جست‌وجوی استاد و پژوهشگر

Kenji Kawaguchiمشاهده پروفایل

استادیار

• Deep Learning
• Machine Learning
• Theoretical Foundations of Deep Learning
• +۱۲ مورد دیگر

Kenji Kawaguchi is the Presidential Young Professor in the Department of Computer Science at the National University of Singapore (NUS), where he leads the Deep Learning Lab and is a faculty affiliate at the NUS Institute of Data Science. His research bridges theoretical and applied machine learning, focusing on deep learning, large language models, and physics-informed neural networks. His educational background includes a Ph.D. and S.M. in Computer Science and Electrical Engineering from the Massachusetts Institute of Technology (MIT), advised by Leslie Pack Kaelbling, and a postdoctoral fellowship at Harvard University’s Center of Mathematical Sciences and Applications. Dr. Kawaguchi’s research interests center on the theoretical foundations of deep learning, optimization, generalization, and applications in areas such as molecular modeling, AI safety, and efficient training of large models. He has made significant contributions to understanding in-context learning, diffusion models, and neural operators for partial differential equations. His recent publications (2023–2025) reflect a strong trend toward improving the efficiency, robustness, and interpretability of large-scale models, particularly in language and scientific domains. Key themes include LLM alignment and safety, diffusion model optimization, and physics-informed learning for high-dimensional problems. Presidential Young Professor He has served as Area Chair and PC Member for top-tier conferences including NeurIPS, ICML, ICLR, AAAI, and UAI, and as reviewer for journals such as JMLR and Annals of Statistics. He has delivered invited talks at Harvard, MIT, Stanford, CMU, Brown, and Google Research, reflecting his international recognition. He actively mentors students and welcomes PhD candidates and postdocs to join his research group.

Aarti Singhمشاهده پروفایل

استاد

• Reinforcement Learning
• Bandit Algorithms
• Active Learning
• +۷ مورد دیگر

Aarti Singh is a Professor in the Machine Learning Department at Carnegie Mellon University and Director of the NSF AI Institute for Societal Decision Making. She leads research at the intersection of machine learning, statistics, and decision making, with applications to scientific and societal domains. Her work focuses on designing principled interactive algorithms for learning and decision making under uncertainty. Education: Ph.D. in Electrical Engineering, University of Wisconsin-Madison (2008) M.S. in Electrical Engineering, University of Wisconsin-Madison (2003) B.E. in Electronics and Communication Engineering, University of Delhi (2001) Research Interests: Professor Singh's research centers on developing interactive machine learning algorithms that go beyond finding input-output associations to make higher-level decisions about the most informative data and actions. Her work spans autonomous decision making, including active sampling, stochastic optimization, bandits, and reinforcement learning that are statistically optimal, computationally tractable, and robust. She also investigates human factors in decision making, designing algorithms that model and leverage human feedback while accounting for bias, memory effects, and calibration. Her research has applications in material science, cosmology, and peer review systems. Research Trends: Professor Singh's recent publications demonstrate a strong focus on reinforcement learning, particularly in developing more efficient and robust algorithms for decision making under uncertainty. Her work bridges theoretical foundations with practical applications, spanning from fundamental algorithm development to real-world implementation in scientific domains. There's a clear trajectory toward integrating human factors into decision-making algorithms, with significant contributions to peer review systems and preference learning. Scientific Awards: NSF Career Award United States Air Force Young Investigator Award A. Nico Habermann Faculty Chair Award Harold A. Peterson Best Dissertation Award Multiple paper awards Advising and Grants: Professor Singh has advised numerous PhD and master's students, many of whom have gone on to faculty positions or research roles at leading institutions. Her research is supported by prestigious grants from ONR, Simons Foundation, AFRL, ARL, and NSF. She serves as General Chair (2025) and Program Chair (2020) for the International Conference on Machine Learning (ICML) and has held leadership roles in multiple professional organizations. Research Team: Professor Singh leads a vibrant research group within the Machine Learning Department at CMU, with current PhD students working on topics including reinforcement learning, human-AI collaboration, and decision making under uncertainty. She also directs the NSF AI Institute for Societal Decision Making, which brings together researchers from multiple disciplines to develop AI systems that support human decision making in societal contexts.

