جستجوی استاد راهنمای دانشگاهی

Charles Rahalمشاهده پروفایل

دانشیار

• Social Science Methodology
• Applied Social Data Science
• High-dimensional Econometrics
• +۸ مورد دیگر

Charles Rahal is an Associate Professor in Data Science and Informatics at the University of Oxford, with additional affiliations as an Associate Member of Nuffield College and Researcher at the Gradel Institute, New College. He serves as a Co-Investigator at the ESRC Centre for Care and sits on the Steering Group of Reproducible Research Oxford. His academic career includes previous roles as a Senior Departmental Research Lecturer at the Leverhulme Centre for Demographic Science and a British Academy Postdoctoral Fellow. Dr. Rahal completed his PhD in 2016 and has established himself as a prominent social science methodologist and applied social data scientist with expertise in high-dimensional econometrics. His research spans multiple domains, focusing particularly on unique Big Data origination processes and their relationship to social inequality, mobility, and stratification. He is deeply engaged in machine learning methods, civic technology, spatial and time series econometrics, model uncertainty, and scientometrics. His recent publications reveal a strong trend toward computational social science, with significant contributions to understanding prediction limits, pandemic impacts, healthcare systems, and environmental sustainability. The articles demonstrate his interdisciplinary approach, bridging traditional social science with cutting-edge computational methods, particularly in the analysis of large-scale datasets and development of novel metrics like the InterModel Vigorish for model comparison. Dr. Rahal is actively involved in teaching and mentoring, co-convening courses in Demographic Analysis, Life Course Research, and the Oxford Partner site of the Summer Institute in Computational Social Sciences. He has developed workshops on machine learning, command line interfaces, and LaTeX, reflecting his commitment to methodological training in social science. He leads the Metrics and Models lab and maintains several open-source projects including the GWAS Diversity Monitor and RobustiPy. His editorial roles include Associate Editor-in-Chief at the Journal of Social Computing and Associate Editor at ACM Transactions on Social Computing, highlighting his influence in shaping computational social science methodology.

Song Kimمشاهده پروفایل

دانشیار

• International Political Economy
• Formal and Quantitative Methodology
• Big Data Analysis
• +۵ مورد دیگر

Song Kim is an Associate Professor of Political Science at the Massachusetts Institute of Technology (MIT) and a Faculty Affiliate at the Institute for Data, Systems, and Society (IDSS). He holds a Ph.D. in Politics from Princeton University, where he was awarded the Harold W. Dodds Fellowship (2012-2013). His research focuses on International Political Economy, Formal and Quantitative Methodology, and Big Data analysis of international trade. He is particularly known for his work on firm-level political incentives in trade liberalization, which earned him the 2015 Mancur Olson Award and the 2018 Michael Wallerstein Award for best published article in political economy. Kim develops computational methods for analyzing trade data, including dimension reduction and visualization techniques. He maintains two key databases: LobbyView (tracking firm lobbying efforts) and TradeLab (for trade policy analysis). His research has been published in top journals such as the American Political Science Review, American Journal of Political Science, and International Organization. Educations : Ph.D. in Politics (Princeton University), B.A. not explicitly stated. His research interests include the dynamical evolution of lobbying networks, strategic links between political donations and lobbying, and the political origins of trade regulations. He also contributes methodological innovations, such as two-way fixed effects models and matching methods for causal inference with panel data. Awards : Mancur Olson Award (2015) Michael Wallerstein Award (2018) Harold W. Dodds Fellowship (2012-2013) Advising & Grants : No listed advisees. His work is supported by MIT’s IDSS and institutional funding. He collaborates on software tools like the 'wfe' and 'concordance' R packages, advancing computational social science. Labs/Teams : Associated with MIT’s Political Science Department and IDSS, focusing on interdisciplinary projects in trade, lobbying, and quantitative methods.

Alex Liuمشاهده پروفایل

پژوهشگر

• Paleobiology
• Early Animal Evolution
• Ediacaran Biota
• +۸ مورد دیگر

Alex Liu is a Researcher at the Department of Earth Sciences within the University of Cambridge. He specializes in palaeobiology , focusing on the origin and early evolution of animals, particularly the Ediacaran biota (~579–539 million years ago), and their co-evolution with Earth's environment. Research Focus: Refines understanding of animal body plan evolution, taphonomy, sedimentology, and macroevolutionary trends. Methodologies: Combines fieldwork, experimental studies, petrology, phylogenetics, and big-data analyses. Collaborations: Works with international museums and research teams on fossil sites in Namibia, Canada, and Brazil. Additional Interests: Explores meiofaunal evolution, paleogeography, paleoclimate, and conservation paleobiology. He supervises Cambridge NERC Doctoral Landscape Awards (DLA) projects and welcomes student contributions to taxonomic, paleoecological, and analytical studies.

