Chair of Financial Data Analytics at the University of Passau, Faculty of Economics. His work integrates economics, data science, and statistics, focusing on empirical and application-oriented research to explore how statistical learning and AI can uncover insights in data-driven decision-making processes that generate economic value. He also teaches courses such as Deep Learning and Text Analysis in Finance, Financial Data Analytics and Machine Learning, and Scientific Computing with Python. His research examines the intersection of financial markets, statistical learning, and artificial intelligence, with specific interests in modeling adverse financial developments, systemic risks, and analyzing text data via domain-specific language models. Publications highlight collaborations with researchers like D. Rösch and N. Gatzert. Recent publications include work on hybrid service agents, quantile neural networks, default resolution time analysis, Bayesian sovereign bond risk models, and international diversification studies. His methodological approaches span extreme value theory, quantile regression, and multivariate statistical techniques applied to financial and insurance contexts. Contact: ralf.kellner@uni-passau.de

Sandra Safoمشاهده پروفایل

دانشیار

• Multivariate Statistical Analysis
• High-dimensional data
• Data integration
• +۱۴ مورد دیگر

Sandra Safo is an Associate Professor in the Division of Biostatistics and Health Data Science within the College of Science and Engineering at the University of Minnesota. She serves as Graduate Faculty in Bioinformatics and Computational Biology and Data Science. Education: PhD in Statistics, University of Georgia, 2014 MSc in Applied Mathematics, The University of Akron, 2009 BA in Mathematics and Economics, University of Ghana, 2006 Research Interests: Dr. Safo develops robust, explainable statistical and machine learning methods for high-dimensional data including multivariate analysis, integrative multi-omics data fusion, discriminant analysis, classification, clustering, and functional data analysis. Her applied work focuses on cardiovascular diseases in HIV populations, diabetes complications, and metabolomics with emphasis on social determinants of health. Scientific Awards and Recognition: COPSS Emerging Leader Award, 2024 McKnight Land-Grant Professor, 2023-2025 NIH ESI Outstanding Award, 2021-2026 International Statistical Institute Member, 2022 NIH ASPA Standing Member, 2022-2026 UMN CTSI KL2 Scholar, 2018-2021 BIRCWH Scholar, Emory University, 2016-2017 PRIDE Scholar, Washington University, 2016-2018 Grants and Leadership: Principal Investigator on NIH Maximizing Investigators' Research Award (MIRA R35), Administrative Supplements from NIA and Office of Data Science and Strategy, and UMN internal grants. Leads development of the Integrative Modeling Dashboard for multi-view data analysis. Computational Resources: Creator of open-source tools including iDeepViewLearn (interpretable deep learning), DeepIDA-GRU (longitudinal data integration), SIDA (multi-view association studies), and HIP (joint association prediction) available on GitHub.

Krish Muralidharمشاهده پروفایل

استاد

• Data Privacy
• Statistical Disclosure Limitation
• Database Security
• +۳ مورد دیگر

Krish Muralidhar is the Baldwin Chair and Professor of Marketing & Supply Chain Management at the University of Oklahoma's Price College of Business. He holds a Ph.D. from Texas A&M University, an MBA from Sam Houston State University, and a B.Sc. from the University of Madras, India. His research centers on data privacy , developing techniques for secure data analysis, sharing, and dissemination. Key areas include statistical disclosure limitation, differential privacy, database reconstruction risks, and perturbation methods. He patented the Data Shuffling technique for secure data release. Recent publications (2022–2025) focus on census data privacy, reidentification vulnerabilities, and critiques of differential privacy in machine learning. Trends highlight rigorous evaluations of privacy risks in statistical databases and policy-relevant solutions. Awards: Distinguished Doctoral Alumni Award (Texas A&M, 2006) Teaching Incentive Program Award (1994) Excellence in Research Award (1995) Best Inter-disciplinary Paper Award (2002) Best Paper Award (2005) No advising, grant, lab, or team details were provided.

