جست‌وجوی استاد و پژوهشگر

Abhijit Banerjeeمشاهده پروفایل

استاد

• Economics
• Development Economics
• Public Health Policy
• +۳ مورد دیگر

Abhijit Banerjee is a Professor in the Department of Economics at the Massachusetts Institute of Technology (MIT). His research focuses on development economics, public health policy, and social protection programs, particularly addressing poverty and inequality in low- and middle-income countries. He has conducted large-scale experiments evaluating interventions such as conditional cash transfers, universal basic income, and healthcare policies. Key areas of interest include the design and implementation of anti-poverty programs, behavioral economics, and the long-term health impacts of infectious diseases like COVID-19. His work often integrates experimental methods to assess policy effectiveness, with contributions to global health studies and economic development strategies. Notably, his research on the RECOVERY trial evaluates treatments for hospitalized COVID-19 patients, while other studies explore financial spillover effects of electronic government transfers in Indonesia and savings behavior interventions in Chile. Banerjee has collaborated on projects analyzing post-COVID-19 health outcomes, labor market dynamics in India, and the role of trusted messengers in public health communication during crises. Despite the breadth of his contributions, specific details about his educational background, grants, or lab affiliations are not explicitly provided in the source text.

Adriana Kovashkaمشاهده پروفایل

دانشیار

• Computer Vision
• Machine Learning
• Natural Language Processing
• +۷ مورد دیگر

Adriana Kovashka is an Associate Professor at the University of Pittsburgh , affiliated with the School of Computing and Information and serving as Department Chair . Her academic journey began with BA degrees in Computer Science and Media Studies from Pomona College (2008) and a PhD in Computer Science from The University of Texas at Austin (2014). Joined Pitt’s faculty in January 2015 NSF CAREER awardee (2021) Google Faculty Research Award recipient Dr. Kovashka’s research spans Computer Vision , Machine Learning , and Natural Language Processing , focusing on visual rhetoric, weak multimodal supervision, and domain adaptation. She pioneered techniques for analyzing political imagery, developing robust object detection frameworks, and exploring the intersection of visual and textual persuasion through large-scale annotated datasets. Her recent work emphasizes geographic diversity in vision-language systems, audio-visual fusion for domain generalization, and shape-texture bias mitigation in CNNs. Key publications include groundbreaking studies on symbolic reasoning, multimodal dialogue systems, and ethical AI applications in education. Scientific honors include: NSF CRII Award (2016) NSF CAREER Award (2021) Pitt CRDF Award (2016, 2018) Best Paper at ECV Workshop (2021) Google Faculty Research Award (2016, 2018) Dr. Kovashka actively mentors students in multimodal learning projects and collaborates with interdisciplinary teams on NSF-funded initiatives. She co-organizes workshops like the first CVPR workshop on advertisement understanding and leads research groups exploring human-AI co-learning systems.

Daniel Epsteinمشاهده پروفایل

دانشیار

• Human-Computer Interaction
• Ubiquitous Computing
• Social Computing
• +۶ مورد دیگر

Daniel Epstein is an Associate Professor in the Department of Informatics at the University of California, Irvine (UCI), where he leads the Personal Informatics Everyday (PIE) Lab. He holds a courtesy appointment in the Department of Computer Science and is affiliated with the Connected Learning Lab, Institute for Future Health, and Accessibility Research Collective. Epstein earned his Ph.D. in Computer Science & Engineering from the University of Washington and a B.S. in Computer Science from the University of Virginia. His research focuses on how personal tracking technology can better serve diverse users' needs, emphasizing ethical design, health equity, and long-term user engagement. Notable areas include pregnancy tracking, wearable technology for children and ADHD management, and AI-driven health chatbots. Epstein has received grants from NSF, Snap Inc., and UCI programs, totaling over $650k in funding. Epstein's work bridges HCI and health informatics, with over 60 peer-reviewed publications. He advises six Ph.D. students and has mentored numerous undergraduates. Awards include the ACM Senior Member distinction (2025), CHI Best Paper (2023), and NSF CAREER Award (2023). Professional service includes program committees for CHI, CSCW, and UbiComp, plus leadership roles in workshops like the Workgroup on Interactive Systems in Healthcare (WISH). Beyond academia, Epstein enjoys hiking, collecting turtle figures, and advocating for accessible technology.