• Accounting History
• Business History
• Accounting Education
• +۷ مورد دیگر

Professor Alan Sangster is Chair in Accounting History at the University of Aberdeen's Business School, where he is actively engaged in research, teaching, and supervision of PhD students. His work centers on the historical evolution of accounting systems, particularly double-entry bookkeeping, and the pedagogical aspects of accounting education. University: University of Aberdeen School: Business School Position: Chair in Accounting History Email: alan.sangster@abdn.ac.uk Alan Sangster holds a BA in Business Studies, MSc in Operational Research, PhD in Accounting Education, and is a Chartered Accountant (CA). His academic journey reflects a deep commitment to understanding the historical roots of modern accounting practices. His research interests encompass Accounting History , Business History , and Accounting Education , with a focus on medieval and Renaissance accounting systems, the work of Luca Pacioli, digital methodologies in historical research, and ethical issues in accounting scholarship. He advocates for rigorous historical methodology and critical reassessment of established narratives. The 15 most recent publications highlight a sustained and influential research trajectory in accounting history, with a strong emphasis on the origins and diffusion of double-entry bookkeeping, digital transformation of archival research, and critical reflections on historiography. His work bridges historical analysis with contemporary pedagogical and ethical concerns in accounting. Professor Sangster has received numerous accolades recognizing his exceptional contributions: 2022: Outstanding Accounting Educator Award (American Accounting Association) 2022: Outstanding Contribution to Accounting & Finance Education Award (British Accounting & Finance Association) 2021: Barbara D. Merino Award for Excellence in Accounting History Publication 2015: Hourglass Award (Academy of Accounting Historians) 2014: Premio Enrique Fernández Peña de Historia de la Contabilidad 2013: Life-Time Achievement Award (British Accounting and Finance Association) He serves as Editor-in-Chief of Accounting Education (Routledge), Deputy Chair of the BAFA Accounting History SIG, and Trustee of The Academy of Accounting Historians. These roles underscore his leadership and influence in shaping the field globally. Although no specific students or grants are mentioned, his active supervision of PhDs and extensive publication record indicate a vibrant research program. He is not associated with any lab or team in the provided text, but his collaborative publications suggest active academic networks.

Matt Nowinskiمشاهده پروفایل

دانشیار

• Aerospace Engineering
• Asteroid Dynamics
• Machine Learning
• +۵ مورد دیگر

Matt Nowinski is a Collegiate Associate Professor in the Department of Mechanical Engineering at Virginia Tech's College of Engineering. His professional roles include advisory board memberships and leadership positions within the department. He holds multiple degrees including a Ph.D. in Mechanical Engineering from ETH Zurich (1999), an M.S. in Computer Science from Syracuse University (2022), and prior mechanical/aerospace engineering degrees from Virginia Tech. His research focuses on asteroid dynamics (particularly D-type and V-type asteroids), gas turbine engines, aeroelasticity, and education technology. Notable areas include lightcurve analysis, surface mineralogy modeling, and machine learning applications in astronomy. His work bridges aerospace engineering with astrophysics, leveraging both experimental and computational methods. Dr. Nowinski has over 24 years of industry experience as a Boeing subject matter expert in military communications systems, complemented by academic roles at George Mason University and University of Chicago. He is a recipient of the John Jones Faculty Fellowship and Society of Distinguished Alumni honor. His research contributions span asteroid characterization, turbine blade flutter mechanisms, and telescope instrumentation. Current work emphasizes observational astronomy through the Stone Edge Observatory and Slack-based collaborative platforms. He actively contributes to advancing STEM education through innovative curricula and research integration.

