جستجوی استاد راهنمای دانشگاهی

Dr. Herb Lin is the Hank J. Holland Fellow in Cyber Policy and Security at the Hoover Institution and Senior Research Scholar for Cyber Policy and Security at the Center for International Security and Cooperation (CISAC), both at Stanford University. He also serves as Chief Scientist, Emeritus for the Computer Science and Telecommunications Board of the National Academies, where he worked from 1990 to 2014, and as Adjunct Senior Research Scholar and Senior Fellow in Cybersecurity at Columbia University's Saltzman Institute for War and Peace Studies. Dr. Lin received his doctorate in physics from MIT, providing him with a strong technical foundation that informs his policy work at the intersection of technology and national security. His academic background bridges the gap between deep technical understanding and policy application in the cybersecurity domain. Dr. Lin's research focuses on the policy dimensions of cybersecurity and cyberspace, with particular emphasis on offensive cyber operations as instruments of national policy, information warfare, and influence operations affecting national security. His work addresses critical challenges at the intersection of emerging technologies like artificial intelligence, quantum computing, and their implications for nuclear security, election integrity, and democratic processes. He has been instrumental in analyzing how cyber capabilities are transforming traditional security paradigms and how policy frameworks must adapt to these changes. His extensive publication record reveals a consistent focus on the evolving relationship between cyber capabilities and national security strategy. Lin's work demonstrates increasing attention to the implications of artificial intelligence for warfare, the vulnerabilities created by quantum computing for current cryptographic systems, and the growing threat of cyber-enabled information warfare to democratic institutions. His research trajectory shows a progression from traditional cybersecurity issues toward the broader implications of digital technologies for national and international security. Member of Science and Security Board of Bulletin of the Atomic Scientists Served on President Obama's Commission on Enhancing National Cybersecurity (2016) Regular congressional testimony on cybersecurity matters Contributor to Stanford Emerging Technology Review As a mentor and collaborator, Dr. Lin works extensively with policymakers, military officials, and technology experts to translate complex cybersecurity concepts into actionable policy recommendations. His approach emphasizes practical solutions to emerging threats while recognizing the technical limitations and policy constraints that shape real-world security outcomes. Dr. Lin is associated with multiple research initiatives including Stanford's Center for International Security and Cooperation and the Stanford Emerging Technology Review, which aim to connect technological advances with policy considerations for national security decision-makers.

• Cybersecurity Policy
• Information Warfare
• Nuclear Security
• +۴ مورد دیگر

Ricardo Caballero is the Ford International Professor of Economics at the Massachusetts Institute of Technology's School of Humanities, Arts, and Social Sciences, where he previously served as Chairman of the Economics Department from 2008 to 2011. A leading scholar in macroeconomics and financial economics, his research focuses on safe assets, monetary policy, financial crises, and international economics. His research interests center on the macroeconomic implications of financial frictions, with particular emphasis on safe asset shortages, risk premium dynamics, and monetary policy transmission mechanisms. Caballero's work has pioneered the risk-centric approach to macroeconomics, explaining phenomena such as the Wall Street/Main Street disconnect, global imbalances, and the collapse of interest rates through the lens of safe asset scarcity and risk intolerance. His research bridges theoretical modeling with empirical analysis of financial crises and policy interventions. Caballero's recent publications demonstrate a consistent focus on financial conditions indexing, monetary policy frameworks, and the interaction between financial markets and the real economy. His work increasingly examines how central banks can target financial conditions directly and how risk premia evolve during crises, with applications to pandemic-era economic policy and zero lower bound environments. 2002 Frisch Medal of the Econometric Society Smith Breeden Prize by the American Finance Association Journal of Finance 2014 Brattle Group Prize 2022 Banque de France-TSE Senior Prize in Monetary Economics and Finance Elected Fellow of the Econometric Society (1998) Elected Fellow of the American Academy of Arts and Sciences (2010) As an NBER Research Associate and frequent policy advisor, Caballero has influenced central bank thinking globally through his work on financial stability, monetary policy frameworks, and global imbalances. His research has informed policy discussions at the Federal Reserve, IMF, and multiple central banks regarding crisis management, safe asset creation, and the appropriate monetary response to financial shocks. Caballero maintains active collaborations with major financial institutions and central banks worldwide, translating theoretical insights into practical policy frameworks.

