جستجوی استاد راهنمای دانشگاهی

Joshua D. Angristمشاهده پروفایل

استاد

• Econometrics
• Labor Economics
• Causal Inference
• +۳ مورد دیگر

Joshua D. Angrist is the Ford Professor of Economics at the Massachusetts Institute of Technology, where he has been a faculty member since 1996. He is also a co-founder and director of MIT's Blueprint Labs and a Research Associate at the National Bureau of Economic Research. Angrist shares the 2021 Nobel Prize in Economic Sciences with David Card and Guido Imbens for their methodological contributions to the analysis of causal relationships. Angrist received his B.A. from Oberlin College in 1982 and completed his Ph.D. in Economics at Princeton University in 1989. Prior to joining MIT, he taught at Harvard University and the Hebrew University of Jerusalem. His academic journey began somewhat unconventionally, as he left high school early after 11th grade, worked for over a year, and only later discovered his passion for economics through an inspiring teacher at Oberlin. Angrist's research focuses on developing and applying innovative econometric methods to answer important economic questions using natural experiments. His work spans labor economics, education economics, and causal inference methodology. He is particularly known for his contributions to instrumental variables methods and the Local Average Treatment Effect (LATE) framework developed with Guido Imbens. His research explores the economics of education and school reform, the impact of social programs on labor markets, and the effects of immigration and regulation. His recent publications reveal a continued focus on causal inference methods applied to education policy questions, labor market issues, and health economics. The trend shows increasing sophistication in research design, with particular attention to addressing selection bias and developing methods for external validity. His work spans theoretical econometric contributions alongside empirical applications in education, labor markets, and health. Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel (2021) Fama Prize for Graduate Education (2018) Fellow of the American Academy of Arts and Sciences Fellow of the Econometric Society Angrist is deeply committed to teaching and mentoring. He has developed influential econometrics textbooks including 'Mostly Harmless Econometrics' and 'Mastering Metrics' with Jörn-Steffen Pischke. At MIT, he teaches courses including Labor Economics I (14.661), Econometric Data Science (14.32), and Labor Economics and Public Policy (14.64). He emphasizes selecting UROP students who have mastered foundational economics through courses like 14.64 and 14.32. Beyond MIT, Angrist co-founded Avela, a software startup using cutting-edge research to help schools improve enrollment and operations. Angrist co-founded and directs MIT's Blueprint Labs, which brings together researchers from economics, computer science, and education to develop innovative solutions for educational challenges. Through Blueprint Labs and Avela, his work bridges academic research with practical applications in education policy and technology.

David Bammanمشاهده پروفایل

دانشیار

• Natural Language Processing
• Cultural Analytics
• Computational Social Science
• +۳ مورد دیگر

David Bamman is an Associate Professor in the School of Information at UC Berkeley, specializing in applying Natural Language Processing (NLP) and machine learning to cultural and social science questions. He leads research in born-literary NLP, computational humanities, and cultural analytics, with affiliated roles in EECS, Linguistics, and Computational Precision Health. Bamman holds degrees from Carnegie Mellon (Ph.D., 2015), Boston University (M.A., 2006), and University of Wisconsin-Madison (B.A., 1998). His work is supported by NEH, NSF, and industry grants. Educations: Ph.D. in Computer Science (2015), Carnegie Mellon University M.A. in Applied Linguistics (2006), Boston University B.A. in Classics (1998), University of Wisconsin-Madison Research Interests: NLP for underserved domains (e.g., literature, social media), coreference resolution, cultural analytics, and computational methods for studying literature and culture. Projects include LitBank and BookNLP datasets. Grants & Awards: Hellman Fellow (2019), Amazon Research Award (2017), NSF CAREER Award, and NEH funding. Teaching: Courses include Natural Language Processing (Info 159/259), Computational Humanities (INFO 190), and Applied NLP (INFO 256). His research group explores topics like racial representation in high school literature, Hollywood diversity metrics, and the sociocultural implications of LLMs. Bamman advises multiple PhD students and collaborates on datasets like CMU Book Summaries and 11K Latin Books.

