جستجوی استاد راهنمای دانشگاهی

Urszula Ala-Karviaمشاهده پروفایل

پژوهشگر

• Social Sciences
• Statistics and Probability
• Food Science
• +۳ مورد دیگر

Urszula Ala-Karvia is a Doctoral Researcher at the Ruralia Institute Seinäjoki , part of the Faculty of Agriculture and Forestry at the University of Helsinki . She is affiliated with the Helsinki Institute of Sustainability Science (HELSUS) and actively contributes to research on sustainable food systems, demographic analysis, and statistical modeling. Her research interests include urban-rural migration patterns , household structure changes , sustainable public meal provision , energy policy analysis , and statistical demography . She employs both quantitative and qualitative methods to study socio-economic phenomena across Finland, Poland, and the Baltic Sea Region. Recent publications focus on suburbanization effects in Poland , electricity price structures in EU countries , and digital innovation hubs in Arctic regions . Her work addresses sustainability challenges in public catering , climate-smart dairy transitions , and gender equity in rural entrepreneurship . She participates in EU-funded projects such as GENGREEN (2024-2026) and StratKIT+ (2022-2024), and contributes to interdisciplinary collaborations through conferences and workshops across Nordic-Baltic regions.

Laura K. Nelsonمشاهده پروفایل

دانشیار

• Computational Sociology
• Social Movements
• Gender Studies
• +۴ مورد دیگر

Laura K. Nelson is an Associate Professor of Sociology at the University of British Columbia (UBC) and Director of the Centre for Computational Social Science. Her research focuses on computational methods applied to social movements, gender studies, and text analysis. She holds a PhD and MA from the University of California, Berkeley, and a BA from the University of Wisconsin, Madison. **Education**: PhD in Sociology, University of California, Berkeley MA in Sociology, University of California, Berkeley BA in Sociology (Analysis and Research), University of Wisconsin, Madison Her work bridges sociology and computational methods, examining topics like institutional equity (e.g., NSF ADVANCE), gender disparities in academia, and the use of AI in qualitative research. She has published extensively in journals like *American Journal of Sociology* and serves on editorial boards of *Poetics* and *Acta Sociologica*. Her recent projects include analyzing gender bias in evaluations and leveraging machine learning for feminist social science. **Grants & Advising**: Her postdoctoral work at UC Berkeley and Northwestern University focused on data science and interdisciplinary collaboration. She advises on AI ethics and computational grounded theory, and her teaching includes courses on computational methods in the social sciences. **Affiliations**: She is elected council member for the American Sociological Association’s sections on Sociology of Culture and Mathematical Sociology. She also contributes to initiatives like the *Society-Centered AI* program at Duke University.

Bronson Huiمشاهده پروفایل

استادیار

• Second Language Acquisition
• Applied Psycholinguistics
• Vocabulary Learning and Teaching
• +۴ مورد دیگر

Bronson Hui is an Assistant Professor of Second Language Acquisition at the University of Maryland, College Park, within the School of Languages, Literatures, and Cultures (SLLC). He is also a member of the Maryland Language Science Center. His research focuses on applied psycholinguistics, particularly second language acquisition in instructed contexts, multi-modal input, vocabulary learning, and open science practices. Hui holds a Ph.D. in Second Language Studies from Michigan State University, an M.S. in Applied Linguistics from the University of Oxford, and dual B.A./B.Ed. degrees in English Language and Education from the University of Hong Kong. Education: Ph.D., Second Language Studies, Michigan State University M.S., Applied Linguistics and Second Language Acquisition, University of Oxford B.A. & B.Ed., English Language and Linguistics / Language Education, University of Hong Kong His research interests include experimental methods in SLA, quantitative analysis, and the use of AI tools in meta-research. He has published in journals like Studies in Second Language Acquisition , Language Learning , and Applied Psycholinguistics . Hui serves on the editorial boards of TESOL Quarterly and Studies in Second Language Acquisition . He teaches courses such as Second Language Research Methodologies , Psycholinguistics , and Vocabulary Acquisition in Instructional Contexts . Hui actively advises graduate students in empirical studies, dissertation research, and grant proposals. His work emphasizes open science practices, including pre-registration, data sharing, and reproducible analyses. Hui has developed workshops on R programming for applied linguists, emphasizing ethical data practices and open-source tools. He collaborates internationally on projects like the ASReview tutorial for meta-research and has contributed to book projects on quantitative methods in applied linguistics.