• Macroeconomics
• Financial Economics
• International Economics
• +۳ مورد دیگر

Moshe E. Ben-Akiva is the Edmund K Turner Professor at the Massachusetts Institute of Technology (MIT), affiliated with the School of Engineering and the Department of Civil and Environmental Engineering. He holds a B.S. from Technion-Israel Institute of Technology (1968), and M.S. and Ph.D. degrees in transportation systems from MIT (1971, 1973). His research focuses on transportation systems analysis, intelligent transportation systems, demand modeling, econometrics, and infrastructure management. He has been recognized with prestigious awards, including election to the National Academy of Engineering (2025) for contributions to transportation systems modeling and demand analysis. His work spans theoretical and applied domains, including agent-based microsimulation for freight logistics, tradable credit schemes for congestion management, and behavioral dimensions of transport decarbonization. Ben-Akiva collaborates with industry and policymakers to design sustainable mobility solutions. His notable publications include foundational texts on discrete choice analysis and stated preference elicitation. He advises on transportation policy, urban planning, and emerging mobility technologies such as automated vehicles and urban air mobility. Current research explores impacts of automated mobility-on-demand systems, real-time tolling strategies, and e-commerce delivery demand modeling. His team develops tools like SimMobility Freight, an agent-based urban freight simulator. He remains active in teaching, focusing on demand modeling and econometrics courses at MIT.

• Transportation Systems Analysis
• Intelligent Transportation Systems
• Demand Modeling
• +۶ مورد دیگر

Matthew Kay is an Associate Professor in the Department of Communication Studies at Northwestern University's School of Communication, with a secondary appointment in Computer Science. He serves as Co-Director of Graduate Studies for the PhD in Technology and Social Behavior program. His research focuses on human-computer interaction and information visualization, specializing in uncertainty communication, usable statistics, and personal informatics. He employs mixed-method approaches including behavioral analysis, interactive system development, and visualization technique evaluation to address real-world data interpretation challenges. Analysis of his recent publications reveals dominant themes in visualization literacy development, uncertainty representation for decision-making, and health informatics applications. His work consistently bridges theoretical frameworks with practical implementations, particularly in educational assessment tools and election forecast visualizations. Professor Kay co-directs the Midwest Uncertainty Collective (MU collective), a research group advancing uncertainty communication methodologies. Previously faculty at the University of Michigan School of Information, he maintains active contributions to visualization tool development including the ggdist R package for uncertainty visualization.

• Human-Computer Interaction
• Information Visualization
• Uncertainty Communication
• +۲ مورد دیگر

Morris P. Fiorina is the Wendt Family Professor of Political Science at Stanford University and a Senior Fellow at the Hoover Institution. He joined Stanford in 1998 after teaching at Caltech and Harvard. His academic credentials include a B.A. from Allegheny College (1968) and a Ph.D. from the University of Rochester (1972), both in Political Science. Fiorina's research focuses on American politics, emphasizing representation, public opinion, elections, and partisan dynamics. His influential works include Retrospective Voting in American National Elections , Culture War? The Myth of a Polarized America , and Unstable Majorities . He has authored or edited thirteen books and numerous articles, challenging conventional views on polarization, electoral behavior, and political institutions. He has held editorial roles across a dozen political science journals and chaired the American National Election Studies Board (1986–1990). A distinguished scholar, he is an elected member of the American Academy of Arts and Sciences, the American Academy of Political and Social Sciences, and the National Academy of Sciences. He received Career Achievement Awards from the American Political Science Association's sections on Elections, Public Opinion, and Voting Behavior, as well as Political Organizations and Parties. Key Contributions: Pioneered studies on retrospective voting, party sorting, and the 'myth of polarization.' Public Engagement: Analyzes contemporary issues like divided government, electoral reform, and the role of third parties. Fiorina’s work bridges academia and public discourse, addressing critical challenges in American democracy. His current research continues to explore polarization, representation, and governance in the modern political landscape.

