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Dawn SongView profile

Professor

• Artificial Intelligence
• Cybersecurity
• Machine Learning
• +7 more

Dawn Song is a Professor in the Department of Electrical Engineering and Computer Science at the University of California, Berkeley, affiliated with multiple research centers including the Berkeley Artificial Intelligence Research Lab (BAIR) and the Berkeley Center for Responsible, Decentralized Intelligence (RDI). She holds leadership roles in AI safety, cybersecurity, and blockchain research. Her work bridges machine learning, security, and distributed systems, with notable contributions to formal verification, privacy-preserving technologies, and AI governance. Education: Ph.D. (2002) and M.S. (1999) in Computer Science from UC Berkeley and Carnegie Mellon University, respectively. She previously served as an Assistant Professor at Carnegie Mellon University before joining UC Berkeley in 2007. Research Interests: Dawn's work focuses on AI safety, cybersecurity, and the ethical implications of frontier AI. She explores topics such as large language model vulnerabilities, zero-knowledge proofs, blockchain security, and policy frameworks for AI governance. Her research combines theoretical rigor with practical applications, addressing challenges in secure systems, adversarial machine learning, and privacy-preserving computation. Publications: Her recent work includes groundbreaking studies on LLM memorization, smart contract decompilation, and AI agent cybersecurity evaluation. She also leads initiatives like the Singapore Consensus and California Report on AI safety priorities, emphasizing global collaboration in risk mitigation. Notable Awards: MacArthur Fellowship (2010), ACM Fellow (2019), IEEE Fellow (2019) Advising & Grants: She advises projects on AI policy and cybersecurity, securing grants from NSF, DARPA, and industry collaborations. Her lab develops tools like CyberGym for evaluating AI agents and zkPyTorch for secure machine learning. Labs & Teams: Her research groups at UC Berkeley focus on cutting-edge projects in AI safety, blockchain, and cybersecurity, collaborating with industry leaders and policymakers to advance both technical and ethical standards.

Tianqi ChenView profile

Assistant Professor

• Machine Learning
• Deep Learning Systems
• Compiler Optimization
• +6 more

Tianqi Chen is an Assistant Professor at the Machine Learning Department and Computer Science Department of Carnegie Mellon University (CMU), with a courtesy appointment as a Professor in the Electrical and Computer Engineering Department within the College of Engineering. His research focuses on scalable machine learning systems, compiler optimization, and efficient deep learning frameworks. He holds a PhD from the Paul G. Allen School of Computer Science & Engineering at the University of Washington. Key contributions include the creation of XGBoost, Apache TVM, and MLC-LLM—widely adopted systems for machine learning and large language models. His work bridges algorithmic innovation with high-performance computing, emphasizing efficient deployment, quantization, and edge computing. Recent publications highlight advancements in LLM serving (e.g., WebLLM, Flashinfer), compiler-driven optimizations (e.g., TVM, Relax), and low-latency inference techniques (e.g., Magicdec, Tilus). These efforts address scalability, energy efficiency, and cross-platform compatibility in modern AI systems. Chen’s research has been applied to diverse domains, including music AI, browser-based inference, and microservice architectures for LLMs. His work underscores the importance of system-level thinking in advancing AI capabilities.

Claire BowernView profile

Professor

• Historical Linguistics
• Language Documentation
• Australian Indigenous Languages
• +3 more

Claire Bowern is Professor of Linguistics at Yale University specializing in historical linguistics, language documentation, and Australian Indigenous languages. Her research employs computational phylogenetics to study language evolution and supports language revitalization through digital archives and fieldwork methodologies. Recent publications address: Phylogenetic signal in lexical evolution across language families Digital infrastructure for endangered language documentation (FLEx software analysis) Decolonizing linguistics pedagogy and research practices Her work consistently integrates linguistic, anthropological, and computational approaches to analyze language diversity and change. She contributes to global databases including Grambank and D-PLACE, examining links between linguistic, cultural, and environmental patterns.