Ala Alrababahمشاهده پروفایل

استادیار

• Immigration Studies
• Political Violence
• Refugee Politics
• +۳ مورد دیگر

Dr. Ala Alrababah is an Assistant Professor in the Department of Social and Political Sciences at Bocconi University, with affiliations including the Evidence in Governance and Politics (EGAP) network, Immigration Policy Lab (IPL) at ETH Zurich and Stanford, BAFFI Center on Economics, Finance and Regulation at Bocconi, and the Abdul Latif Jameel Poverty Action Lab (J-PAL). She holds a Ph.D. in Political Science from Stanford University (2021). Her research examines immigration, refugees, and political violence using innovative mixed-methods approaches combining fieldwork with experimental and computational techniques. Primary domains include comparative analysis of migration policies, conflict dynamics in the Middle East, prejudice reduction strategies, and quantitative analysis of political discourse. She maintains active field research programs focused on Syrian refugee communities. Publications demonstrate consistent focus on migration policy impacts, refugee decision-making, and political violence analysis across multiple contexts. Computational methods feature prominently alongside field experiments, with strong methodological contributions to survey research and text analysis. As an active member of international research networks, Dr. Alrababah collaborates on large-scale projects examining refugee integration policies, transitional justice mechanisms, and political behavior in conflict regions. Her work has received international media coverage in outlets including The Economist, Foreign Policy, and BBC Arabic.

• Digital Humanities
• Early Modern Literature
• Corpus Linguistics
• +۴ مورد دیگر

Heather Froehlich is an Assistant Specialist in Research Engagement at the University of Arizona Libraries, specializing in digital humanities and corpus linguistics. She holds affiliations with Literature Faculty, English Applied Linguistics, and RCTE (Research, Creation, and Teaching Excellence). Her work bridges traditional literary studies with modern computational methods, focusing on early modern texts, Shakespearean drama, and gender representation. Her research interests include quantitative literary analysis, corpus-based studies using tools like AntConc, and the integration of digital methods into pedagogy. Notable projects involve analyzing Aphra Behn’s works, transcribing recipe manuscripts, and exploring nuclear physics discourse through text corpora. Publications span topics from early modern drama’s social structures to postdoctoral labor advocacy. She actively promotes research data management and collaborates on interdisciplinary projects such as the Early English Books Online review and the Philosophical Magazine Nuclear Physics Corpus . Her contributions include advancing digital humanities pedagogy through EEBO-TCP integration in teaching and advocating for equitable academic labor practices via the Postdoctoral Laborers Bill of Rights .

Dave Clarkeمشاهده پروفایل

استاد مدعو

• Quantitative Exercise Biology
• Exercise Physiology
• Sports Analytics
• +۳ مورد دیگر

Dr. Dave Clarke is an Adjunct Professor in the Department of Biomedical Physiology and Kinesiology at Simon Fraser University, leading the Clarke Laboratory for Quantitative Exercise Biology . His research focuses on Exercise-responsive cell signaling , Sports analytics using wearable sensors , Evidence-based exercise programming , and Clinical exercise physiology . The lab integrates mathematical modeling, clinical insights, and biomechanical approaches to address questions in athletic performance, metabolic disorders, and wearable technology applications. Dr. Clarke collaborates with institutions such as TRIUMF and the BC Cancer Research Centre. Publications highlight his work in critical power modeling , AMP-activated protein kinase dynamics , and mitochondrial disease treatments . His lab emphasizes interdisciplinary training, offering mentorship in experimental design, data analysis, and translational research. The Clarke Lab is affiliated with SFU’s Faculty of Health Sciences and maintains active outreach programs for public health education. Notable projects include developing hydraulic models for recovery kinetics prediction and validating chloride test strips for sodium excretion analysis. The lab’s work has been featured in journals like Frontiers in Sports and Active Living and Orphanet Journal of Rare Diseases . For real-time updates, follow the lab on Facebook .