Andrew Postlewaiteمشاهده پروفایل

استاد

• Game Theory
• Behavioral Economics
• Social Norms
• +۳ مورد دیگر

Andrew Postlewaite is the Harry P. Kamen Professor of Economics and Professor of Finance at the University of Pennsylvania's School of Arts and Sciences. He holds dual roles in the Department of Economics and the Ronald O. Perelman Center for Political Science and Economics. As a distinguished academic, he is a member of the American Academy of Arts and Sciences and serves as a director at the National Bureau of Economic Research (NBER). Additionally, he is the founding editor of the American Economic Journal: Microeconomics and a research associate at Penn's Population Studies Center and Institute for Law and Economics. Postlewaite's research focuses on game theory, behavioral economics, and social norms, with contributions to mechanism design, repeated games, and intergenerational transmission of preferences. His work bridges theoretical foundations with applied economic analysis, particularly in areas like consumer behavior, decision-making, and institutional design. He has held visiting positions at institutions including Caltech, Harvard, and Stanford, reflecting his academic prominence. His scholarly contributions include pioneering studies on future-oriented decision-making, interdependent valuations in markets, and equilibrium concepts in repeated games. Recent publications explore topics such as the impact of local media accessibility in the digital age and the welfare implications of consumption fluctuations. His editorial leadership at journals like Econometrica and International Economic Review underscores his influence in shaping economic discourse. Awarded prestigious fellowships and editorial roles, Postlewaite's career exemplifies a blend of rigorous theoretical research and practical applications in economics. His current research trends emphasize behavioral insights and the methodological underpinnings of economic models, reflecting a commitment to advancing both theory and real-world relevance.

• Machine Learning
• Deep Learning
• AI Safety
• +۱۲ مورد دیگر

Tim G. J. Rudner is an Assistant Professor in the Department of Statistical Sciences at the University of Toronto, a Faculty Member at the Vector Institute, and a Title A Fellow at Trinity College, University of Cambridge. He was previously an Assistant Professor and Faculty Fellow at New York University. University: University of Toronto School: Faculty of Arts and Science Department: Department of Statistical Sciences Affiliation: Vector Institute, Trinity College (Cambridge) He holds a PhD in Computer Science and an MSc in Statistics from the University of Oxford, where he was advised by Yee Whye Teh and Yarin Gal, and a BS in Applied Mathematics and Economics from Yale University. PhD: Computer Science, University of Oxford MSc: Statistics, University of Oxford BS: Applied Mathematics and Economics, Yale University His research focuses on building robust, transparent, and trustworthy machine learning systems, particularly for high-stakes applications. He develops probabilistic models that improve generalization under distribution shifts, provide reliable uncertainty estimates, and enable fair and interpretable predictions. His work spans generative models, large language models, healthcare, and biomedical discovery. The recent publications highlight a strong trend toward function-space modeling, Bayesian regularization, and AI safety. Tim's work emphasizes principled uncertainty quantification, robustness to subpopulation and semantic shifts, and the development of frameworks for AI governance and specification. His research bridges theoretical advances with real-world applications, especially in safety-critical domains like medicine and defense. Tim has received numerous accolades including being named a Rhodes Scholar, Qualcomm Innovation Fellow, and 2024 Rising Star in Generative AI. He was awarded a $700,000 Foundational Research Grant and a $30,000 Apple Seed Grant for improving LLM trustworthiness. Rhodes Scholar Qualcomm Innovation Fellow AISTATS Notable Paper Award (2024) Outstanding Paper Award, ICLR GenAI4DM Workshop (2024) Apple Seed Grant ($30,000) Foundational Research Grant ($700,000) NeurIPS Spotlight Talk 2024 Rising Star in Generative AI He actively mentors students, particularly first-generation and low-income scholars, and has contributed to major policy frameworks including the OECD AI Classification Framework and a series of CSET issue briefs on AI safety. His work demonstrates a strong commitment to responsible AI development, combining technical rigor with societal impact. Tim leads research efforts at the intersection of machine learning theory and practical deployment, with ongoing projects in generative modeling, reliable LLMs, and AI governance. His lab produces high-impact work regularly published at top-tier conferences such as NeurIPS, ICML, and AISTATS.

