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Adrian WellerView profile

Research Professor

• Artificial Intelligence
• Machine Learning
• Explainability
• +9 more

Adrian Weller is a prominent researcher and academic at the University of Cambridge, serving as a Director of Research in Machine Learning within the Department of Engineering. He holds multiple significant leadership roles including Programme Director for Trust and Society at the Leverhulme Centre for the Future of Intelligence (CFI), and previously served as Programme Director for AI at The Alan Turing Institute, the UK national institute for data science and AI. His work bridges theoretical machine learning research with practical applications and societal implications of artificial intelligence. Weller's research interests span a broad spectrum of AI and machine learning topics with a particular focus on ensuring beneficial societal outcomes. His work encompasses explainability, fairness, robustness, scalability, privacy, safety, and ethics in AI systems. He has made significant contributions to trustworthy machine learning, including developing frameworks for AI governance, certification, and human-AI collaboration. His research group actively investigates neuro-symbolic approaches, privacy-preserving techniques, and methods for improving the reliability and interpretability of AI systems. His recent publications demonstrate a strong trend toward addressing the practical challenges of deploying AI systems in real-world contexts, particularly focusing on certification frameworks, governance mechanisms, and human-centered approaches. His work spans theoretical advances in machine learning architectures while maintaining a strong connection to societal impact, with publications appearing in top venues across AI, machine learning, and interdisciplinary applications. Scientific Awards: MBE for services to digital innovation (2022 Queen's Birthday Honours) Turing AI Fellowship for Trustworthy Machine Learning Weller actively supervises a large group of PhD students and postdocs, with current students including Juyeon Heo, Yanzhi Chen, Katie Collins, Isaac Reid, Yichao Liang, Herbie Bradley, and Shoaib Siddiqui. His former students have gone on to positions at leading institutions including Google DeepMind, ETH Zurich, NYU, and MPI-IS Tübingen. He has served on numerous advisory boards including the Centre for Data Ethics and Innovation, UNESCO's expert group on AI ethics, and the World Economic Forum's Global Future Council on AI. His research has been supported through his Turing AI Fellowship and various collaborative projects focused on safe and ethical AI development. Weller leads a vibrant research group focused on trustworthy machine learning, which actively organizes workshops and conferences including ICML 2024 (where he served as Program Chair), multiple workshops on responsible AI, and events through the ELLIS network. His group collaborates extensively across disciplines, working with researchers in computer science, social sciences, law, and policy to address the multifaceted challenges of developing beneficial AI systems.

Tien Tsin WongView profile

Professor

• Generative AI
• Computer Graphics
• Computer Vision
• +4 more

Tien Tsin Wong is a Professor in the Department of Data Science & AI at Monash University, Australia. Previously, he served as a Professor at the Chinese University of Hong Kong (1999–2024) and held a Visiting Assistant Professor position at the Hong Kong University of Science and Technology (1998–1999). His research focuses on Generative AI, Computer Graphics, Computer Vision, and Computational Manga, with significant contributions to GPU techniques, image-based rendering, and multimedia compression. Education: He earned a B.Sc. (1992), MPhil (1994), and PhD (1998) in Computer Science from the Chinese University of Hong Kong. Research Interests: His work bridges computational techniques with artistic applications, particularly in manga and animation. Notable areas include generative models, diffusion-based video synthesis, and physically plausible scene generation. His research aligns with UN Sustainable Development Goals through innovations in education and digital accessibility. Awards : He has received the 2004 Young Researcher Award, 2005 IEEE Transactions on Multimedia Prize Paper Award, and two international invention medals (Geneva 2018, Asia Hong Kong 2019). Editorial Roles : He serves as an Associate Editor for Computer Graphics Forum , IEEE Transactions on Visualization and Computer Graphics , and Computational Visual Media . His editorial work underscores his influence in advancing visualization and graphics research. Labs/Teams : While not explicitly named, his collaborations span global institutions, focusing on computational manga, generative AI, and GPU-optimized techniques. His work often involves interdisciplinary teams addressing challenges in digital media and AI.