Fulai Jinمشاهده پروفایل

دانشیار

• 3D Genome Architecture
• Computational Biology
• Genomics
• +۳ مورد دیگر

Fulai Jin, PhD, is an Associate Professor in the Department of Genetics and Genome Sciences at Case Western Reserve University School of Medicine, with joint appointments in the Department of Population and Quantitative Health Sciences and the Department of Computer and Data Sciences. He is also Co-Leader of the Cancer Genomics and Epigenomics Program at the Case Comprehensive Cancer Center. Dr. Jin holds a PhD in Molecular and Medical Pharmacology from UCLA and bachelor’s degrees in Biology and Computer Science from USTC. His postdoctoral training at the Ludwig Institute for Cancer Research focused on genomics and epigenetics. His research focuses on 3D genome architecture, computational tools for genomic data integration, and single-cell technologies applied to health and disease. Key areas include cancer, diabetes, and neurological disorders, with a focus on chromatin structure, enhancer function, and ancestry-related disease mechanisms. His lab develops low-input 3D genome mapping methods and employs CRISPR tools, scRNA-seq, and multi-omic integration. Research is funded by NIH grants. Dr. Jin seeks motivated students/postdocs with experimental or computational expertise. The lab’s work is detailed on their website, and publications are listed on PubMed.

Scott Morrisمشاهده پروفایل

استاد

• Industrial-Organizational Psychology
• Personnel Selection
• Bias and Discrimination in Employment
• +۴ مورد دیگر

Scott Morris is a Professor and Nambury S. Raju Endowed Chair in Psychology at Illinois Institute of Technology (IIT), leading the Industrial/Organizational Psychology Program within the Lewis College of Science and Letters. He holds a Ph.D. from the University of Akron (1994) and a B.A. from the University of Northern Iowa (1987). A Fellow of the Society for Industrial and Organizational Psychology and the American Psychological Association, Morris is also an associate editor for the Journal of Applied Psychology . His research focuses on advanced statistical methods in personnel selection systems, including meta-analysis, adverse impact analysis, and computer adaptive testing. He explores bias in subjective hiring practices and develops psychometric models to ensure fairness in employment decisions. Morris’s work bridges quantitative methodology with real-world applications, emphasizing ethical and equitable employment practices. Key research areas include adverse impact measurement, meta-analytic techniques, differential item functioning, and the design of efficient testing systems. He co-authored Adverse Impact Analysis: Understanding Data, Statistics and Risk (2017), a foundational text in the field. Morris’s lab, the Personnel Selection & Analytics Lab , investigates topics like multidimensional adaptive testing and statistical methodologies for EEO compliance. Awards: Fellowships from SIOP and APA, recognition for contributions to organizational psychology and statistical rigor. Media Expertise: Regularly consulted on psychology, data science, and ethics in employment. Labs/Teams: Leads the IIT Personnel Selection & Analytics Lab, focusing on quantitative methods in HR and equity analysis.