Paul Wiegertمشاهده پروفایل

استاد

• Planetary Science
• Astronomy
• Celestial Mechanics
• +۶ مورد دیگر

Paul Wiegert is a Full Professor in the Department of Physics and Astronomy at the University of Western Ontario , where he has been since 1996 after positions at York University and Queen's University. He is a member of the Institute for Earth and Space Exploration (IESX) and the Centre for Planetary Science and Exploration (CPSX) . His research spans asteroid dynamics , exoplanet systems , and celestial mechanics , with notable work on Earth co-orbital asteroids like (3753) Cruithne and Earth's first Trojan asteroid 2010 TK7. Education : PhD in Astronomy (University of Toronto, 1996) Research Domains : Planetary Science, Astronomy, Big Data Analytics His recent publications focus on interstellar transport mechanisms , asteroid impact risks , and exomoon detection . Key findings include quantifying risks from asteroid 2024 YR4's potential lunar impact and demonstrating the feasibility of detecting alpha Centauri-origin material in our solar system. He actively supervises graduate students like Cole Gregg and participates in NSERC-funded summer research programs for undergraduates. For planetary defense, he has analyzed collision probabilities for Apophis and developed meteoroid hazard models for spacecraft. His work appears in Planetary Science Journal , Nature Astronomy , and Astrophysical Journal Letters , with media coverage in 60+ outlets and 126 X (Twitter) mentions .

Orazio Giancolaمشاهده پروفایل

دانشیار

• Social Research Methodology
• Data Analysis
• Sociology of Education
• +۵ مورد دیگر

Orazio Giancola is Associate Professor at the Department of Social and Economic Sciences, Sapienza University of Rome. His research focuses on social research methodologies, educational inequality analysis, and policy evaluation in Italian and comparative contexts. He teaches courses such as Applied Social Research Methodology , Research Methods for Social Policies , and data analysis techniques. Research Interests : Sociology of education, social stratification, big data analytics, educational equity, tertiary education access, and policy evaluation. Key Projects : School experiences and educational choices in the post-pandemic landscape (Rome high school survey). His recent publications examine educational poverty , digital technology disparities , and policy impacts in Italy and Europe. Articles employ multivariate analysis and logistic modeling to explore structural inequalities. No scientific awards are currently documented.

Daniel M. Smithمشاهده پروفایل

دانشیار

• Comparative Politics
• Political Economy
• Political Behavior
• +۷ مورد دیگر

Daniel M. Smith is an Associate Professor in the Department of Political Science at the University of Pennsylvania, School of Arts & Sciences. He holds a PhD from the University of California, San Diego, and has held academic positions at Harvard University, Columbia University, and Stanford University. His research focuses on comparative politics, political economy, and political behavior, with regional expertise in Japan and Western Europe. PhD, Political Science, University of California, San Diego (2012) MA, Political Science, University of California, San Diego (2009) BA, Political Science and Italian, University of California, Los Angeles (2005) His research centers on political institutions, democratic representation, electoral systems, and political dynasties. He is the author of the acclaimed book Dynasties and Democracy (Stanford University Press, 2018), which explores the persistence of political families in democracies, particularly in Japan. His work also investigates voter behavior, gender and age in politics, distributive politics, and legislative accountability. His recent publications in top journals such as the American Political Science Review , American Journal of Political Science , and The Journal of Politics reflect a strong trend toward mixed-methods research, combining large-scale data analysis with experimental designs. His work frequently employs conjoint experiments, natural experiments, and administrative data to study political behavior and institutional effects. Winner of the 2023 Lawrence Longley Award (APSA) Winner of the 2022 Kenneth A. Shepsle Prize Honorable mention for the 2024 APSA Best Paper Award Smith has advised numerous graduate students and co-organizes the Japanese Politics Online Seminar Series (JPOSS). He has also co-edited multiple volumes in the Japan Decides series, analyzing Japanese general elections. He teaches courses on electoral rules, representation, and Japanese politics at both undergraduate and graduate levels. His research is supported by active collaborations with scholars across the U.S. and Japan, and he maintains a robust pipeline of working papers on topics such as coalition dynamics, gender bias, and constituency-building.

Sean Ehlmanمشاهده پروفایل

استادیار

• Evolutionary Behavioral Ecology
• Phenotypic Plasticity
• Behavioral Individuality
• +۳ مورد دیگر

Sean Ehlman is an Assistant Professor in the Department of Biological Sciences at the University of South Carolina's McCausland College of Arts and Sciences. He leads the Ehlman Lab, which focuses on evolutionary behavioral ecology using integrated lab, field, and theoretical approaches. His research examines how ecological and evolutionary processes shape animal behavior development, with specific interests in: Phenotypic plasticity in response to environmental changes Origins and maintenance of behavioral individuality Aquatic ecosystem dynamics using Poeciliid fish models Application of tracking technology and AI in behavioral mapping Recent publications (2023-2024) demonstrate his interdisciplinary approach, combining behavioral ecology with data science to study: Developmental impacts of predator exposure Reproductive individuality in controlled environments Genotype-phenotype relationships in evolution Big data applications in behavioral research