• American Politics
• Political Representation
• Public Opinion
• +۳ 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

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

Maisha T. Winn serves as the Excellence in Learning Graduate School of Education Professor at Stanford University and is Faculty Director of the Stanford Accelerator for Learning's Equity in Learning Initiative. She leads the Futuring for Equity Lab as Principal Investigator and holds significant leadership positions including President-Elect of the American Educational Research Association and membership in the National Academy of Education. Dr. Winn's research examines how non-dominant youth and communities develop literate trajectories across historical and contemporary settings. As an ethnographer by training, she investigates how communities depicted as under-resourced create their own educational practices, processes, and institutions. Her scholarship bridges historical analysis with contemporary educational practice to build more just, collaborative, and equitable futures in education. Her work spans restorative justice in education, Black literacy studies, and transformative justice approaches, with particular attention to the school-to-prison pipeline, independent Black institutions, and futures-oriented educational frameworks. Dr. Winn analyzes how historical educational models can inform contemporary practices that center community knowledge and cultural identity. Andrew W. Mellon Fellow at CASBS (2022-23) American Educational Research Association Fellow Member of the National Academy of Education Dr. Winn advises doctoral students including Christina Hewko and Misbah Naseer, and leads research initiatives focused on educational equity. Her Futuring for Equity Lab develops frameworks for understanding how marginalized communities have historically created educational spaces that affirm their identities and knowledge systems, with direct implications for contemporary educational practice and policy. Her research team collaborates with community organizations and schools to translate scholarly insights into practical applications that promote educational justice, particularly in areas of school discipline reform and literacy education for marginalized youth.

• Restorative Justice in Education
• Black Education and Literacy Studies
• Social Justice and Equity in Education
• +۴ مورد دیگر

Tarik Abou-Chadi is a Professor in European Union and Comparative European Politics at the University of Oxford's Department of Politics and International Relations, and a Professorial Fellow at Nuffield College. He holds a PhD from Humboldt University Berlin (2015). His research focuses on elections, political parties, and the transformation of democratic representation in post-industrial societies. Key affiliations include the Government and Politics Network, Comparative Politics and Government, and leadership of the Swiss National Science Foundation-funded project on 'Social Status and the Transformation of Electoral Behavior in Western Europe'. He previously served as Assistant Professor at the University of Zurich before joining Oxford. His work appears in top journals like the American Political Science Review and World Politics. Awards include the Henrik Enderlein Prize (2022) and inclusion in Capital magazine's 'Top 40 under 40' (2022). He advises four doctoral students and actively contributes to media commentary on European political trends through outlets like The Economist. Research interests emphasize far-right dynamics, voter behavior, and party strategy in Western Europe. His recent analyses address gendered political preferences among youth, climate policy acceptance, and the electoral consequences of mainstream parties adopting radical-right policies.

• European Union Politics
• Comparative European Politics
• Electoral Behavior
• +۳ مورد دیگر

Gary King is the Albert J. Weatherhead III University Professor at Harvard University and Director of the Institute for Quantitative Social Science. He is based in the Department of Government within Harvard's Faculty of Arts and Sciences. One of only 22 University Professors at Harvard, this represents the institution's most distinguished faculty position. King received his B.A. from SUNY New Paltz in 1980 and his Ph.D. from the University of Wisconsin-Madison in 1984. His academic journey has led him to become one of the most influential scholars in political methodology and quantitative social science. Professor King's research spans numerous areas of methodological innovation in the social sciences. His work focuses on developing and applying empirical methods across various domains. Key research interests include: Ecological Inference - developing methods to infer individual behavior from group-level data Automated Text Analysis - creating techniques for extracting knowledge from massive text collections Causal Inference - methods for detecting and reducing model dependence in causal effect estimation Missing Data and Measurement Error - statistical approaches to handle incomplete or imperfect data Survey Research - developing methods for more accurate cross-cultural survey comparisons Unifying Statistical Analysis - integrating diverse methodological approaches into coherent frameworks King's recent publications demonstrate a continued focus on methodological innovation with practical applications. His work spans political science, public health, and data science, with particular emphasis on privacy-preserving data analysis, maternal health metrics, survey methodology, and media effects. A notable trend is the increasing interdisciplinary nature of his research, bridging political methodology with public health, computer science, and demography. His work on census data privacy, maternal mortality disparities, and media influence represents cutting-edge applications of social science methodology to critical societal issues. His scientific achievements have been recognized with numerous prestigious awards: Fellow of the National Academy of Sciences (2010) Fellow of the American Statistical Association (2009) Fellow of the American Academy of Arts and Sciences (1998) Guggenheim Foundation Fellow (1994-1995) Career Achievement Award (2010) Warren Miller Prize (2008) Multiple awards for research software and methodology King has mentored numerous students and postdocs, many of whom now hold faculty positions at leading universities. His research has been supported by major funding agencies including the National Science Foundation, Centers for Disease Control and Prevention, World Health Organization, and National Institute of Aging. He has collaborated with over seventy scholars on research publications and served on numerous editorial boards and professional organization councils. His work on the Mexican universal health insurance program represents one of the largest randomized health policy experiments to date, demonstrating his commitment to rigorous evaluation of real-world policy interventions. As Director of the Institute for Quantitative Social Science, King leads a vibrant research community focused on methodological innovation. His work has practical applications in diverse areas including legislative redistricting (used by the U.S. Supreme Court), health policy evaluation (including the largest randomized health policy experiment to date in Mexico), Chinese censorship analysis (revealing government fabrication of 450 million social media comments annually), and automated text analysis (through Crimson Hexagon, a company he co-founded).