• Optimization
• Complex Networks
• Statistical Inference
• +۳ مورد دیگر

Stefano NASINI is an Associate Professor at the University of Lille 3, specializing in Quantitative Methods within the Economics and Mathematics Sciences. He holds a HDR (Habilitation à Diriger des Recherches) from the University of Lille 3 (2021), a Ph.D. in Statistics and Operations Research from the Polytechnic University of Catalonia (2015), and a Master in Statistics (2011). His research focuses on optimization, complex networks, statistical inference, and microeconomic applications. He has held academic positions including a post-doctoral role at IESE Business School (2014–2016) and a visiting researcher role at the University of Lisbon (2014). His work spans scheduling optimization, network analysis, financial contagion modeling, and energy system planning. Key contributions include specialized algorithms for large-scale optimization problems and frameworks for decentralized portfolio management. He is a member of the LEM research group and teaches courses in optimization, econometrics, and social network analysis at the Grande École and MSc levels. Publications highlight interdisciplinary applications, including network-based diffusion models, multi-market financial strategies, and dynamic choice analysis. His research bridges theoretical advancements in operations research with practical challenges in economics, energy, and transportation systems. No scientific awards are explicitly listed in the provided materials. His advising roles and grants are not detailed here, but his extensive publication record reflects active collaboration within academic and applied domains.

• Quantitative Science Studies
• Bibliometrics
• Scientometrics
• +۷ مورد دیگر

Ludo Waltman serves as Scientific Director and Professor of Quantitative Science Studies at the Centre for Science and Technology Studies (CWTS) within Leiden University's Faculty of Social and Behavioural Sciences. He holds multiple influential positions including Co-chair of the Research on Research Institute (RoRI), President of ASAPbio, and Editor-in-Chief of MetaROR (MetaResearch Open Review). As an Open Science Ambassador for Leiden University, he actively promotes transparency and innovation in scholarly communication. Waltman's research spans Quantitative Science Studies, Bibliometrics, and Metascience, with particular focus on university rankings, preprint ecosystems, open access publishing models, and research evaluation frameworks. His work critically examines the infrastructure of scholarly communication, advocating for more transparent and efficient systems that better serve the research community. He has been instrumental in developing initiatives like the Barcelona Declaration on Open Research Information and advancing publish-then-review models as alternatives to traditional peer review. His recent publications reveal a consistent emphasis on systemic issues in scholarly communication, with particular attention to preprint adoption across Europe, the relationship between assessment reform and publishing reform, and the methodological transparency of university rankings. These works collectively demonstrate his commitment to evidence-based approaches for improving research infrastructure and evaluation practices. Waltman actively engages in advising and shaping research policy through his leadership roles. As Co-chair of RoRI, he helps guide metascience research that examines the research system itself. His work with MetaROR promotes innovative peer review models, while his presidency at ASAPbio advances preprint culture in life sciences. He frequently collaborates with major research funders, publishers, and infrastructure organizations to implement practical reforms in scholarly communication. Through CWTS at Leiden University, Waltman leads a research environment focused on quantitative analysis of science and technology systems. His work connects with broader initiatives like the Research on Research Institute and the Barcelona Declaration movement, creating networks that bridge researchers, funders, and infrastructure providers committed to improving research practices.

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.

Jana Diesnerمشاهده پروفایل

استاد

• Human-centered data science
• Computational social science
• Network science
• +۵ مورد دیگر

Jana Diesner is a Professor at the Technical University of Munich (TUM), leading the Human Centered Computing group within the School of Social Science and Technology. Previously, she held a tenured position at the University of Illinois Urbana Champaign (UIUC) School of Information Sciences. She earned her PhD in Computation, Organizations, and Society from Carnegie Mellon University's School of Computer Science. Her research focuses on human-centered data science, computational social science, network science, and ethical AI. She integrates methods from natural language processing, machine learning, and social science theories to study societal systems and responsible computing. Key areas include crisis informatics, data regulations, and impact assessment of media and research. Leadership Academy Fellow for underrepresented STEM leaders (2020) R.C. Evans Data Analytics Fellow (2018) NCSA Faculty Fellow (2015) Siebel Scholarship (2011) Recent work addresses stereotypes in large language models, reliability of crisis data extraction, and societal impact assessment of research. She advises on projects like the NCSA Faculty Fellowship and collaborates with organizations globally. Her teaching includes independent studies at TUM. Her research has been presented at venues like the International Conference on Computational Social Science (IC2S2), European Computational Social Science Symposium, and conferences on ethics in AI. She actively engages in initiatives promoting inclusive STEM leadership and responsible data science practices.