Michael P. Clementsمشاهده پروفایل

استاد

• Time-Series Econometrics
• Economic Forecasting
• Data Revisions
• +۷ مورد دیگر

Professor Michael P. Clements is a leading econometrician at the ICMA Centre , Henley Business School, University of Reading. His research focuses on time-series econometrics, forecasting methodologies, and macroeconomic uncertainty. A DPhil graduate from Nuffield College, Oxford (1993), he held roles at Warwick University (1995–2007) before becoming a full professor in 2007 and joining Reading in 2013. Research Themes : Data revisions, mixed-frequency models, survey expectations, factor models, and macroeconomic forecasting. Editorial Roles : Former Editor of International Journal of Forecasting (2001–2012), current Associate Editor. Scientific Contributions include over 100 journal articles and 5 books. Key awards: Journal of Applied Econometrics Distinguished Author (2008) Honorary Fellow, International Institute of Forecasters (2014) Fellow, International Association for Applied Econometrics (2018) Palgrave Texts in Econometrics Series Editor (2017–) Collaborations with Ana Beatriz Galvão, David Hendry, and others have advanced real-time forecasting and uncertainty analysis. His work bridges econometric theory with practical applications in inflation, GDP growth, and financial markets.

Adam J Rothmanمشاهده پروفایل

استاد

• High-Dimensional Statistics
• Covariance Estimation
• Multivariate Analysis
• +۲ مورد دیگر

Adam J Rothman is a Professor in the Department of Statistics at the University of Minnesota, Twin Cities campus, specializing in high-dimensional statistical methodologies. His research focuses on covariance estimation, multivariate analysis, and developing innovative regression frameworks for complex data structures. His primary research interests include High-Dimensional Statistics, Covariance Estimation, Multivariate Analysis, and Statistical Machine Learning. Rothman develops penalized likelihood methods and shrinkage estimators to address challenges in matrix-valued predictors, categorical responses, and large covariance matrices, with applications spanning scientific domains requiring scalable high-dimensional analysis. Rothman's recent publications (2019-2024) demonstrate consistent innovation in high-dimensional regression and classification. Key trends include covariance matrix regularization, sufficient dimension reduction techniques, and likelihood-based approaches for categorical multivariate responses. His work emphasizes computational efficiency and theoretical guarantees for datasets where variables exceed sample sizes. He has secured major National Science Foundation funding as Principal Investigator for two projects: Sufficient Dimension Reduction of High-Dimensional Data (2011-2015) and New methods for multivariate analysis in high dimensions (2015-2021). These grants supported foundational work in dimension reduction and covariance estimation, advancing methodologies for modern statistical challenges.

• Linguistics
• Second Language Acquisition
• Language Assessment
• +۵ مورد دیگر

Scott Jarvis is a Professor in the Department of English at Northern Arizona University with an extensive research portfolio spanning linguistics and language acquisition. His scholarly impact is evidenced by an h-index of 26 and 4029 citations according to Scopus metrics. Dr. Jarvis's research focuses on second language acquisition , language assessment , and cross-linguistic influences . His work examines language attrition among Macedonian L2 learners, conceptual transfer mechanisms between languages, and lexical diversity patterns across media contexts. The research fingerprint analysis shows strong associations with English (100%), Lexical studies (61%), Finnish language (58%), Swedish language (54%), and Native Speaker phenomena (47%). Recent publications demonstrate increasing interdisciplinary applications of linguistic research, particularly in forensic contexts (Miranda rights comprehension analysis) and digital humanities (TV genre prediction through lexical analysis). His methodological approaches range from Rasch analysis for assessment tools to multivariate modeling for corpus linguistics. With 59 scholarly works documented since 2000, Dr. Jarvis maintains consistent research productivity with publications appearing through 2024. His work shows international collaboration patterns and appears in journals spanning applied linguistics, language assessment, and forensic linguistics.

• Quantum Topology
• Knot Theory
• Algebraic Topology
• +۳ مورد دیگر

Jorge Becerra is a part-time Post-Doctoral Fellow at the University of Burgundy , affiliated with the Faculty of Science and working in the Mathematics-Physics team. He collaborates with Lukas Woike on quantum topology and grid homology. PhD in Mathematics from the University of Groningen. Master's degree from Utrecht University. Bachelor's degree from the University of Extremadura. His research focuses on Knot Theory , Algebraic Topology , and Category Theory , with applications in Quantum Topology and Heegaard-Floer Homology . He has co-lectured Topics in Topology at the University of Groningen and organized seminars on knot theory. He supervised D. Apol 's Bachelor's thesis on cohomology theories and contributed to teaching courses like Multivariable Analysis and Algebraic Topology . His contact email is Jorge.Becerra-Garrido@ube.fr .