Achuta KadambiView profile

Associate Professor

• AI
• Computational Imaging
• Computer Vision
• +7 more

Achuta Kadambi, Ph.D., is an Associate Professor at UCLA in Electrical Engineering and Computer Science, leading an interdisciplinary research group focused on AI, computational imaging, and bias mitigation in medical technologies. He recruits PhD students from EE, CS, and Bioengineering departments and has commercialized research through two California-based companies. His research investigates the intersection of physics and artificial intelligence, with a focus on unbiased low-level vision systems. Current projects explore how light transport interacts with human skin variations to identify and correct imaging biases in facial recognition and medical devices. His work has produced over 70 patents, with 30+ issued, and a textbook Computational Imaging (MIT Press, 2022). NSF CAREER Award (2021) for light transport bias research DARPA Young Faculty Award (2021) for AI and medical imaging innovations ARO Young Investigator Program (2021) for computational sensing IEEE-HKN Under 35 Award (2022) for inclusive EECS inventions Forbes 30 Under 30 recognition His recent publications focus on polarization imaging, 3D Gaussian splatting, synthetic data generation for healthcare, and bias mitigation in machine learning. Collaborations with UCLA medical school faculty, including Dr. Laleh Jalilian, aim to deploy these innovations in clinical settings. Current teaching includes ECE 149: Foundations of Computer Vision (Fall 2024, Spring 2025) and ECE 102: Signals and Systems (Winter 2024).

Rajeev AlurView profile

Professor

• Formal Methods
• Artificial Intelligence
• Cyber-Physical Systems
• +6 more

Rajeev Alur is the Zisman Family Professor in the Department of Computer and Information Science at the University of Pennsylvania, leading the School of Engineering and Applied Science. He is the Founding Director of the ASSET Center for Trustworthy AI and a member of the PRECISE Center. His research focuses on formal methods for system design, integrating AI, cyber-physical systems, and machine learning with logical reasoning to ensure safety in autonomous systems. Alur has held leadership roles in major NSF projects like ExCAPE and has directed the Embedded and Multi-Scale Systems (EMBS) program. His research interests span formal verification, temporal logics, programming abstractions, and synthesis techniques. Notable contributions include the development of Nested Words (visibly pushdown languages), streaming string transducers, and tools like AutomataTutor for education. He has advised over 60 PhD students and postdocs, many of whom now hold academic and industry leadership positions. Alur’s awards include the 2024 Knuth Prize and the 2016 Alonzo Church Award. His work on Verisig and compositional verification of neural networks has advanced safety-critical AI applications. He teaches foundational courses like CIS 2620 and develops educational tools, emphasizing both theoretical rigor and practical impact. Key projects include the ASSET Center’s focus on trustworthy AI, integration of logical specifications in reinforcement learning, and formal verification of closed-loop systems with neural components. His publications span over 350 papers, with recent work addressing neurosymbolic learning, security in large language models, and efficient neural network verification.

Kevin M. KruseView profile

Professor

• Political History
• Urban History
• Race and Ethnicity
• +5 more

Kevin M. Kruse is Professor of History at Princeton University and Director of Undergraduate Studies. Specializing in 20th-century U.S. political, social, and urban history, his research examines conflicts over race, rights, and religion. Kruse earned his B.A. from UNC Chapel Hill and Ph.D. from Cornell University, joining Princeton after positions at the University of Virginia. His scholarship explores the civil rights movement, religious nationalism, suburbanization, and modern conservatism. Recent books analyze the corporate invention of Christian America and historical myths in American political discourse. Current projects include studies of civil rights lawyer John Doar and 'law and order' politics in New York City. Honored as a Guggenheim Fellow and Smithsonian Innovator, Kruse has received the Francis B. Simkins Award and Best Book in Urban Politics award. He teaches courses on civil rights, suburban history, and modern U.S. politics, and advises graduate students in 20th-century U.S. history. Kruse frequently engages public discourse through media appearances and collaborative projects with documentary filmmakers.