Thomas HofmannView profile

Professor

• Machine Learning
• Deep Learning
• Natural Language Understanding
• +3 more

Prof. Dr. Thomas Hofmann is a Full Professor and Head of the Department of Computer Science at ETH Zurich since 2014. He also leads the Institute for Machine Learning. His research focuses on machine learning, deep learning, natural language understanding, and text understanding. Hofmann holds a Ph.D. from the University of Bonn (1997) and has held academic positions at Brown University (1999–2004) and TU Darmstadt. He transitioned to industry as Director of Engineering at Google (2006–2014), leading the Zurich R&D center, before returning to academia. He co-founded Recommind (2000) and 1plusX (Swiss marketing tech company), currently serving as Chief Scientist and board member at 1plusX. Education: Ph.D. in Computer Science, University of Bonn (1997) Postdoctoral Work: MIT (CBCL/AI Lab), UC Berkeley (EECS/ICSI) His research explores advanced machine learning techniques, including diffusion models, generative adversarial networks, and optimization dynamics. Hofmann’s entrepreneurial ventures reflect his focus on applying AI to real-world challenges, such as e-discovery and marketing technology. His work spans theoretical contributions (e.g., neural network training dynamics, continual learning) and applied innovations (e.g., image editing, portrait generation). Hofmann actively bridges academia and industry, influencing both research and commercial AI applications.

Jason D. LeeView profile

Associate Professor

• Machine Learning
• Deep Learning
• Artificial Intelligence
• +7 more

Jason D. Lee is an associate professor of Electrical Engineering and Computer Sciences (EECS) and Statistics at the University of California, Berkeley. Previously, he held academic positions at Princeton University as an associate professor, and was a research scientist at Google DeepMind. He completed his Ph.D. in Computational and Mathematical Engineering at Stanford University under the advisement of Trevor Hastie and Jonathan Taylor. For students and collaborators, his primary contact email is jasonlee@princeton.edu, though prospective students and postdocs are asked to include "filter_student" in the subject line. Ph.D., Computational and Mathematical Engineering, Stanford University (2015) B.Sc., Mathematics, Duke University (2010) Lee's research lies at the intersection of machine learning, statistics, and optimization, focusing on the theoretical foundations of artificial intelligence. His work addresses fundamental questions in deep learning, including optimization landscapes, representation learning, and reinforcement learning theory. He has made significant contributions to understanding how gradient descent operates in neural network training and has developed provably efficient algorithms for various learning scenarios. His ten most recent publications represent a diverse yet coherent body of work across machine learning theory, focusing on topics such as Gaussian multi-index models, transformer learning capabilities, shallow neural networks, and optimization techniques. These publications appear in top venues including COLT, ICML, NeurIPS, and JMLR. Among his notable accolades are: Samsung AI Researcher of the Year Award (2023) NSF Career Award (2022) ONR Young Investigator Award (2021) Sloan Research Fellow in Computer Science (2019) NIPS Best Student Paper Award (2016) Princeton Commendation for Outstanding Teaching (ECE538B) Lee has advised numerous students including Alex Damian, Wenhao Zhan, Eshaan Nichani, Tianle Cai, Zixuan Wang, and Yunwei Ren. Former advisees have gone on to positions at institutions like NYU Courant, Facebook AI Research, UW, MIT, Duke, and Microsoft Research. His research group and collaborators span multiple institutions, working on theoretical and applied aspects of machine learning and artificial intelligence, with a particular focus on the optimization and learning dynamics of neural networks and transformer models.

Kai S. ExnerView profile

Professor

• Electrocatalysis
• Inorganic Chemistry
• Materials Science
• +7 more

Prof. Kai S. Exner is a Professor of Theoretical Inorganic Chemistry at the University of Duisburg-Essen's Faculty of Chemistry and a member of the Zentrum für Medizinische Biotechnologie (ZMB). His research focuses on electrocatalysis , particularly optimizing electrode materials for energy applications such as batteries, electrolyzers, and fuel cells. He employs computational methods like ab initio calculations and microkinetic modeling to bridge theoretical insights with experimental and industrial applications, emphasizing sustainable catalyst design without relying on noble metals. His work integrates basic research with applied medical biotechnology through ZMB collaborations, though his primary affiliation lies in the Faculty of Chemistry. Exner has pioneered concepts like the electrochemical-step asymmetry index and free-energy span model, which are critical for screening electrocatalysts. His research group, 'Theoretical Inorganic Chemistry,' actively explores mechanisms behind oxygen and chlorine evolution reactions, emphasizing selectivity control and reaction pathway complexity. Exner received the Gottschalk-Diederich-Baedeker-Preis (2024) for advancing the energy transition through foundational electrocatalysis research. He leads Aktuelles Projekt funded by third-party grants and collaborates with facilities like the Analytics Core Facility Essen (ACE) and Imaging Center Campus Essen (ICCE). His advisory role focuses on guiding theoretical and computational approaches in electrochemistry, and he has established a reputation for interdisciplinary research connecting computational chemistry with practical energy solutions.