• Sports Science
• Biathlon Training
• Physiological Responses
• +۷ مورد دیگر

Marko Laaksonen is a Professor at the Department of Health Sciences (HOV) at Mid Sweden University, specializing in winter sports biomechanics and performance analysis. He is affiliated with the Swedish Winter Sports Research Centre, focusing on biathlon and cross-country skiing. His research examines physiological responses to training, rifle carriage effects on skiing mechanics, and performance indicators in biathlon. Key areas include exercise intensity distribution, shooting precision, and muscle metabolism during endurance activities. Recent publications analyze biathlon shooting performance under varying conditions, training load measurement, and equipment impacts on athlete efficiency. Over 15 articles demonstrate expertise in winter sports analytics and physiological monitoring.

• Biomedical Sciences
• Translational Research
• Tuberculosis Diagnostics
• +۵ مورد دیگر

Colleen Bannon Bushell serves as a Research Associate Professor in Biomedical and Translational Sciences at the University of Illinois. She also holds the position of Director of the Healthcare Innovation Program Office at the National Center for Supercomputing Applications (NCSA) and is an Affiliate at the Carl R. Woese Institute for Genomic Biology, including the Personalized Nutrition Initiative. Dr. Bushell's research spans multiple interdisciplinary domains at the intersection of biomedical science, data analytics, and clinical applications. Her work focuses on developing novel diagnostic approaches and biomarkers for various conditions including tuberculosis, cancer, and microbiome-related disorders. She applies advanced computational methods to analyze complex biological data, with particular expertise in cytokine profiling, label-free imaging techniques, and microbiome analysis. Her publication record demonstrates a strong focus on translating basic science discoveries into clinical applications. Recent work shows expertise in tuberculosis diagnostics using multiplexed cytokine profiling, cancer research using patient-derived xenograft models, and nutritional biomarker development through microbiome analysis. Her research bridges computational approaches with biomedical applications, particularly in the areas of infectious disease, oncology, and nutritional science. Dr. Bushell collaborates extensively across disciplines, working with researchers in statistics, computer science, microbiology, and clinical medicine. Her work has received attention across multiple platforms, with mentions in news outlets, blog posts, and patent applications related to her biomarker research. She directs the Healthcare Innovation Program Office at NCSA, indicating leadership in applying computational resources to healthcare challenges. Her affiliation with the Personalized Nutrition Initiative suggests involvement in research connecting dietary patterns, microbiome composition, and health outcomes.

• Process Control
• Systems Biology
• Mathematical Modeling
• +۳ مورد دیگر

Elling W Jacobsen is a Professor at the Division of Decision and Control Systems, KTH Royal Institute of Technology . His research focuses on process control (mathematical modeling and control of chemical and biochemical systems) and systems biology (learning intracellular network structures and analyzing their impact on cellular robustness). He has held academic positions at Imperial College, Caltech, and NTNU. He is affiliated with the IFAC Technical Committee on Chemical Process Control and serves on the Editorial Board of IET Systems Biology . Research Interests Dynamic behavior of process systems Feedback mechanisms in biochemical systems Network interactions in cellular functions Scientific Awards O. Hugo Schuck Award ExxonMobil Prize Teacher Award 'En Fjäder i Hatten' Teaching Roles Examiner for multiple advanced courses in control systems and robotics Teacher for nonlinear control, multivariable control, and sustainable systems

• Bayesian Methods
• Stochastic Processes
• Time Series Analysis
• +۳ مورد دیگر

Tevfik Aktekin is a Professor in the Department of Decision Sciences at the Paul College of Business and Economics, University of New Hampshire. His research focuses on Bayesian inference and stochastic modeling in service systems and business analytics. Education : Ph.D. in Decision Sciences (George Washington University), M.B.A. in Management Decision Making (George Washington University), B.S. in Mechanical Engineering (Yildiz Technical University). His work applies Bayesian state-space models to multivariate count data, with applications in call center staffing, product modification cycles, and public health analysis. He has published in journals like Annals of Applied Statistics , Bayesian Analysis , and European Journal of Operational Research . The 15 most recent articles highlight trends in sequential Bayesian learning for dynamic systems (e.g., bike-sharing, web traffic), time series of non-Gaussian data, and stochastic optimization under uncertainty. These works bridge statistical theory with practical applications in business and health.