Giovanni Forchiniمشاهده پروفایل

استاد

• Econometrics
• Panel Data Analysis
• Health Economics
• +۳ مورد دیگر

Giovanni Forchini is a Professor at the Umeå School of Business, Economics and Statistics (USBE), Umeå University, Sweden. His research focuses on econometrics, panel data analysis, and their applications in health economics and epidemiological modeling. He holds the title of Docent, a Swedish academic qualification reflecting advanced expertise. His work bridges theoretical econometrics with practical policy analysis, particularly in pandemic preparedness and healthcare optimization. Research Themes: Econometric methodologies for panel data and structural equation models Quantifying pandemic impacts on healthcare systems and economies Optimization of resource allocation during public health crises Key Contributions: Developed the DAEDALUS model for integrated economic-epidemiological policy simulations Analyzed SARS-CoV-2 transmission dynamics and vaccine impact in multiple countries Pioneered statistical methods for handling multifactor structures in panel data Awards & Grants: USBSE Pedagogical Prize 2020 Funding from Forte (Swedish Research Council for Health, Working Life and Welfare) and Handelsbanken Teaching & Mentorship: Coordinates Master’s theses in Economics at USBSE Teaches advanced courses like Econometrics 1 & 2 and Analysis of Financial Data

• Biostatistics
• Public Health
• Data Science
• +۳ مورد دیگر

Yuki Ohnishi is a Research Fellow in the Department of Biostatistics at the Yale School of Public Health. Their work focuses on data science and equity in public health, leveraging advanced statistical methods to address complex health challenges. Contact: yuki.ohnishi@yale.edu . While specific research interests are not explicitly detailed in available records, their affiliation with the Department of Biostatistics suggests expertise in areas such as computational epidemiology, health data analysis, and quantitative public health methodologies.

• Human Genetics
• Health Sciences
• Genomics
• +۵ مورد دیگر

Mads Kaern is an Associate Professor in the Department of Cellular and Molecular Medicine, specializing in synthetic biology, gene regulation, and systems biology. His research integrates computational modeling with experimental approaches to understand cellular processes and design genetic circuits for biomedical applications. Key areas of focus include epistasis analysis, gene expression variability, and the development of educational programs in BIOSTEM. Research interests span molecular mechanisms of gene regulation, synthetic biology applications, and quantitative analysis of genetic interactions. His work emphasizes interdisciplinary methods combining genomics, bioinformatics, and engineering principles to address complex biological questions. Publications highlight contributions to understanding cellular heterogeneity, improving DNA assembly techniques, and advancing therapeutic strategies through synthetic biology. Educational efforts include initiatives like iGEM-inspired programs to enhance undergraduate research and skill development in biotechnology.

• Generalization in deep learning
• Sparse estimation
• Portfolio optimization using reinforcement learning
• +۶ مورد دیگر

LIU Peng is an Assistant Professor of Quantitative Finance (Practice) at the Lee Kong Chian School of Business, Singapore Management University. He holds a Ph.D. in Statistics and Data Science (Part-time) from the National University of Singapore (2021), an M.S. in Business Analytics (2015), and a B.Eng. in Electronic Science and Technology (2012). Prior to his academic role, he worked as a Manager at Standard Chartered Bank (2019–2022) and in analytics roles at Marina Bay Sands and IBM. Education: Ph.D. (NUS), M.S. (NUS), B.Eng. (Beijing Technology and Business University) His research focuses on generalization in deep learning, sparse estimation, portfolio optimization via reinforcement learning, financial text mining, risk management, and Bayesian optimization. His work bridges theoretical advancements with practical applications in quantitative finance and data science. Notable contributions include studies on explainable neural networks, Bayesian optimization frameworks for portfolio management, and risk analytics integrating human decision-making. His recent articles emphasize model risk assessment, cost-aware optimization, and financial data analysis. Awards: Best Ph.D. Graduate Research Award (NUS, 2020), Google TensorFlow Developer Certificate (2020–2023) He teaches courses in quantitative finance, machine learning, and risk management, and has secured grants including the Research Capability Building Fund (2023–2025). His research aligns with strategic priorities in digital transformation and financial innovation.