Pranav AnandView profile

Professor

• Semantics
• Pragmatics
• Syntax-Semantics Interface
• +5 more

Pranav Anand is a Professor in the Department of Linguistics at the University of California, Santa Cruz (UCSC). He currently serves as the Faculty Director of the Humanities Institute at UCSC since July 2023. His research focuses on the interplay between context, interpretation, and grammatical perspective, particularly in areas like de re/de se contrasts, evaluative predication, and indexical shift. He has contributed to studies on narrative structures, evidential restrictions, and the syntax-semantics interface in sluicing. Dr. Anand has taught a variety of courses including Ling 119: Narratives , Ling 231: Semantics A , and special topics like Invented Languages: From Elvish to Esperanto . His work bridges theoretical linguistics with computational methods, evidenced by collaborations in projects such as the Santa Cruz sluicing dataset and analyses of political discourse in online commentary. His research has been published in journals like Linguistics and Philosophy , Language , and Discourse and Society , with a focus on semantics, pragmatics, and narrative linguistics. He has also contributed to computational linguistics initiatives, including the development of annotated corpora for sentiment analysis and argumentation studies. Dr. Anand's academic contributions span both theoretical exploration and applied computational linguistics, reflecting his interdisciplinary approach to understanding language structure and usage.

Sandro ZanettiView profile

Professor

• Artistic Production Processes
• Avant-garde Research
• Poetics of (Im)Probability
• +8 more

Sandro Zanetti, Full Professor of General and Comparative Literature at the University of Zurich's Faculty of Arts and Humanities, specializes in avant-garde research, artistic production processes, and poetics of (im)probability. He studied German, History, and Philosophy at Basel, Freiburg, and Tübingen (1993-1999), earned his PhD in 2005 at Basel's SNSF project, and held positions including Junior Professor at Hildesheim (2008-2011) and DFG network head (2010-2014). Since 2011 at UZH, he progressed from Assistant to Full Professor (2022) and serves as Co-Dean of Studies since 2021. Current affiliations: Department of General and Comparative Literature (UZH), Center for Arts and Cultural Theory (ZKK), Literary Radio Zurich Former roles: ZGW Center (2010-2022), SNF project leader (2015-2019), Co-editor of History of the Present (2016-present) His research explores: Avant-garde genealogies and postwar literary modernity Time perception and aesthetic temporality Writing as cultural technique Interdisciplinary intersections with philosophy, media studies, and art Publications reveal trends in: 2022-2024: Dada historiography, AI-generated literature, Paul Celan's late works 2019-2021: Aesthetic theory, transactuality, Barthesian concepts 2014-2017: Improvisation networks, multilingualism, collaborative writing He co-founded interdisciplinary platforms and maintains editorial roles across 15 anthologies since 2004.

• Managing discontinuous business model innovation
• Digital strategies for Industrie 4.0
• Additive Manufacturing
• +11 more

Prof. Dr. Frank T. Piller is a University Professor and Co-Leader of the Institute for Technology and Innovation Management (TIM) at RWTH Aachen University, where he also serves as Academic Director of the Executive MBA program at RWTH Business School. He leads a research team of approximately 30 doctoral students, 5 postdocs, and over 20 student researchers within the TIME Research Area of the School of Business and Economics. His educational background includes a doctoral degree in Operations Management from the University of Würzburg (1999) and a Habilitation degree from TUM Business School (2004) on "Innovation and Value Co-Creation." Prior to joining RWTH Aachen in 2007, he was a Research Fellow at MIT Sloan School of Management and faculty at TUM Business School. Prof. Piller is recognized as one of the world's leading experts in customer-centered value creation, specializing in mass customization, personalization, and customer co-creation. His current research focuses on how established companies can transform in response to disruptive business model innovations, with particular emphasis on digital transformation (Industry 4.0), AI-augmented innovation, and sustainable business models. He is particularly known for his work on innovation ecosystems, platform-based business models, and stakeholder-oriented technology development. His recent publications demonstrate a clear trajectory toward integrating artificial intelligence with traditional innovation management frameworks, exploring how AI transforms manufacturing systems, innovation processes, and business models. His work increasingly addresses the challenges of digital transformation in established industries while maintaining focus on customer co-creation and mass customization principles. His scientific achievements have been recognized with numerous awards: Co-Creation Award of the PDMA Nomination for "Innovating Innovation" Prize by Harvard Business Review and McKinsey "Lecturer of the Year" by Executive MBA students at TU Munich RWTH Aachen Rector's Prize for Excellent Teaching (since 2010) Grant for innovative "Flipping the Classroom" teaching concept ERC Synergy Grant for SAFER Grid project (2025-2031) Prof. Piller maintains an extensive research network spanning academia and industry. He collaborates with numerous corporations including 3M, Adidas, BASF, EON, J&J, P&G, Siemens, and Vodafone, as well as many technology startups across Europe and North America. As a co-founder, supervisory board member, and investor in innovative startups, he actively transfers research into practice. His research has received significant funding, most notably the prestigious ERC Synergy Grant for the SAFER Grid project. He leads the Technology and Innovation Management Group (TIM) within the TIME Research Area at RWTH Aachen, which comprises over 100 senior and junior researchers working at the intersection of innovation, technology management, marketing, and entrepreneurship. The institute is a leading European research institution for strategic, behavioral, and computer-supported technology and innovation management.