Richard M. Murrayمشاهده پروفایل

استاد

• Control Theory
• Autonomous Vehicles
• Biological Circuit Design
• +۳ مورد دیگر

Richard M. Murray is the Thomas E. and Doris Everhart Professor of Control and Dynamical Systems and Bioengineering at the California Institute of Technology (Caltech). He holds a B.S. from Caltech (1985), M.S. from UC Berkeley (1988), and Ph.D. from UC Berkeley (1990). He has served in academic roles from Assistant Professor (1991–1997) to his current endowed professorship. He chaired the Engineering and Applied Science division (2000–2005) and Biology and Biological Engineering (2020–2024). His research focuses on feedback control in biological and autonomous systems, synthetic cells, and networked control systems. Collaborators include experts in robotics, synthetic biology, and systems biology. Key awards include the IEEE Control Systems Award and election to the National Academy of Engineering. His educational contributions span courses on control systems, robotics, and bioengineering. Current research projects include the Developer Cell initiative (Sloan Foundation), layered testing for autonomous systems (AFOSR), and microbiome-based environmental solutions (CHARMME, ARO). He advises numerous graduate students and postdocs, with notable alumni in academia and industry. Labs include facilities in Keck and Steele laboratories at Caltech. His work bridges control theory, synthetic biology, and autonomous systems to address societal challenges like environmental monitoring and safe autonomy.

Kingsley Edneyمشاهده پروفایل

دانشیار

• International Relations
• Chinese Politics
• Soft Power
• +۴ مورد دیگر

Dr Kingsley Edney is an Associate Professor in International Relations of China at the University of Leeds' School of Politics and International Studies. He holds a PhD (International Relations) and MA (Political Science) from the University of Melbourne, along with a BA(Hons) in Politics and Anthropology from Victoria University of Wellington. Fluent in Chinese and with experience living in Shanghai and Beijing, his research focuses on China's non-material international security dynamics, including cultural diplomacy, propaganda, and ideological strategies to manage global information flows. His expertise includes Chinese soft power, the role of ideology in foreign policy, and the intersection of domestic political cohesion with international security objectives. He teaches undergraduate and master's courses on China's domestic and international politics. Current postgraduate researchers under his supervision are Jinru Huang, Yanyu Lu, and Hengfeng Zhao. Edney's research outputs span topics like public perceptions of China in the Anglosphere, Chinese youth nationalism, and environmental governance. His work often bridges theoretical frameworks with empirical analysis of China's evolving global engagement strategies. He maintains active academic engagement through platforms like Google Scholar and ORCID.

Anna S. Mattilaمشاهده پروفایل

استاد

• Social Media
• Service Recovery
• Servicescape
• +۸ مورد دیگر

Anna S. Mattila is the Marriott Professor of Lodging Management and serves as Professor-in-Charge of the Graduate Program at the School of Hospitality Management, Pennsylvania State University. Her research spans social media, service recovery, servicescape, prosocial behaviors, cross-cultural studies, and wellness in hospitality contexts. Education : B.S. and Ph.D. from Cornell University, M.B.A. from University of Hartford Mattila's work examines how emotions, cultural norms, and technological innovations like AI influence consumer decisions in hospitality. Her studies cover topics from robotic service interactions to sustainable food marketing and moral psychology in tourism. She has published extensively in journals such as International Journal of Hospitality Management and Journal of Consumer Marketing . Her recent articles focus on AI integration in hospitality, consumer trust in virtual influencers, upcycled food adoption, and the psychological effects of servicescape design. Key themes include ethical consumption, digital transformation, and cross-cultural consumer behavior. Advising : Supervised Anqi Luo's dissertation on service recovery in 2022 Mattila's office is located in 224 Mateer Building, University Park, PA. She contributes to advancing hospitality research through methodological consulting and the Penn State Biomarker Core Laboratory.