Ying Chenمشاهده پروفایل

دانشیار

• Financial Statistics
• Machine Learning
• Quantitative Finance
• +۷ مورد دیگر

Assoc Prof Ying Chen is an Associate Professor at the National University of Singapore , affiliated with the Department of Mathematics, Asian Institute of Digital Finance (as Academic Director of PhD Program in Digital FinTech 2022–2024), Risk Management Institute (2019–2023), Department of Statistics and Data Science (2019–2023), and Department of Economics (2018–2023). She also contributes to NUS Graduate School for Integrative Sciences and Engineering since 2016. Research Interests include: AI forecasting and quantum computing for finance Nonstationary time series and functional data analysis Energy data analytics and precision medicine Network autoregression and spatial-temporal modeling Explainable AI and citation metrics Portfolio liquidation and market-making algorithms Article Trends demonstrate expertise in: Adaptive forecasting for gas flows and electricity prices Blockchain network influence detection Quantum computing applications in finance Functional autoregression with mixed predictors Credit rating fairness and explainability High-resolution implied volatility modeling Scientific Awards include: ISI Elected Member (2016–) International Statistical Institute Council (2023–2027) IASC Scientific Secretary (2017–2019, 2023–2025) Advisory roles for EU FIN-TECH and xAIM projects

• Dynamics of Innovation
• Regulatory Sciences
• Economics of Science and Innovation
• +۵ مورد دیگر

Dr. Jarno Hoekman is an Associate Professor in Innovation Studies at the Copernicus Institute of Sustainable Development, Utrecht University. His research focuses on the dynamics and governance of science in the context of innovation, regulation, and societal challenges, with particular emphasis on sustainability and health. He is affiliated with both the Copernicus Institute of Sustainable Development and the Utrecht collaborating Centre for Pharmaceutical Policy & Regulation in the Department of Pharmaceutical Sciences. Dr. Hoekman serves as the programme leader of the research master in Innovation Sciences and teaches academic integrity courses to Master students and PhD candidates. Dr. Hoekman's research is organized around three interconnected themes: Science in transition , examining how scientific practices and institutional arrangements are evolving through open science, interdisciplinary research collaborations, and alternative recognition systems; Regulatory science and innovation , investigating innovations in tools and standards for assessing risks and benefits of new technologies, including safety assessment methods and regulatory authorization standards; and Geography of science , exploring the role of location factors in scientific knowledge production and diffusion. Analysis of Dr. Hoekman's recent publications (2022-2024) reveals a strong interdisciplinary focus spanning pharmacology, toxicology, innovation studies, and science policy. Key research trends include examining conditional marketing authorization pathways, post-approval studies for conditionally authorized medicines, animal-free safety testing methodologies, and the societal impact of transdisciplinary research projects. His work frequently employs mixed-methods approaches and involves multi-stakeholder perspectives to address complex regulatory and innovation challenges. Dr. Hoekman actively contributes to policy-relevant research, including major European Commission studies on pharmaceutical legislation. His collaborative work extends across multiple institutions and involves interdisciplinary teams working on pharmaceutical policy, sustainable innovation, and science-society interactions. As a member of the Utrecht Young Academy and the UU Open Science Platform, he engages with broader academic community initiatives related to research integrity and open science practices.