Sham KakadeView profile

Professor

• Artificial Intelligence
• Machine Learning
• Reinforcement Learning
• +7 more

Sham Kakade is the Rampell Family Professor of Computer Science and Professor of Statistics at Harvard University, co-director of the Kempner Institute. His research focuses on advancing artificial general intelligence through foundational work in reinforcement learning, large-scale learning systems, and autonomous agent architectures. He earned his PhD in 2003 from the Gatsby Computational Neuroscience Unit at University College London. His work emphasizes scalable optimization algorithms, distributed systems for foundation models, and understanding emergent capabilities in neural architectures. Research interests include full-stack training pipelines for foundation models, mathematical principles of large-scale learning systems, and bridging language models with embodied intelligence. He advises prospective students with backgrounds in applied deep learning or theoretical computer science, offering access to the Kempner Institute's computational resources. He serves on committees for the ACM Prize in Computing and Sloan Research Fellowships, co-organizes the Simons Symposium on Theoretical Machine Learning, and chaired COLT 2011. His lab works at the intersection of theory and practice, addressing challenges in AI's societal impact and technical scalability. Labs/Teams: Co-directs the Kempner Institute, fostering collaborations between AI researchers and social scientists. Active in Harvard's SEAS community.

Alexander SchwingView profile

Associate Professor

• Machine Learning
• Computer Vision
• Structured Prediction
• +7 more

Alexander Schwing is an Associate Professor in the Department of Electrical and Computer Engineering and Computer Science at the University of Illinois at Urbana-Champaign, affiliated with the Coordinated Science Laboratory. His research focuses on machine learning and computer vision with applications in 3D scene understanding, generative modeling, and multi-agent systems. Education: Diploma in Electrical Engineering and Information Technology, Technical University of Munich (TUM) PhD in Computer Science, ETH Zurich Postdoctoral Fellow, University of Toronto Research Interests: Structured prediction in deep learning Generative adversarial networks and stability Multi-modal vision-language models 3D scene reconstruction from single images Embodied agent collaboration Semantic segmentation with temporal coherence Recent Publications: Highlight trends in neural rendering, video object segmentation, and reinforcement learning with applications to 3D modeling and multi-agent systems. Notable innovations include SAIL-VOS dataset for amodal segmentation and NeRFDeformer for single-view scene transformation. Scientific Awards: NSF CAREER Award, 3M and Amazon research awards, multiple student recognition awards, ETH Zurich PhD medal, and best paper at Intelligent Tutoring Systems 2014. Teaching: Offers graduate courses in Pattern Recognition (ECE 544) and Machine Learning (CS 446/ECE 449). Previously taught at University of Toronto and ETH Zurich. Labs & Collaborations: Leads research at Coordinated Science Laboratory (UIUC) with collaborations across University of Toronto, ETH Zurich, and industry partners like Samsung SAIT and Amazon.

K. Michael HaysView profile

Professor

• Architectural Theory
• European Modernism
• Critical Theory
• +3 more

K. Michael Hays is the Eliot Noyes Professor of Architectural Theory at Harvard University's Graduate School of Design (GSD) and Co-Director of the Master in Design Studies program. He has been a faculty member since 1988, specializing in architectural history and theory. His research focuses on European modernism, critical theory, and contemporary architectural practice, with notable contributions to the field through writings on figures like Mies van der Rohe and Peter Eisenman. Education: He holds a Bachelor of Architecture (1976) from Georgia Institute of Technology, a Master of Architecture in Advanced Studies (1979) from MIT, and a PhD in History, Theory, and Criticism of Architecture and Art (1990) from MIT. Research Interests: Hays is renowned for founding the journal Assemblage , a pivotal forum for architectural theory. His work bridges historical analysis and contemporary practice, emphasizing theoretical frameworks for understanding modernism and its evolution. He has curated exhibitions at institutions like the Whitney Museum of American Art (as its first Adjunct Curator from 2000–2009). Publications: His authored and edited works include Architecture's Desire , Inscriptions: Architecture Before Speech , and critical studies on architects such as Buckminster Fuller and Diller + Scofidio. These publications explore themes of representation, modernist aesthetics, and interdisciplinary design. Awards and Roles: While no specific awards are listed, his academic leadership roles include Chair of the GSD PhD Committee (1995–2005) and Director of Advanced Independent Study Programs. He has also served on editorial boards for journals like Assemblage and Thresholds . Labs and Collaborations: Hays collaborates with academic and institutional partners, notably through curatorial projects and his role in shaping the GSD's theoretical curriculum. His influence extends to both pedagogical innovation and scholarly discourse in architectural education.