John T. Gasperمشاهده پروفایل

دانشگاهی

• Political Economy
• Game Theory
• Decision Sciences
• +۶ مورد دیگر

John T. Gasper is an Associate Teaching Professor of Economics and former Assistant Dean of Strategic Initiatives at Carnegie Mellon University’s Tepper School of Business. His work bridges political economy, game theory, and quantitative analysis. Research focuses on U.S. disaster relief accountability , examining how electoral outcomes respond to natural disasters and governmental aid decisions. He also investigates media bias origins through market models and formal theory. Notable projects include analyses of gubernatorial-presidential dynamics in disaster declarations and ideological shifts in media outlet positioning. Teaching spans economics, data science, decision analysis, and agent-based modeling. Courses include Principles of Game Theory for Business and Empirical Research Methods at both undergraduate and executive education levels. Current research includes work on investigative journalism economics (under review) and computational models of political protests. Active collaborations with Andrew Reeves and Cristina Bicchieri address electoral strategies and protest dynamics.

• Statistics
• High-Dimensional Data Analysis
• Statistical Genetics
• +۷ مورد دیگر

Aaron J Molstad is an Assistant Professor in the Department of Statistics at the University of Minnesota – Twin Cities, within the College of Science and Engineering. His research lies at the intersection of statistical methodology and genomic data science, with a focus on developing rigorous and scalable methods for modern high-dimensional datasets. His research interests include high-dimensional statistics, covariance and precision matrix estimation, regression modeling with structured responses, variable selection, and integrative analysis of omics data. He develops methods tailored for compositional data, multivariate responses, and ancestry-specific genetic association studies, contributing to both theoretical statistics and public health applications. The recent publications and funded projects highlight a strong trend in developing objective, reliable, and heterogeneous-aware statistical frameworks for genomics and biomedicine. His work emphasizes methodological innovation with direct applicability to complex biological data, particularly in diverse populations and multi-omics integration. Awarded grants from the National Science Foundation and the National Institutes of Health demonstrate recognition of his research’s significance and impact. These include projects on inference from omics data, new regression models for categorical responses, and integrative genomics in African American populations. Objective and reliable methods for inference from modern omics data (NSF, 2024–2027) Collaborative Research: New Regression Models for Multiple Categorical Responses (NSF, 2024–2025) Integrative Genomics into Genetic Association Studies of Blood Pressure and Stroke in African Americans (NIH/Fred Hutchinson, 2023–2024) Dr. Molstad advises and collaborates on major genomic studies involving protein expression, blood pressure, stroke, and ancestry-specific effects. While specific PhD students are not listed, his role as Principal Investigator on multiple grants indicates mentorship of graduate researchers and postdoctoral scholars. He is also active in the broader statistical community, with publications in top-tier journals such as Biometrika , Biometrics , and Genome Biology .

• Chiral Recognition
• Enantiomeric Separations
• Ionic Liquids
• +۵ مورد دیگر

Daniel W Armstrong is a Professor at the University of Texas at Arlington in the Department of Chemistry and Biochemistry. With over 35 years of experience, he is a pioneering figure in chiral recognition, enantiomeric separations, and the biological relevance of D-amino acids. His work has led to over 740 publications, 35 patents, and 560 invited seminars worldwide. Developed first chiral recognition mechanism by cyclodextrins First to use macrocyclic antibiotics as chiral selectors Synthesized most new ionic liquids (ILs) globally Created ultra-fast separation techniques now standard in analytical chemistry Contributed to FDA 1992 guidelines on chiral drug separation His research focuses on chiral separations, ionic liquids, and the role of D-amino acids in biological systems. He has commercialized over 30 HPLC and GC columns, transforming analytical chemistry and pharmaceutical analysis. Recent publications demonstrate continued innovation in chiral chromatography, biomarker analysis, and AI-driven separation optimization. His grants include industry collaborations with Merck, Alcon, and Sigma-Aldrich, emphasizing practical applications of his work. Scientific honors include multiple lifetime achievement awards, fellowships in the Royal Society of Chemistry and American Chemical Society, the Chirality Medal, and induction into the National Academy of Inventors. He has mentored over 100 PhD students, many from first-generation college backgrounds.