• Comparative Public Policy
• Innovation Studies
• Science of Science
• +۴ مورد دیگر

Claudia Acciai is a Guest Researcher at SODAS (Sociology Department) at the University of Copenhagen, where she works on the research project "Quantifying institutional and country-related Matthew effects in science." She holds a PhD in Political Science and Sociology from the Scuola Normale Superiore, with a dissertation focused on policy design in the Research and Innovation sector. Her academic journey includes research visits at Alliance Manchester Business School, Science Po Paris, and Copenhagen Business School. Her research interests lie at the intersection of comparative public policy, innovation studies, and science of science. She combines computational and experimental methods with qualitative content analysis techniques to examine policy design, institutional effects in science, and research evaluation. Her work frequently addresses how policy instruments function in complex governance environments and investigates gender-related differences in academic publishing. Analyzing her recent publications reveals a strong focus on the science of science, with particular attention to bibliometrics, policy instrument effectiveness, and gender dynamics in academic careers. Her work spans multiple disciplines including political science, sociology of science, and innovation studies, often employing mixed-methods approaches that combine quantitative analysis with qualitative insights. Acciai is an active member of the Knowledge, Organization and Politics research group at the Department of Sociology. Her collaborations span multiple countries and institutions, reflecting the international nature of her research on comparative policy and science studies. She has conducted significant work for research projects funded by the Italian Ministry of Education, including analyses of policy analysis capacity in Italian policymaking and governance changes in higher education systems.

• Data Visualization
• Scientometrics
• Science of Science
• +۴ مورد دیگر

Katy Börner is a Professor affiliated with Indiana University, Bloomington, USA. Her research focuses on data visualization, scientometrics, and the science of science, with contributions to tools like Network Workbench (NWB) and Sci2. She leads interdisciplinary projects such as the Human Reference Atlas and explores visualization literacy in education and public health. Her work spans virtual reality applications, biomedical knowledge networks, and AI-driven scientific discovery. Key research interests include mapping scientific collaboration networks, analyzing scholarly publications, and developing visualization frameworks for big data. She collaborates widely with institutions like NIH and VIVO, advancing open science and interdisciplinary research. Her projects often bridge computational methods with human-centric design, enhancing understanding of complex systems in health, technology, and social sciences. Publications highlight innovations in interactive visualization tools (e.g., opioid crisis research networks), data integration (Human Reference Atlas), and AI applications in biomedical research. She emphasizes translating data into actionable insights through visual analytics, impacting policy, education, and healthcare.

• Machine Learning
• Deep Learning
• Graph Analysis
• +۶ مورد دیگر

Michalis Vazirgiannis is a Professor at LIX, École Polytechnique (France) leading the Data Science and Mining (DaSciM) group. With academic backgrounds in Physics (Athens University), AI (Heriot-Watt University), and Informatics (Athens University), he has conducted research at Fraunhofer, Max Planck MPI, and INRIA/FUTURS while teaching at institutions across Greece, France, China, and Spain. His research spans Machine/Deep Learning for Graphs (GNNs, graph kernels, embeddings) Text Mining & NLP (Graph-of-Words, biomedical text analysis) Combinatorial Optimization for pandemic forecasting and energy systems Event/Anomaly Detection in time series and sensory data Industrial collaborations with Airbus, Google, Tencent, and BNP . He has supervised 29 completed PhD theses, published over 250 papers, and received prestigious awards including Marie Curie and Tencent Rhino-Bird Fellowships. His team leads the ANR-HELAS Chair (2020-2025) focusing on heterogeneous data deep learning.

Manuel Anglada-Tortمشاهده پروفایل

مدرس

• Cultural Evolution
• Music Perception and Cognition
• Empirical Aesthetics
• +۳ مورد دیگر

Dr. Manuel Anglada-Tort is a Lecturer in Psychology at Goldsmiths, University of London, and a visiting researcher at the Max Planck Institute for Empirical Aesthetics. His research focuses on the psychology of cultural systems, including music, creativity, and empirical aesthetics. He combines computational methods with psychological experiments to explore cultural evolution, music perception, and the interplay of cognition and social interaction. Research Interests: Cultural Evolution Music Perception & Cognition Empirical Aesthetics Creativity Big Data Analyses Key Projects: Large-scale iterated singing experiments on music evolution Investigating weather's influence on music success Developing the REPP platform for online sensorimotor synchronization studies Teaching: MSc in Music, Mind, and Brain MSc Psychology of the Arts, Neuroaesthetics, and Creativity Affiliations: Music, Mind and Brain Group at Goldsmiths Computational Auditory Perception Group at Max Planck Institute

Agnes Horvatمشاهده پروفایل

دانشیار

• Human-Centered Computing
• Network Science
• Artificial Intelligence
• +۵ مورد دیگر