Kate Laskowskiمشاهده پروفایل

دانشیار

• Behavioral Ecology
• Evolutionary Biology
• Animal Behavior
• +۴ مورد دیگر

Kate Laskowski is an Associate Professor in the Department of Evolution and Ecology at University of California, Davis , focusing on behavioral diversity and plasticity. Her research explores how evolutionary processes shape developmental mechanisms generating individual variation. Education: B.S. in Biological Sciences (2006, UMBC), Ph.D. in Integrative Biology (2013, University of Illinois) Her work integrates ultimate and proximate perspectives to analyze how genetic, parental, and experiential cues build phenotypes. Recent research emphasizes clonal fish models to study non-genetic origins of behavior, eco-evolutionary dynamics, and collective behavior across scales. Publications from 2023-2025 highlight themes in behavioral repeatability , predation risk responses , genetic life-history trade-offs , and social conformity vs. individuality . Her methods combine experimental studies with statistical modeling and meta-analytic frameworks. Scientific Awards: Sloan Fellow (2023) Kate collaborates with the Center for Population Biology and advises in the Animal Behavior and Population Biology graduate programs. Her lab investigates behavioral individuality in clonal systems, with applications to conservation and evolutionary theory.

G. Scott Watsonمشاهده پروفایل

استاد

• Early Universe Cosmology
• Inflation
• Dark Matter
• +۳ مورد دیگر

Prof. G. Scott Watson is a Professor in the Department of Physics at Syracuse University, affiliated with the College of Arts & Sciences. His research focuses on the interplay between fundamental particle physics and cosmology, particularly early universe cosmology, inflationary models, dark matter/energy, and string theory applications. He holds a Ph.D. in Physics from Brown University (2005) and B.S. degrees in Mathematics and Physics from the University of North Carolina at Wilmington (2000). Key research interests include string phenomenology as a quantum gravity framework, probing inflationary scenarios through cosmic microwave background (CMB) studies, and exploring dark matter origins. He leads major projects like CMB-S4 and contributes to the CMBPol mission concept. Watson has received the American Physical Society Outstanding Referee Award (2021) and serves on high-profile collaborations such as the Inflation Probe Study Analysis Group (IPSAG). Teaching responsibilities include advanced courses like Quantum Field Theory, Relativity and Cosmology, and Quantum Mechanics II. He actively mentors students through independent studies and advises on graduate admissions. Watson has secured significant grants, including a Department of Energy-funded project on theoretical particle physics and cosmology (2013–2025) and NSF support for cosmic acceleration research (2018–2023).

Elvin Wylyمشاهده پروفایل

استاد

• Urban Geography
• Housing Policy and Finance
• Gentrification and Displacement
• +۷ مورد دیگر

Elvin Wyly is a Professor in the Department of Geography within the Faculty of Arts at the University of British Columbia. His research focuses on the relations between market processes and state policy in producing and reinforcing urban social inequalities, blending critical social theory, legal and policy analysis, and multivariate quantitative methods. Wyly earned his PhD (1995) and MA from the University of Minnesota, Minneapolis, and his BSc from The Pennsylvania State University. His academic journey reflects a deep engagement with geographical thought and methodology. His research interests span urban geography, housing policy and finance, gentrification and displacement, urban inequality, spatial analysis, critical social theory, digital geographies, GIS, and race, class, and gender studies. Wyly's approach combines critical theory with empirical analysis to examine how market forces and public policy interact to create spatial inequalities in urban environments. Analysis of Wyly's recent publications (2019-2024) reveals consistent engagement with themes of urban transformation, housing finance, and spatial inequality. His work increasingly addresses the digital turn in urban studies, examining smart cities, datafication of urban space, and the evolving nature of gentrification in the 21st century. There's a clear trajectory from studying traditional urban processes toward examining how digital technologies reshape urban inequalities and governance. Wyly's research demonstrates significant contributions to understanding the financialization of urban space, particularly through his work on subprime mortgage markets, housing discrimination, and the racial dimensions of urban development. His publications in leading geography and urban studies journals establish him as a significant voice in critical urban scholarship. His teaching appears to focus on urban geography, with courses covering topics related to cities, economies, transnational flows, digital geographies, and issues of gender, race, and class. His research website serves as a resource for students and colleagues interested in advanced urban geographical analysis.