Tim Conleyمشاهده پروفایل

استاد

• Econometrics
• Development Economics
• Empirical Industrial Organization
• +۳ مورد دیگر

Tim Conley is Professor and Chair at the Department of Economics, University of Western Ontario. He holds a Ph.D. from the University of Chicago (1996). His research focuses on applied econometrics with emphasis on spatial dependence, cross-sectional analysis, and empirical industrial organization. His primary research interests include methodological development in econometrics, particularly around dependence modeling in cross-sectional data and spatial analysis techniques. He has made significant contributions to understanding technology adoption in developing economies and detection of collusion in market mechanisms. Professor Conley's publications demonstrate consistent focus on developing robust statistical methods for economic applications, with recent work emphasizing practical applications in policy evaluation and market analysis. His methodological innovations have been implemented in statistical software packages used by researchers worldwide.

Gavin McNicolمشاهده پروفایل

استادیار

• Soil Biogeochemistry
• Biosphere-Atmosphere Exchange
• Wetland Ecology
• +۳ مورد دیگر

Gavin McNicol is an Assistant Professor in the Department of Earth and Environmental Sciences at the University of Illinois at Chicago (UIC). His research focuses on soil biogeochemistry and its connection to Earth’s climate system, particularly methane emissions from wetlands, temperate rainforests, and waste systems. He employs field measurements, laboratory experiments, and data science to study greenhouse gas dynamics across scales. McNicol teaches courses on data science (EAES 420) and climate-ecosystem interactions (EAES 579). His work integrates machine learning with satellite remote sensing to monitor global wetland methane emissions. Key collaborations include FLUXNET-CH4, CRMRCN, and the SOIL NGO in Haiti. McNicol holds a BS from the University of Stirling (2010) and a PhD from UC Berkeley (2016). Research interests span wetland methane budgets, carbon cycling in coastal ecosystems, and climate impacts of sanitation systems. He has secured grants from NASA, DOE, and NSF, totaling over $87,000. His team, the McNicol Lab, emphasizes interdisciplinary approaches combining fieldwork, lab analysis, and computational modeling. Recent publications (2023–2025) address global methane upscaling, tropical wetland monitoring gaps, and boreal-Arctic methane feedbacks. McNicol’s work bridges local measurements to global climate models, with applications in climate change mitigation and sustainable development.

Parastoo Abtahiمشاهده پروفایل

استادیار

• Human-Computer Interaction
• Augmented Reality
• Virtual Reality
• +۷ مورد دیگر

Parastoo Abtahi is an Assistant Professor in the Computer Science Department at Princeton University. She leads the Situated Interactions Lab (Ψ Lab) as part of the Princeton HCI Group, focusing on AR/VR and spatial computing. Prior to Princeton, she worked at Meta Reality Labs Research. PhD in Computer Science from Stanford University BSc in Electrical and Computer Engineering from University of Toronto (Engineering Science program) Her research explores wearable interactive technologies that augment human intelligence in physical contexts through: Input on-the-go: Low-effort, privacy-preserving multimodal interfaces Intelligent output: Timely, minimal multisensory systems Situated AI: Personalizable, predictable, safe physical-digital interaction Recent publications analyze: Drone-based haptic illusions for AR/VR Microgestures for mobile AR input Interactivity in explainable AI systems Temporal dynamics in VR haptics Awards include: 2025 Google Research Scholar Award CHI 2019 & 2018 Honorable Mentions She teaches courses like: COS 436: Human-Computer Interaction COS IW: AR Meets AI