Hans Beckمشاهده پروفایل

استاد

• History and culture of ancient Greece
• Historical geography of Greece
• Historical environmental studies of ancient Greece
• +۵ مورد دیگر

Hans Beck serves as Professor of Greek History at the University of Münster (Westfälische Wilhelms-Universität) since 2018, with an additional appointment as Adjunct Professor in the Faculty of Arts at McGill University. His academic career includes previous positions as Professor of Ancient History and Director of Classical Studies at McGill University (2005-2018), Heisenberg Fellow at Goethe-Universität Frankfurt (2004-2005), and Research Assistant at the University of Cologne (1997-2004). Beck earned his academic training through doctoral studies at the Universities of Erlangen, Canterbury, and Cambridge (1989-1996), followed by a fellowship at the Center for Hellenic Studies in Washington, DC (2001-2002). His educational background reflects a strong international foundation in classical studies. His research spans multiple interconnected fields within ancient history, with particular emphasis on the history and culture of ancient Greece, historical geography of Greece, environmental studies of the ancient Greek world, political culture of the Roman Republic, and ancient historiography. Beck's work consistently explores themes of localism, federalism, and political structures across ancient societies, with notable contributions to understanding Greek city-states, regional identities, and comparative political systems. His approach often bridges geographical, historical, and cultural perspectives to examine how ancient communities organized themselves politically and maintained regional identities within larger frameworks. Analyzing his recent publications reveals a sustained focus on local political structures within broader contexts, particularly examining how Greek city-states maintained autonomy while participating in federal leagues. His work increasingly incorporates comparative approaches, connecting Greek political structures with those of Rome and even ancient China, reflecting his editorial work on cross-cultural studies. Beck demonstrates particular expertise in analyzing how physical landscapes shaped political organization and how religious practices reinforced regional identities. Fellow of the Royal Society of Canada (2018) Anneliese Maier Research Award from Alexander von Humboldt Foundation (2014) Heisenberg Fellowship from Deutsche Forschungsgemeinschaft (2004) Doctoral scholarship from German Academic Exchange Service (1995) Doctoral scholarship from Hanns Seidel Foundation (1994) Beck has supervised numerous doctoral students including Jordan Christopher (2022), Chandra Giroux (2021), Wentian Fu (2020), Rebecca Robinson (2017), Alex McAuley (2015), and François Gauthier (2015), covering diverse topics from ancient Qin and Macedon to cult practices in ancient empires. His academic leadership extends to directing research projects B3-49 'Belonging in/to Lakonia' and B3-40 'Localism and Religion in Ancient Greece' within the Excellence Cluster focusing on 'Religious Diversity and Legal-Political Unity.' As head of the project 'Belonging in/to Lakonia' and 'Localism and Religion in Ancient Greece,' Beck leads interdisciplinary research teams examining archaeological and historical evidence from the Sanctuary of Apollo at Amyklai and its surroundings. His work integrates textual analysis with material culture studies, creating comprehensive approaches to understanding ancient regional identities and religious practices. Beck's leadership in these projects demonstrates his commitment to bridging traditional disciplinary boundaries in classical studies.