Sebastijan DumancicView profile

Assistant Professor

• Program Synthesis
• Probabilistic Programming
• Neuro-Symbolic AI
• +2 more

Sebastijan Dumancic is an Assistant Professor at Delft University of Technology, focusing on neuro-symbolic AI through program synthesis and probabilistic programming. He leads the RAIL lab and collaborates with institutions like Harvard, MIT, and CNRS. His research bridges symbolic AI and machine learning, applying program synthesis to scientific discovery, transportation, and robotics. He holds an FWO-funded PhD from KU Leuven and has participated in initiatives like ELLIS and the Symbolic Computation and Machine Learning Initiative. Program synthesis Probabilistic programming Neuro-symbolic AI Constraint-based learning His recent articles highlight advancements in program synthesis, neuro-symbolic integration, and constraint satisfaction. Projects like Find2Fix and Intelligent Greenhouse Horticulture (funded by NWO) demonstrate practical applications. ELLIS Membership University Teaching Qualification He supervises numerous MSc and PhD students in projects involving logic programming, program synthesis, and probabilistic modeling. Active in workshops and symposia, he contributes to neuro-symbolic AI and scientific discovery.

• Linguistic Anthropology
• Sociolinguistics
• Honorific Systems
• +4 more

Dr. Luke Fleming is an Associate Professor in the Department of Anthropology at the University of Montreal's Faculty of Arts and Sciences. His research focuses on comparative linguistic anthropology, particularly the typology of honorific systems, kinship-related linguistic avoidance practices, and sociolinguistic dynamics in indigenous and small-scale societies. He has authored over 20 peer-reviewed publications and led numerous research projects funded by the Social Sciences and Humanities Research Council of Canada (SSHRC) and international institutions. Teaching responsibilities include courses on sociolinguistics, linguistic anthropology, and language and culture. He supervises graduate students engaged in interdisciplinary research spanning from Sri Lanka to the Amazon basin. Current projects investigate honorific pronoun systems across Theravada Buddhist communities and Tamil language usage in South Asia. Lead researcher for SSHRC-funded projects studying honorific systems and small-scale sociolinguistics Published in Journal of Linguistic Anthropology , Language in Society , and Anthropological Linguistics Advisor to 9 graduate students since 2018 Research networks include collaborative projects with Patagonian language speakers and ongoing comparative studies linking Southeast Asian honorifics to African avoidance practices. His forthcoming book On Speaking Terms examines kinship-related linguistic avoidance worldwide. Active in program development for interdisciplinary anthropology degrees, contributing to 15 academic programs at undergraduate and graduate levels.