John Carruthersمشاهده پروفایل

دانشیار

• Sustainable Urban Development
• Economic Geography
• Urban and Regional Economics
• +۲ مورد دیگر

John Carruthers is an Associate Professor and Director of Graduate Studies in the Department of City and Regional Planning at Cornell University, affiliated with the Carl Sagan Institute and the AAP school. His research bridges regional science and urban planning. Ph.D. in Regional Science, University of Washington (2001) M.S. in Regional Science, University of Arizona (1998) B.A. in Economics, Hunter College, CUNY (1996) Carruthers specializes in Sustainable Urban Development , Economic Geography , and Geospatial Analysis , focusing on environmental remediation in Puget Sound and public amenities in Seoul. His work employs spatial econometrics and input-output analysis to address urban challenges. His recent publications in journals like International Regional Science Review and Journal of Regional Science explore Land Use Policy , Urban Growth Patterns , and Environmental Valuation . George Washington Award (2019) Distinguished Leadership Award for a Planning Educator (2016) Carruthers has led grants such as the Estimating the Public Benefits of Green Space in the Seoul Metropolitan Area project (Korea Development Institute, $75,000). He teaches courses on regional economic impact analysis and climate change economics.

• Macroeconomics
• Monetary Policy
• Heterogeneous Agent Models
• +۲ مورد دیگر

Aarti Singh is Associate Professor of Economics at the University of Sydney, specializing in macroeconomics and monetary policy. She serves as Associate Editor for the Journal of Money, Credit and Banking and the Journal of Economic Dynamics and Control. Her research examines optimal monetary policies in economies with heterogeneous agents, sectoral interdependencies, and incomplete markets. Singh collaborates with central banks globally and has held visiting positions at Cornell, Oxford, and the Federal Reserve Bank of St. Louis. Recent work analyzes how tax progressivity affects consumption insurance and the labor market impacts of monetary shocks. Grants include an ARC DECRA on human capital risk.

• Computer Security
• Privacy
• Applied Cryptography
• +۶ مورد دیگر

Aggelos Kiayias FRSE is Chair in Cyber Security and Privacy and Director of the Blockchain Technology Laboratory at the University of Edinburgh. He is also Chief Scientist at blockchain technology company Input Output. His academic work spans over two decades with more than 200 publications in cryptography, blockchain, and security. Dr. Kiayias received his Ph.D. from the City University of New York and was an undergraduate at the University of Athens Mathematics department. His research focuses on computer security, privacy, applied cryptography, and foundations of cryptography with particular emphasis on blockchain technologies, distributed systems, e-voting, secure multiparty protocols, and identity management. His recent work demonstrates continued innovation across multiple dimensions of blockchain technology, with publications spanning theoretical foundations, practical implementations, economic modeling, and privacy-preserving techniques. The research output shows strong emphasis on security analysis, consensus protocols, transaction processing, and economic incentives within decentralized systems. His work bridges theoretical cryptography with real-world blockchain applications. Among his notable recognitions are an ERC Starting Grant, Marie Curie fellowship, NSF Career Award, Fulbright Fellowship, election as Fellow of the Royal Society of Edinburgh in 2021, and the BCS Lovelace Medal in 2024. He has served as program chair for major conferences including the Cryptographers' Track of RSA (2011), Financial Cryptography (2017), Real World Crypto Symposium (2020), and Public-Key Cryptography Conference (2020), and as general chair of Eurocrypt 2013. Professor Kiayias has supervised over 20 PhD students, many of whom have gone on to academic positions at institutions including Imperial College, Stanford University, Royal Holloway University London, University of Glasgow, University of Sydney, and Virginia Commonwealth University. His current advisees include Yu Shen, Amirreza Sarencheh, and Christina Ovezik with expected graduations between 2025-2026. He leads the Blockchain Technology Laboratory at the University of Edinburgh and is involved in several major blockchain research projects including Panoramix and Fentec. His research has received significant funding from the European Union (Horizon 2020, ERC), UK research councils (EPSRC), US agencies (NSF, DHS, NIST), and Greek research bodies.