• Political Methodology
• Statistical Inference
• Quantitative Social Science
• +۷ مورد دیگر

Mark Coeckelbergh is a Professor of Philosophy at the University of Vienna, specializing in the philosophy of technology, AI ethics, and robot ethics. He is affiliated with the Department of Philosophy and the Research Network Data Science at the University of Vienna. In addition to his academic position, Coeckelbergh has held significant roles including Former President of the Society for Philosophy and Technology (SPT) and Member of the European Commission's High-Level Expert Group on Artificial Intelligence (AI HLEG). His research focuses on the ethical, political, and philosophical implications of emerging technologies, particularly artificial intelligence and robotics. Coeckelbergh has published extensively in these areas, authoring influential books such as Robot Ethics (2022), The Political Philosophy of AI (2022), and Why AI Undermines Democracy and What To Do About It . His work explores how AI systems affect democratic processes, human agency, and social relationships. Recent publications demonstrate a strong focus on the relationship between AI, democracy, and ethical governance, examining how AI systems can both threaten and potentially enhance democratic processes through algorithmic transparency and participatory design approaches. Finalist of the World Technology Award 2017 Coeckelbergh teaches various courses including 'Introduction to Philosophy of LLMs,' 'LLMs and the Future of Writing,' 'Ethics and Robotics,' and 'Global Governance of AI.' He has supervised numerous students working on topics related to technology ethics and philosophy. He has been involved in several major research projects including H2020 PERSEO, WWTF Democracy Responsible Entrepreneurship, and FP7 DREAM (Development of Robot-Enhanced therapy for children with Autism spectrum disorders). Coeckelbergh has also announced upcoming guest professorships at the Institute of Philosophy of the Czech Academy of Sciences and Uppsala University, where he will work on environmental and technology ethics projects.

• AI Ethics
• Robot Ethics
• Political Philosophy of AI
• +۴ مورد دیگر

Michael Stamm is Chairperson and Professor in the Department of History at Michigan State University, within the College of Social Science. His research focuses on media and journalism history, with specialties in cultural, political, and environmental history. He has authored influential books like Sound Business (2011) and Dead Tree Media (2018), which explore the material and economic dimensions of print media. His work bridges media studies with environmental history, examining global commodity chains and the geopolitical impact of newsprint production. Stamm’s research has been recognized with awards including the Canadian Business History Association’s Best Book Prize (2019) and the Richard E. Sullivan Teaching Excellence Award (2022). He leads courses on North American history, media, business, and environmental history. From 2017–2020, he directed MSU’s participation in the American Historical Association’s Career Diversity initiative, fostering innovative historian training. His recent projects expand into international media comparisons and digital-age publishing challenges. Stamm’s academic profile combines rigorous historical scholarship with interdisciplinary engagement, reflecting his dual role as a researcher and educator.