LEE Mong LiView profile

Professor

• Data Management
• Data Cleaning
• Data Fusion
• +5 more

LEE Mong Li is a Professor of Computer Science at the National University of Singapore (NUS) and serves as Director of the NUS Centre for Trusted Internet and Community. She holds a Ph.D., M.Sc., and B.Sc. (First Class Honours) in Computer Science from NUS, where she was awarded the IEEE Singapore Information Technology Gold Medal as the top Computer Science student in 1989. Her academic career includes a visiting fellowship at the University of Wisconsin-Madison (1999) and consultancy with QUIQ USA (2000). Her research spans Data Management, Spatio-temporal Databases, Biomedical Informatics, and Retinal Image Analysis . She has pioneered work in data cleaning, data fusion, and analysis of semistructured data, with applications in social media analytics and healthcare. Her recent publications demonstrate strong interdisciplinary focus, particularly in AI-driven medical diagnostics including diabetic retinopathy screening and chronic kidney disease detection from retinal images. She co-authored foundational books on 'Designing Semi-structured Database' and 'Temporal and Spatio-Temporal Data Mining'. Her 150+ publications in major database conferences and journals reflect leadership in both theoretical and applied research. Recent work shows significant emphasis on Medical AI applications (retinal analysis, kidney disease prediction) Temporal fact verification systems Misinformation detection in multimodal environments Privacy challenges in large language models Key honors include: Singapore's President Technology Award (2014) for co-inventing an AI system screening eye conditions IEEE Singapore Information Technology Gold Medal (1989) She actively contributes to government-funded multidisciplinary projects building practical deployable systems. Her leadership extends to program committees of prestigious database conferences and directing the NUS Centre for Trusted Internet and Community. She teaches BT5110 Data Management and Warehousing and has co-developed an AI system for diabetic retinopathy screening deployed in Singapore's national teleophthalmology program.

Robert R. EdwardsView profile

Professor

• Medieval Literature
• Chaucer Studies
• Book History
• +4 more

Robert R. Edwards serves as the Edwin Erle Sparks Professor of English and Comparative Literature at Pennsylvania State University within the College of the Liberal Arts. His office is located in Burrowes Building, where he maintains regular office hours including scheduled appointments for Fall 2025. As a distinguished scholar in medieval literary studies, Professor Edwards has established himself as a leading authority on Chaucer, medieval drama, and book history. Professor Edwards specializes in Book History and Textual Studies with particular expertise in Medieval Literature. His research focuses on Chaucer studies, continental and Latin literary relations, and authorship in trilingual England. His scholarly approach integrates historical context with literary analysis, examining how medieval writers engaged with classical traditions while developing innovative narrative forms. His work reveals the complex interplay between textual production, cultural identity, and literary innovation in the medieval period. His publication record demonstrates consistent scholarly productivity spanning several decades, with significant contributions to understanding medieval literary theory, authorship concepts, and cross-cultural literary relations. His works show an evolving trajectory from foundational studies of medieval poetics to more nuanced examinations of specific authors and textual traditions, particularly focusing on how medieval writers negotiated classical heritage with contemporary cultural concerns. Professor Edwards has edited significant works including John Lydgate's writings and essay collections on medieval love, desire, and sexuality. His scholarly editing demonstrates commitment to making primary medieval texts accessible while providing critical frameworks for contemporary interpretation. His research continues to influence how scholars understand the development of literary consciousness in the medieval period.

Rune NyordView profile

Associate Professor

• Ancient Egyptian mortuary religion
• Ancient Egyptian art and archaeology
• History of Egyptology
• +3 more

Rune Nyord is an Associate Professor of Ancient Egyptian Art and Archaeology at Emory University's Art History Department since 2018. He holds a Dr. phil. in Egyptology from the University of Copenhagen (2010) and has held academic positions at institutions including the University of Cambridge and Freie Universität Berlin. His research focuses on ancient Egyptian mortuary religion, conceptions of images, and the history of Egyptology, particularly examining Middle Kingdom (early 2nd millennium BCE) funerary culture through archaeological and textual sources. He has authored and edited multiple books, including Seeing Perfection: Ancient Egyptian Images beyond Representation (2020) and Yearning for Immortality: The European Invention of the Ancient Egyptian Afterlife (2025). Recent projects explore reinterpreting the 'Book of the Dead' through indigenous conceptual frameworks. His work bridges anthropology, cognitive approaches, and material culture studies. Rune Nyord has received notable awards such as the 2022 Senior Fellowship at the National Gallery of Art and the 2016 Lady Wallis Budge Junior Research Fellowship. He actively participates in academic service roles, including editorial work for journals like Papyrus and the UCLA Encyclopedia of Egyptology. His teaching spans undergraduate and graduate courses on ancient Egyptian art, language, and religion, integrating museum resources and object studies into his pedagogy.