Gioele Zardiniمشاهده پروفایل

استادیار

• Co-design of complex systems
• Autonomous systems
• Transportation systems
• +۴ مورد دیگر

Gioele Zardini is the Rudge (1948) and Nancy Allen Assistant Professor at MIT's Department of Civil and Environmental Engineering (CEE), with affiliations to the Laboratory for Information and Decision Systems (LIDS) and the Institute for Data, Systems, and Society (IDSS). He holds a PhD from ETH Zurich and previously worked as a postdoctoral scholar at Stanford University. His research focuses on co-design of complex systems, autonomous systems, and game-theoretic modeling of transportation networks. Education: BSc and MSc in Mechanical Engineering and Robotics from ETH Zurich (2017–2019), PhD in 2023. He has held visiting roles at nuTonomy Singapore, Stanford, and MIT. Research interests include co-design methodologies, autonomous vehicle systems, compositionality in engineering, and strategic interactions in mobility networks. Recent work emphasizes scalable fleet coordination, safety-critical robotics, and user-centric transportation solutions. Notable awards include the 2024 ETH Doctoral Dissertation Award (Silver Medal), Best Paper at ITSC 2021, and federal grants for enhancing urban transit equity. He leads the Zardini Lab, fostering interdisciplinary collaboration in systems engineering and autonomy. Grants and advising: Received federal grants for transit accessibility projects. His work on Autonomy Talks has produced over 180 recorded lectures, promoting knowledge exchange in autonomous systems. Labs/Teams: Principal Investigator at LIDS, affiliate at IDSS, and founder of the Zardini Lab, focusing on systems co-design, mobility innovation, and game-theoretic frameworks.

Mohammad T. Alhawaryمشاهده پروفایل

استاد

• Arabic Second Language Acquisition
• Arabic Language Pedagogy
• Bilingualism
• +۹ مورد دیگر

Mohammad T. Alhawary is Professor of Arabic Linguistics and Second Language Acquisition at the University of Michigan's Middle East Studies department within the College of Literature, Science, and the Arts. He serves as Director of both the MA Program in Arabic for Professional Purposes (APP) and the MA Program in Teaching Arabic as a Foreign Language (TAFL). His educational background includes a Ph.D. from Georgetown University (1999). Prior to joining the University of Michigan, he contributed to developing Arabic and Middle Eastern Studies programs at various US institutions. Professor Alhawary's research spans both theoretical and applied Arabic linguistics, with particular focus on second language acquisition processes. His work examines how factors like age, input quality, output practice, and first language transfer affect Arabic language learning. He has made significant contributions to understanding Arabic language pedagogy, curriculum design, proficiency testing, and the application of technology in language learning. His research also extends to bilingualism, multilingualism, language impairment, and Arabic medieval grammatical traditions. His publications reflect a strong trajectory in Arabic linguistics research, with recent works focusing on practical language teaching applications, reading comprehension mechanisms, code-switching patterns in digital communication, and multilingual acquisition processes. The 2023 publication 'Teaching Arabic as a Foreign Language' represents his latest contribution to language pedagogy methodology. 2019 AATA Book Award for 'Arabic Second Language Learning and Effects of Input, Transfer, and Typology' As an academic leader, Professor Alhawary serves as Executive Director of the American Association of Teachers of Arabic and edits both the Journal of Arabic Linguistics Tradition and Al-'Arabiyya journal. He continues to develop empirical research on Arabic second language acquisition to inform teaching practices both in America and globally.