Ian Goldbergمشاهده پروفایل

استاد

• Security
• Privacy
• Privacy-Enhancing Technologies (PETs)
• +۵ مورد دیگر

Ian Goldberg is a Professor at the Cheriton School of Computer Science , University of Waterloo, Canada. He holds the Canada Research Chair in Privacy Enhancing Technologies and leads the Cryptography, Security, and Privacy (CrySP) group . He is affiliated with the Cybersecurity and Privacy Institute and the Institute for Quantum Computing . Research Focus: Security, privacy, and privacy-enhancing technologies (PETs) for the Internet, including Off-the-Record (OTR) Messaging , censorship resistance , private information retrieval , and zero-knowledge proofs . Recent Publications: His work addresses metadata protection , deniable authentication , and secure multi-party computation , with applications to anonymous communication and censorship resistance. Scientific Awards: Canada Research Chair in Privacy Enhancing Technologies Students: He advises current and former PhD/Master’s students in projects like Lox , PRSONA , Walkie-Talkie , and SkypeMorph . Notable advisees include Sajin Sasy (Privacy-Preserving Communications), Justin Tracey (PETs Development), and Tao Wang (Website Fingerprinting Defenses). Labs & Teams: Goldberg is a core member of the CrySP group and contributes to the Tor Project and Off-the-Record Messaging open-source initiatives. His research bridges theoretical and applied cryptography, with deployments in real-world systems like Tor and PIR protocols.

Granger Morganمشاهده پروفایل

استاد

• Energy Policy
• Climate Change
• Electric Power Systems
• +۳ مورد دیگر

Granger Morgan is the Hamerschlag University Professor of Engineering at Carnegie Mellon University, holding joint appointments in the Department of Electrical and Computer Engineering, the Department of Engineering and Public Policy, and the H. John Heinz III College. His research focuses on science, technology, and public policy, particularly energy systems, climate change, risk analysis, and regulatory frameworks. He co-directs the NSF Center for Climate and Energy Decision Making and the Electricity Industry Center. Education: Ph.D., Applied Physics and Information Science, University of California, San Diego (1969) M.S., Astronomy and Space Science, Cornell University (1965) B.A., Physics, Harvard College (1963) Research Interests: Energy decarbonization and electric power resilience Climate change mitigation and adaptation strategies Risk assessment and policy analysis Hydrogen and nuclear energy systems Global technology adoption dynamics Awards and Affiliations: FAS Public Service Award (2016) Member, National Academy of Sciences Fellow, AAAS, IEEE, and Society for Risk Analysis National Academies Report Review Committee Co-Chair Advisory roles at DOE, PNNL, and international energy councils Advisory and Grants: Leadership in national studies on electric grid resilience and hydrogen infrastructure Recipient of NSF and industry-funded research grants Guidance on global energy policy and regulatory frameworks Labs and Teams: NSF Center for Climate and Energy Decision Making (co-director) Carnegie Mellon Electricity Industry Center Interdisciplinary energy policy research groups

Lin Tanمشاهده پروفایل

استاد

• Software-AI synergy
• Software dependability
• Software engineering
• +۷ مورد دیگر

Lin Tan is a Professor of Computer Science at Purdue University , holding the Mary J. Elmore New Frontiers Professorship . She joined Purdue in 2019 after serving as a Canada Research Chair and associate professor at the University of Waterloo. She is an ACM Distinguished Member and IEEE Senior Member . Education: PhD in Computer Science, University of Illinois Urbana-Champaign BS in Computer Science and Technology, Zhejiang University Research Interests: Professor Tan’s research lies at the intersection of software engineering , artificial intelligence , and security . Her work focuses on software-AI synergy , software dependability , defect detection & repair , and software text analytics . She leverages machine learning and natural language processing to enhance software reliability, and conversely uses software techniques to improve the dependability of AI systems. Her recent projects include building binary foundation models (Nova), evaluating large language models for code generation and repair, and developing interactive debugging tools that reduce debugging time by one-third. She also explores robot task planning with LLMs and automated front-end development . Awards & Honors: Best Paper Award Finalist, ICRA 2025 ELATES Fellow, 2024-2025 ACM SIGSAC Distinguished Paper Award, CCS 2024 J.P.Morgan AI Faculty Research Awards (2020, 2021, 2022) ACM SIGSOFT Distinguished Paper Awards (ASE 2020, MSR 2018, FSE 2016) Canada Research Chair (2017) Ontario Early Researcher Award (2015) NSERC Discovery Accelerator Supplements Award (2015) Google Faculty Research Awards (2010, 2014) IEEE Micro Top Picks (2006) Advising & Funding: Professor Tan currently advises eight PhD students and has graduated 20+ PhD and Master’s students now thriving in academia (York University, Concordia University, University of Alberta) and industry (Microsoft, Meta, Amazon, Google). Her group is generously supported by NSF , Meta/Facebook Research Awards , J.P.Morgan AI Faculty Awards , and NSF REU programs. Labs & Teams: She leads the Software Reliability & AI Lab at Purdue, recruiting postdocs, PhD, MS, and undergraduate researchers year-round. Lab interests span binary recovery , LLM-based program repair , testing deep-learning libraries , and data-free model extraction .