• Public Law
• American Constitutional Law
• Administrative Law
• +3 more

Susan Fino is a Professor at the College of Liberal Arts and Sciences, Wayne State University. Her research focuses on public law, American constitutional law, administrative law, and the role of state supreme courts. She holds a B.A. from Johns Hopkins University, an M.A. and Ph.D. from Rutgers University. She has received the President's Award for Excellence in Teaching. Her courses include American Government (PS1010) and Constitutional Law (PS5110/PS5120), taught across multiple terms from 2023 to 2025. Dr. Fino's research explores judicial federalism, state constitutional frameworks, and legal interpretations of rights. Her work analyzes topics like church-state relations, taxation provisions in state constitutions, and assisted suicide debates. She has written extensively on state supreme court dynamics, including landmark cases and institutional performance metrics. Her scholarship bridges legal theory with practical governance challenges at both state and federal levels. Her publications span over three decades, addressing evolving legal landscapes such as the Rehnquist Court’s federalism approach and technological impacts on criminal sentencing. She consistently engages with issues at the intersection of law, politics, and societal values.

Salvatore CallesanoView profile

Assistant Professor

• Sociolinguistics
• Bilingual Communities
• Language Perception
• +4 more

Salvatore Callesano is an Assistant Professor of Hispanic Linguistics at the University of Illinois Urbana-Champaign (UIUC), affiliated with the Department of Spanish and Portuguese and the College of Liberal Arts & Sciences. His research focuses on sociolinguistics, particularly bilingual communities in the U.S., language perception, and digital media representations of bilingualism. He employs both quantitative and qualitative methods to investigate how language variation interacts with identity, media, and social structures. Dr. Callesano collaborates on Project 16 of the Asociación de Lingüística y Filología de América Latina, addressing linguistic aspects of Latin American diaspora communities. His work bridges traditional sociolinguistic inquiry with modern digital practices, analyzing how social media shapes perceptions of language use among Latinx populations. Recent research highlights include studies on code-switching in Miami's linguistic landscape, dialect perception, and the role of media in mediating language attitudes. His publications span peer-reviewed articles and book reviews, emphasizing empirical rigor and interdisciplinary connections between language, culture, and society.

William KennedyView profile

Professor

• Fiction
• Creative Writing
• American Literature
• +2 more

William Kennedy is a Professor in the English Department at the University at Albany, State University of New York. For over 40 years, he has crafted a body of literature centered on Albany, New York, creating what is known as the "Albany Cycle" of novels. His work has established Albany as a significant place in American literature, comparable to Joyce's Dublin and Bellow's Chicago. His educational background includes a BA from Siena College, following attendance at Public School 20 and Christian Brother's Academy. Professor Kennedy's creative work focuses on American fiction, particularly historical and urban narratives rooted in Albany's cultural and political landscape. His writing explores machine politics, family sagas, and the interplay between individual lives and historical events, rendering Albany's "outcasts and machine politicians, lowlifes and swells" with profound humanity. His narratives transform the city into a mythic capital of national memory. His publications consistently draw from Albany's history, with recurring themes of political corruption, redemption, and the resilience of marginalized communities. The "Albany Cycle" demonstrates his mastery in blending local history with universal human struggles across multiple literary forms. William Kennedy's distinguished honors include: John D. and Catherine T. MacArthur Foundation Fellowship Election to the American Academy of Arts and Letters National Endowment for the Arts Fellowship Regents Medal of Excellence from SUNY Governor's Arts Award Commander of the Order of Arts and Letters in France Election to the American Academy of Arts and Sciences As an educator, Kennedy taught creative writing and journalism at the University at Albany from 1974-1982 and Cornell University in 1982-83. His MacArthur Fellowship directly funded the creation of the New York State Writers Institute at Albany, with matching funds from the university and legislative support from Governor Cuomo. He has served on the New York State Council for the Humanities board and the Academy of Motion Picture Arts and Sciences. William Kennedy co-founded the New York State Writers Institute in 1984, which has grown into a major literary hub conducting statewide cultural and educational activities. The Institute remains central to his legacy, fostering literary arts through readings, workshops, and educational programs across New York.

Hans BeckView profile

Professor

• History and culture of ancient Greece
• Historical geography of Greece
• Historical environmental studies of ancient Greece
• +5 more

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.