Mengdi WangView profile

Professor

• Reinforcement Learning
• Machine Learning Theory
• Generative AI
• +4 more

Mengdi Wang is a Professor at Princeton University with primary appointments in the Department of Electrical and Computer Engineering and the Center for Statistics and Machine Learning, and courtesy appointments in the Department of Computer Science and Omenn-Darling Bioengineering Institute. She co-directs Princeton AI for Accelerated Invention and is affiliated with the Princeton ML Theory Group and Princeton Language+Intelligence Initiative, with prior visiting roles at DeepMind, IAS, and Simons Institute. Her educational background includes a PhD in Electrical Engineering and Computer Science (with Mathematics minor) from MIT (2013), advised by Dimitri P. Bertsekas at LIDS, and undergraduate studies in Automation at Tsinghua University: PhD: MIT, Electrical Engineering and Computer Science (2013) Bachelor: Tsinghua University, Automation Her research establishes theoretical foundations for machine learning with emphasis on reinforcement learning algorithms, generative AI, and large language models. She investigates data-driven stochastic optimization, statistical limits of reinforcement learning, representation learning, and diffusion models, developing provably robust algorithms for complex systems. Her work bridges theoretical guarantees with real-world applications in healthcare, biotech drug discovery, fintech, and scientific acceleration, focusing on how AI can transform discovery processes across disciplines. Her scientific contributions are recognized by prestigious awards: Young Researcher Prize in Continuous Optimization (Mathematical Optimization Society, 2016) Princeton SEAS Innovation Award (2016) NSF Career Award (2017) Google Faculty Award (2017) MIT Tech Review 35-Under-35 (China region, 2018) WAIC YunFan Award (2022) Donald Eckman Award (American Automatic Control Council, 2024) Professor Wang actively mentors students and recruits undergraduate interns, visitors, and postdocs for her research group. Her work is supported by major grants from NSF, AFOSR, NIH, ONR, Google, Microsoft C3.ai, FinUP, RVAC Medicines, MURI, and GenMab. She serves as Program Chair for ICLR 2023 and Senior Area Chair for NeurIPS, ICML, and COLT, while editing for Harvard Data Science Review and Operations Research. She leads Princeton AI for Accelerated Invention, which develops AI-driven solutions for scientific discovery, collaborating closely with Princeton's ML Theory Group and Language+Intelligence Initiative to advance algorithmic innovation and interdisciplinary applications.

Thad StarnerView profile

Professor

• Wearable Computing
• Human-Computer Interaction (HCI)
• Augmented Reality
• +7 more

Thad Starner is a Professor in the College of Computing at Georgia Institute of Technology and Technical Lead/Manager on Google's Glass. He directs the Contextual Computing Group (CCG), co-founded the Animal Computer Interaction Lab, and contributes to Georgia Tech's Ubicomp Group and Brainlab. A wearable computing pioneer since 1993, he has over 500 publications and 80 issued U.S. patents. Coined 'augmented reality' in 1990 Developed CopyCat for ASL learning in deaf children Invented Passive Haptic Learning for skill acquisition His research spans wearable interfaces for Deaf-hearing communication, dolphin interaction systems (CHAT), dog-handler communication (FIDO), and brain-computer interfaces for ALS patients. Current projects focus on optical aging simulation, XR input methods, and animal behavior telemetry. Recent publications (2023-2025) explore AR display ergonomics, AI-augmented reasoning, sign language recognition, and animal-computer interaction. His work has been featured in 60 Minutes, BBC, National Geographic, and Time Magazine. CHI Academy (2017) Lemelson-MIT Prize finalist White House Champions of Change finalist He advises graduate students in wearable systems and teaches AI and prototyping courses. His lab developed the Perceptive Workbench for gesture tracking and created early Eigenfaces research for face recognition.