André Laplumeمشاهده پروفایل

استاد

• Strategy
• Entrepreneurship
• Innovation Management
• +۵ مورد دیگر

Dr. André Laplume is a Professor in the Entrepreneurship & Strategy Department at the Ted Rogers School of Management, Toronto Metropolitan University. He holds a PhD, MBA, and BCS in addition to extensive industry experience in IT consulting and entrepreneurship. His research focuses on strategic innovation, spinout ventures, and entrepreneurial ecosystems, with a notable 2024 book on spinout transitions. He has served as Director of Research-Based Graduate Programs at the Yeates School of Graduate Studies (2019–2024) and Interim Director of the Entrepreneurship Research Institute (2024–2025). Dr. Laplume’s teaching portfolio includes courses on strategic management, intrapreneurship, and innovation at both undergraduate and graduate levels. His research has been featured in top journals such as Journal of Business Venturing Insights and Journal of Management , with a focus on spinouts, entrepreneurial barriers, and stakeholder dynamics. He actively mentors graduate students in Management, Data Science, and related disciplines. Professional contributions include co-founding LaunchScore.com, a data-driven startup recommendation tool, and over 14 peer-reviewed articles addressing topics like restrictive covenant enforcement, startup diversity, and agile innovation frameworks. His work bridges academic theory with practical applications in corporate innovation and entrepreneurial ecosystems.

• Algorithms for Big Data Analytics
• Computational Geometry
• Machine Learning
• +۴ مورد دیگر

Jeff M Phillips is a Professor in the Kahlert School of Computing at the University of Utah, specializing in algorithms for big data analytics, computational geometry, and machine learning. He holds a BS in Computer Science and Mathematics from Rice University (2003) and a PhD in Computer Science from Duke University (2009). He serves as Director of the Utah Center for Data Science, Director of the Data Science Program in the Kahlert School of Computing, and Faculty Co-Director of the One U Data Science Hub. His research focuses on geometric data analysis, coresets, sketches, and handling uncertainty in data. Education: BS/BA (Rice University, 2003), PhD (Duke University, 2009) CI Postdoctoral Fellow at University of Utah (2009–2011) His research interests include algorithms for big data analytics, computational geometry, machine learning, spatial statistics, and AI. He has led NSF-funded projects on spatial data analysis, cosmic origins via AI, and reactive flow data modeling. Phillips has advised numerous PhD and master’s students, contributing to topics like trajectory classification and bias mitigation in word embeddings. His publications span computational geometry, data science, and machine learning. Notable work includes coresets for kernel density estimates, bias mitigation in language models, and scalable spatial scan statistics. Phillips is also active in academic service, serving as co-PC chair for SoCG 2024 and on program committees for major conferences like NeurIPS and ICML.

• Computational Social Science
• Social Computing
• Information Systems
• +۱۲ مورد دیگر

Bjorn Ross is a Lecturer in Computational Social Science at the School of Informatics, University of Edinburgh. He is affiliated with the Institute for Language, Cognition and Computation and actively contributes to the Computational Social Science research area. He serves as Director of the SMASH research group and is part of the management team for the Centre for Doctoral Training in Natural Language Processing (CDT in NLP). Education: PhD, 2019, University of Duisburg-Essen MSc in Computer Science, 2016, University of Münster Exchange year, 2014–2015, University of Strasbourg BSc in Information Systems, 2013, University of Münster His research focuses on computational methods for analyzing social media, particularly using natural language processing, social network analysis, and agent-based modeling. Key interests include misinformation, hate speech, social bots, and the ethical implications of automated systems. He emphasizes fairness, bias, and data ethics in AI applications. His recent publications span topics such as queerphobic bias in sentiment analysis, explainable hate speech detection, temporal generalizability in misinformation models, and cross-lingual bias amplification. These works appear in leading venues including ACL, ICWSM, Social Science Computer Review, and Big Data & Society, reflecting a strong interdisciplinary focus bridging computer science, social science, and ethics. Scientific Awards: Best Paper Award, Electronic Government track, HICSS 2018 Ross supervises multiple PhD students and welcomes new applicants. He has also contributed to software tools and web-based platforms for argument analysis and counterspeech. He is an Associate Editor for Business & Information Systems Engineering and a member of AIS, ACL, and ACM. His teaching includes courses on Text Technologies for Data Science and digital persuasion. He leads the SMASH group, which focuses on social media analytics and societal challenges, and collaborates extensively within the CDT in NLP and the Institute for Language, Cognition and Computation.