Terry C. Lansdownمشاهده پروفایل

دانشیار

• Human Factors
• Transport Safety
• Driver Behavior
• +۷ مورد دیگر

Terry C. Lansdown is an Associate Professor in the School of Social Sciences and Department of Psychology at Heriot-Watt University. His expertise lies in Human Factors, particularly focusing on driver safety, workload management, and attentional distraction in transportation contexts. Prior to his academic role, he worked as a senior researcher at the Transport Research Laboratory, contributing to numerous EU-funded and government-sponsored projects. His research integrates ergonomics principles with real-world applications, addressing issues like automated driving systems, social distractions in vehicles, and occupational health in construction industries. Key research interests include: Driver behavior and road safety Human factors in automated systems Workload and attentional demands in complex tasks Health and safety in small-to-medium enterprises (SMEs) He has led studies on pandemic response strategies, such as the CHARIS project analyzing behavioral adherence during the COVID-19 crisis. Lansdown’s work frequently bridges psychological theory with practical interventions, including text messaging campaigns to improve construction worker safety and experimental designs to evaluate automation failure responses. Collaborations span academic and industrial sectors, with publications addressing topics ranging from UV exposure in outdoor workers to the cognitive impacts of in-vehicle distractions. His contributions align with UN Sustainable Development Goals related to health (SDG 3) and sustainable cities (SDG 11).

Arno Solinمشاهده پروفایل

دانشیار

• Machine Learning
• Signal Processing
• Sensor Fusion
• +۸ مورد دیگر

Dr. Arno Solin is a tenured Associate Professor in Machine Learning at Aalto University's Department of Computer Science and an Academy of Finland Research Fellow . He leads the Aalto machine learning research group and serves as Director of the Finnish Doctoral Program Network in AI (AI-DOC) . His work bridges probabilistic modeling with practical applications in sensor fusion and real-time inference. ELLIS Scholar (European Laboratory for Learning and Intelligent Systems) Adjunct Professor at Tampere University Member of Young Academy Finland (2021–2025) Research Interests focus on data-efficient machine learning with probabilistic methods for real-time inference and sensor fusion. Key areas include Gaussian processes, diffusion models, stochastic differential equations, and uncertainty quantification in deep learning. His group develops methods that combine structural constraints with adaptive learning for deployment on resource-limited hardware. Publication Trends show consistent output in top venues (NeurIPS, ICML, ICLR, AISTATS) with emphasis on diffusion models , 3D scene reconstruction , and real-time probabilistic modeling . Recent works explore physics-informed learning, heterophily-aware graph models, and compressed representations for world models in reinforcement learning. Scientific Recognition : Awarded AI Researcher of the Year 2024 by AI Finland Teacher of the Year 2023 at Aalto CS ISIF Jean-Pierre Le Cadre Best Paper Award (2018) MLSP Schizophrenia Classification Challenge Winner (2014) NeurIPS/ICML Reviewer Awards Research Leadership includes coordinating Finland's AI Center of Excellence program and directing the Finnish Doctoral Program Network in AI (AI-DOC). He supervises 15+ doctoral/postdoctoral researchers and has spun off Spectacular AI , a company commercializing sensor fusion technology.