• Management Education
• Project Management
• Information Management
• +3 more

Prof. Dr. Frank Ulbrich is a Lecturer and Programme Director for the BSc Business Administration at the Lucerne School of Business (HSLU). He holds a PhD in Business Administration from the Stockholm School of Economics. His academic career spans roles at universities in Sweden, the UK, Canada, and Switzerland, alongside IT & Management consulting experience. Research focuses on management education, project management, information management, and organizational change. He has published extensively in areas like shared services, digital transformation, and curriculum development. Notable awards include multiple Emerald Literati Awards and a Fellowship from the Higher Education Academy. Education: PhD in Business Administration (Stockholm School of Economics) Affiliations: Institute of Business and Regional Economics at HSLU Teaching Subjects: Academic Methods, Higher Education Management, Project Management, Digital Transformation Recent presentations include discussions on bridging academia-industry gaps, curriculum integration of SDGs, and data-driven learning strategies. His work emphasizes aligning education with labor market needs and advancing evidence-based teaching practices.

Peter A. RaymondView profile

Professor

• Biogeochemistry
• Carbon Cycling
• Greenhouse Gas Exchange
• +6 more

Peter A. Raymond is the Oastler Professor of Biogeochemistry at Yale University's School of the Environment and Department of Geology and Geophysics. He serves as Senior Associate Dean of Research & Director of Doctoral Studies and is Co-Director of the Yale Center for Natural Carbon Capture. Raymond leads the Raymond Biogeochemistry Lab, which investigates the biogeochemistry of inland waters, enhanced weathering, methane cycling, and blue carbon systems through cutting-edge field, laboratory, and modeling approaches. Education B.S., Marist College Ph.D., College of William and Mary/Virginia Institute of Marine Science Research Focus Raymond's research fundamentally reshapes our understanding of carbon cycling in aquatic systems, demonstrating that rivers serve as dynamic conduits rather than passive pipes in the global carbon cycle. His work examines how biology and watershed variables alter carbon chemistry in streams, rivers, and estuaries, with particular emphasis on understanding global carbon cycles in relation to climate change. Raymond employs radiocarbon measurements to explore the age and turnover of carbon in aquatic ecosystems, revealing that rivers are variable sources of both old and young terrestrial dissolved organic carbon to oceans. The Raymond Lab is particularly known for developing the Pulse-Shunt Concept, which challenges traditional views of riverine biogeochemistry by emphasizing the episodic and dynamic nature of elemental fluxes. Current research directions include enhanced weathering and alkalinity studies for carbon removal, global greenhouse gas budgets through projects like RECCAP 2, natural methane cycling in aquatic systems, and blue carbon ecosystems such as mangroves and salt marshes. Publication Trends Raymond's recent publications (2023-2025) demonstrate a strong focus on global carbon and methane cycling, with particular attention to inland water systems' role in the Earth's climate system. His work increasingly integrates large-scale datasets with field measurements to understand how climate change and human activities affect greenhouse gas emissions from rivers and streams. A significant portion of his recent work contributes to international efforts like the Global Carbon Project, aiming to refine estimates of global carbon and methane fluxes. His research also shows growing emphasis on carbon removal strategies, particularly enhanced rock weathering through the Earthshot-funded GOAL-A project, and their potential for climate mitigation. Scientific Recognition Fellow of the American Association for the Advancement of Science Member of the Connecticut Academy of Science and Engineering Coastal and Estuarine Research Federations Cronin Award for Young Scientists ISI highly cited author Past Editor and Chief of the American Geophysical Union's journal Global Biogeochemical Cycles Mentorship and Funding Professor Raymond currently mentors four doctoral students (Jon Gewirtzman, Shou-En "Samuel" Tsao, Benjamin Saalidong, and Mingyu Zhang) and masters student Bella Garrioch. His research is supported by multiple grants from the National Science Foundation (NSF), including CAREER awards, and participation in the Earthshot-funded GOAL-A (Global Ocean And Land Alkalinization) project. Raymond has also been involved in significant collaborative projects with USGS data to research how climate and land use change alter carbon export from US watersheds, and with Lamont Doherty to develop methods for measuring air-sea gas exchange of CO2 in rivers and estuaries. Research Infrastructure The Raymond Biogeochemistry Lab at Yale is a dynamic research group comprising research scientists, postdocs, doctoral and masters students, and postgraduate researchers. The lab recently acquired a Mini Carbon Dating System (MICADAS) at Yale, significantly expanding their research capabilities in ecosystem carbon turnover and verification of natural climate solutions. The lab collaborates globally on projects in the Arctic, Hudson River, and middle Atlantic Bight, and is actively involved in the NASA Carbon Monitoring System BlueFlux field campaign to assess carbon exchange in coastal wetlands.