• Media Studies
• Political History
• Cultural History
• +۳ مورد دیگر

Francis Bach is a Professor and researcher at INRIA, leading the SIERRA project-team since 2011, which is part of the Computer Science Department at Ecole Normale Supérieure (ENS) within PSL Research University. His work bridges CNRS, ENS, and INRIA as a joint research effort. Elected to the French Academy of Sciences in 2020, he currently runs the ERC project SEQUOIA following his previous ERC project SIERRA (2009-2014). His research spans statistical machine learning with focus on optimization, sparse methods, kernel-based learning, neural networks, graphical models, and signal processing. Bach completed his Ph.D. in Computer Science at U.C. Berkeley under Professor Michael Jordan, followed by work at Ecole des Mines de Paris and the WILLOW project-team at INRIA/ENS/CNRS (2007-2010). His recent book "Learning Theory from First Principles" was published by MIT Press in December 2024. Bach's publication record shows consistent high-impact contributions across machine learning theory and applications, with recent work focusing on conformal prediction, diffusion models, optimization theory, and learning theory foundations. His research demonstrates strong connections between theoretical guarantees and practical algorithms, with applications spanning generative modeling, robust optimization, and statistical inference. Elected to French Academy of Sciences (2020) ERC project SIERRA (2009-2014) ERC project SEQUOIA (current) Author of "Learning Theory from First Principles" (MIT Press, 2024) Bach actively mentors numerous PhD students and postdocs, with many alumni now holding faculty positions at institutions like EPFL, Ecole Polytechnique, University of Washington, and University of Montreal. His teaching includes advanced courses on learning theory at ENS's Master's programs. He regularly presents tutorials at major conferences including COLT, NeurIPS, and ICML, demonstrating his leadership in the theoretical machine learning community.

• statistical machine learning
• optimization
• sparse methods
• +۵ مورد دیگر

Akshay R. Rao is a Professor and General Mills Chair in Marketing at the University of Minnesota's Carlson School of Management . He holds a PhD in Marketing from Virginia Tech and has served as founding Director of the Institute for Research in Marketing (2005-2010) and Chairman of the Marketing & Logistics Management Department (2003-2006). Rao has also held visiting positions at MIT and Hong Kong University of Science & Technology. Bachelor of Arts in Economics (Honors), Madras University (1978) Master of Business Administration in Marketing, XLRI - Xavier School of Management (1980) Doctor of Philosophy in Marketing, Virginia Polytechnic Institute and State University (1986) Rao's research spans consumer behavior, pricing strategy, brand management , and political marketplace segmentation , with recent work examining vaccine hesitancy , political ideology effects on consumer behavior , and fake news dynamics . His work appears in top journals including Journal of Consumer Research , Journal of Marketing , and Harvard Business Review , covering topics from neuromarketing to information economics . Scientific recognition includes: Robert Ferber Award (1987) Harold Maynard Award (2000) Distinguished Alumnus, XLRI (2011) He has testified before the Federal Trade Commission and served on editorial boards of Journal of Consumer Research and Journal of Marketing . Beyond academia, Rao consults for global firms like 3M and Medtronic, and has conducted the Minnesota Orchestra twice in 2024-2025.

• Consumer Behavior
• Pricing Strategy
• Brand Management
• +۸ مورد دیگر

Dr. Matloob Khushi serves as a Senior Lecturer in Computer Science at Brunel University London's College of Engineering, Design and Physical Sciences. With over 25 years of combined academic and industry experience, his work bridges theoretical AI advancements with practical applications in finance, healthcare, and public health domains. His research has established significant collaborations with international banks, healthcare institutions, and technology startups. Dr. Khushi earned his PhD in AI and Data Science from the University of Sydney, developing novel algorithms for genomic data analysis. His postdoctoral research at the Children's Medical Research Institute (2014-2017) pioneered AI-based diagnostic tools for medical condition detection. More recently, he developed bioinformatics tools for environmental assessment under a UKRI NEC grant. Research Focus FinTech Innovation : Creator of the SS Ratio (incorporating volatility and drawdown sensitivities), advanced portfolio optimization models, and synthetic data generation techniques for fraud detection and credit risk assessment Bioinformatics Leadership : Developer of AI tools for genomic analysis and early cancer detection, featured in SBS News and The Daily Telegraph Public Health NLP : Architect of systems for vaccine misinformation detection, mental health monitoring, and health surveillance on social media His publication portfolio shows consistent growth from foundational bioinformatics work to current multimodal AI applications, with increasing interdisciplinary collaboration across finance and healthcare sectors. Awards and Recognition Ranked among Stanford/Elsevier's top 2% of global AI scientists Recipient of Best Paper Awards from IEEE Transactions on Computational Social Systems and PeerJ Media recognition for cancer detection research by major news outlets Mentorship and Teaching Dr. Khushi has supervised six PhD candidates to completion and over 100 postgraduate dissertations. He teaches CS3002 Artificial Intelligence and mentors students in Final Year Projects. His supervision focuses on Deep Learning/NLP for FinTech prediction and Public Health Surveillance applications, emphasizing practical implementation of theoretical concepts.

• Artificial Intelligence
• Machine Learning
• Natural Language Processing
• +۷ 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.

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