Kimon Fountoulakisمشاهده پروفایل

دانشیار

• Machine Learning on Graphs
• Numerical Optimization
• Graph Algorithms
• +۲ مورد دیگر

Kimon Fountoulakis is an Associate Professor at the University of Waterloo. His research focuses on Machine Learning on Graphs and Numerical Optimization, with a strong emphasis on algorithmic methods for graph-structured data. He holds a Ph.D. from The University of Edinburgh (2015), an M.Sc. from The University of Edinburgh (2010), and a B.Sc. from Athens University of Economics and Business (2009). His work spans theoretical foundations and practical applications in graph algorithms, optimization, and machine learning. Research interests include graph neural networks, local graph clustering algorithms, and algorithmic reasoning. His contributions address challenges in graph representation learning, message-passing architectures, and scalable optimization methods. Notable themes in his publications include improving counting abilities of vision-language models, analyzing graph convolutions, and developing flow-based clustering techniques with statistical guarantees. His work often bridges theory and practice, with applications in network analysis, pandemic containment strategies, and high-performance computing. While no specific grants or awards are listed, his research demonstrates significant contributions to graph-based machine learning and optimization. He maintains a research group at the University of Waterloo, with a focus on developing open-source tools and frameworks for graph algorithms. His lab’s work emphasizes local graph clustering methods and their scalability in real-world networks.

Elias Dinasمشاهده پروفایل

استاد

• Political Socialization
• Authoritarian and Post-Authoritarian Politics
• Political Methodology
• +۶ مورد دیگر

Elias Dinas is a Full-time Professor in the Department of Political and Social Sciences at the European University Institute (EUI). He holds the Swiss Chair in Federalism, Democracy, and International Governance. His research focuses on political socialization, authoritarian legacies, and research methodology. Dinas earned his PhD in Political Science from the EUI in 2010. His research interests include the impact of historical traumas on political attitudes, experimental methods, and the dynamics of norm change. He collaborates with institutions like the Graduate Institute in Geneva through seminars, conferences, and methodological workshops. Recent work explores topics such as ideology mapping via AI, the electoral effects of early voting experiences, and the interplay between migration crises and public policy. His research has been published in top journals like the American Political Science Review and highlighted in outlets like The New York Times. Received the Michael Wallerstein Award (2019) for his work on migration and hostility. Supervises 14 students researching memory politics, norm change, and intergroup relations. Leads projects on post-authoritarian ideologies, German political identity, and elite-driven norm erosion. His teaching and supervision emphasize causal inference, experimental design, and quantitative methods, reflecting his commitment to rigorous political analysis.

Sebastian Riedelمشاهده پروفایل

استاد

• Natural Language Processing (NLP)
• Machine Learning
• Artificial Intelligence
• +۳ مورد دیگر

Sebastian Riedel is a Professor at University College London (UCL) and a Researcher at DeepMind, leading the UCL NLP Lab. His work focuses on teaching machines to read, reason, and write, integrating Natural Language Processing (NLP) with Machine Learning. He holds an Allen Distinguished Investigator award and has held roles at FAIR, UMass Amherst, Tokyo University, and the University of Edinburgh. Education: PhD in Computer Science from the University of Edinburgh (advisor: Ewan Klein), postdoctoral research at UMass Amherst (advisor: Andrew McCallum), and research at Tokyo University (advisor: Tsujii Junichi). Research Interests: NLP, machine learning, information extraction, and multimodal models like Gemini. He develops tools such as UCLEED (BioNLP event extractor), frontlets (Scala map wrappers), and thebibbrag (BibTeX to HTML converter). Awards: Allen Distinguished Investigator. Software contributions include GitHub repositories for NLP, machine learning, and data tools. Contact: s.riedel@ucl.ac.uk | Office: 1st Floor, 90 High Holborn, London WC1V 6LJ | Office Hours: Mondays 11 AM–12 PM.