Marina Blantonمشاهده پروفایل

دانشیار

• Applied Cryptography
• Information Security
• Privacy-Preserving Computation
• +۳ مورد دیگر

Marina Blanton is an Associate Professor in the Department of Computer Science and Engineering at the University at Buffalo, and Faculty Director of Women in Science and Engineering within the School of Engineering and Applied Sciences. She holds a PhD in Computer Science from Purdue University (2007), along with multiple advanced degrees in Computer Science and Electrical Engineering from prestigious institutions in the US and Russia. Her research focuses on applied cryptography, information security, and privacy-preserving computation and outsourcing. She has pioneered work on secure multi-party computation protocols, privacy-preserving biometric authentication, and secure data analytics across distributed systems. Her contributions include foundational frameworks like PICCO, a compiler for private distributed computation, and advancements in protocols for genomic data analysis and floating-point secure computation. Blanton has been recognized with numerous awards, including IEEE and ACM Senior Membership (2016/2015), the ACM CCS Test of Time Award (2015), and the AFOSR Young Investigator Award (2013). Her research has been supported by grants such as NSF SaTC awards and AFOSR funding. Her work emphasizes practical implementations of secure computation, with applications in healthcare, biometrics, and distributed data systems. She has advised numerous students and contributed to educational initiatives promoting women in STEM through her leadership roles.

• Climate Change Economics
• Carbon Footprints
• Air Pollution and Health
• +۴ مورد دیگر

Dr. Zhifu Mi is a Professor of Climate Change Economics at the Bartlett School of Sustainable Construction , University College London. His research focuses on carbon footprint analysis, climate change economics, air pollution and health, sharing economy sustainability, and input-output modeling. He has published extensively in top journals like Nature Sustainability , Lancet , and Science Advances . Co-Editor-in-Chief, Structural Change and Economic Dynamics (2020–present) Executive Editor, Journal of Cleaner Production (2019–present) President, Chinese Economic Association (UK/Europe) Council Member, International Input-Output Association Fellow of the Royal Geographical Society His research explores: Carbon Footprints: Economic development and emission convergence in Chinese households Climate-Health Linkages: Air pollution impacts, ultra-low emission policies Sharing Economy: Sustainable societies through shared micro-mobility Policy Analysis: Synergies between environmental regulations Recent publications analyze decarbonization employment gaps, polycentric urban structures, and health-environment policy intersections. Awards include the World Sustainability Award (2018), multiple Clarivate Highly Cited Researcher honors, and UCL's Outstanding Research Supervision Award (2022). He teaches modules on construction economics and input-output analysis.

Andrei A. Levchenkoمشاهده پروفایل

استاد

• International Economics
• Macroeconomics
• Development Economics
• +۵ مورد دیگر

Andrei A. Levchenko is the John W. Sweetland Professor of International Economics at the University of Michigan's Department of Economics. He holds affiliations with prominent institutions including NBER, CEPR, and CEBRA, where he directs the International Trade and Macroeconomics Program. His research focuses on international trade, global production networks, business cycle transmission, and the macroeconomic implications of institutional changes. Levchenko's work bridges micro and macroeconomics, analyzing firm-level data to understand aggregate phenomena. Key contributions include studies on global supply chains' role in economic fluctuations, the impact of industrial policy on long-term growth, and the distributional consequences of large devaluations. He has been recognized with the Bhagwati Award and featured in the Economic Report of the President multiple times. His research spans topics such as trade elasticities, inflation dynamics, and the intergenerational trade-offs of pandemic lockdowns. Levchenko collaborates with leading economists globally, producing influential papers in top journals like the American Economic Review and Review of Economic Studies. His Google Scholar profile highlights over 10,000 citations, underscoring his significant impact on modern international economics. Education: Not explicitly listed in the provided materials. Affiliations: NBER Research Associate, CEPR Research Fellow, CEBRA Director of ITM Program. Grants & Awards: Bhagwati Award (2021/2022), multiple NBER/CEPR working papers, and contributions to policy dialogues via IMF and World Bank collaborations.