Agnes Horvat is an Associate Professor of Communication (with a courtesy appointment in Computer Science) at Northwestern University. She directs the Technology and Social Behavior (TSB) joint doctoral program between the McCormick School of Engineering and the School of Communication, and leads the Lab on Innovation, Networks, and Knowledge (LINK). Her research focuses on human-centered computing, network science, and AI's impact on information production/sharing in digital platforms. She has received NSF CAREER, CRII, and collaborative awards as PI. Her work examines algorithmic bias in online spaces, AI-assisted creativity (e.g., LLMs in biomedical writing and music), and collective intelligence dynamics. Media coverage includes Nature , Washington Post , and Le Monde . Her advisees have won prestigious fellowships like the Northwestern Presidential Fellowship and best paper awards at top conferences. Research interests include: (1) algorithmic bias in social media and crowdfunding, (2) AI-driven creativity expansion, (3) network structures of scientific attention, and (4) opinion dynamics in online discussions. Current projects explore LLMs' role in scientific writing and music composition, while past work analyzed gender disparities in scholarly self-promotion and retraction paper attention patterns. Grants: NSF CAREER Award (202?), NSF CRII (202?), Collaborative Grant (202?) Labs/Teams: LINK Lab (focusing on innovation networks), TSB Program (interdisciplinary engineering/communication PhD)

Stefanie Hausteinمشاهده پروفایل

دانشیار

• Scholarly Communication
• Bibliometrics
• Altmetrics
• +۳ مورد دیگر

Stefanie Haustein is an Associate Professor at the University of Ottawa’s School of Information Studies. She co-directs the Scholarly Communications Lab (ScholCommLab), a research group focused on digital-era scholarly communication. Her affiliations include the Institute for Science, Society and Policy (ISSP), the Centre for Journalology at the Ottawa Hospital Research Institute, and the Centre interuniversitaire de recherche sur la science et la technologie (CIRST) at Université du Québec à Montréal. Her research centers on scholarly communication, bibliometrics, altmetrics, and open science. She explores open access, data sharing, academic publishing models, and the role of social media in scientific dissemination. Her recent work examines APC pricing, diamond OA identification, OpenAlex database evaluation, and pandemic research engagement. Stefanie holds a PhD in Information Science from Heinrich Heine University Düsseldorf and Master’s degrees in History, American Linguistics/Literature, and Information Science. She previously conducted postdoctoral work at École de bibliothéconomie et des sciences de l'information (EBSI), University of Montreal, and worked as a research analyst at Science-Metrix and Forschungszentrum Jülich. The ScholCommLab, under her co-direction, investigates multifaceted aspects of scholarly communication, including reward systems, citation patterns, and digital workflows. Her supervision of Madelaine Hare (expected 2027) reflects her commitment to mentoring emerging scholars.

Jodi Schneiderمشاهده پروفایل

دانشیار

• Controversies in Science
• Science of Science
• Argumentation and Evidence
• +۱۲ مورد دیگر

Jodi Schneider is an Associate Professor at the University of Illinois Urbana-Champaign , with affiliate appointments at the Beckman Institute , Health Care Engineering Systems Center , European Union Center , and Center for Health Informatics . She directs the Information Quality Lab and focuses on the science of science through argumentation and evidence analysis. PhD in Informatics (National University of Ireland, Galway) M.S. in Library and Information Science (UIUC) M.A. in Mathematics (UT-Austin) B.A. in Liberal Arts (St. John's College) Her research examines how scientific controversies persist through citation patterns, the role of knowledge brokers in public policy, and information quality in biomedical contexts. She has developed semantic frameworks for micropublications and knowledge maintenance in digital libraries. Recent publications include citation integrity studies in Scientometrics , retraction indexing in STI Conference , and argumentation mining in Human Language Technologies . Collaborative projects span institutions like Harvard Radcliffe Institute and RWTH Aachen . NSF CAREER Award IMLS Early Career Award Senior Member, Association of Computing Machinery Marie Curie Fellow She advises graduate students in information quality and knowledge representation , with funding from the Alfred P. Sloan Foundation , NIH , and European Commission . Her lab develops tools to combat scientific misinformation and improve public health informatics .