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John E. TaylorView profile

Professor

• Smart City Digital Twins
• Urban Infrastructure Resilience
• Network Dynamics
• +5 more

John E. Taylor is the Frederick Law Olmsted Professor and Associate Chair for Faculty Development and Research Innovation at the Georgia Institute of Technology's School of Civil and Environmental Engineering within the College of Engineering. His research focuses on the intersection of human and engineered networks, with particular emphasis on creating resilient infrastructure systems that serve society's needs while creating more livable communities. Taylor's research interests span multiple domains including Smart City Digital Twins , Urban Infrastructure Resilience , Network Dynamics , and Building-Occupant Interaction . His work examines how human behavior, infrastructure systems, and environmental factors interact during normal operations and extreme events. He has developed innovative approaches to understanding urban systems through the lens of network theory and computational modeling. His publication record demonstrates consistent contributions to the fields of urban analytics and infrastructure resilience, with a recent focus on digital twin technologies for urban systems. Taylor's work shows a clear trajectory toward increasingly sophisticated integration of AI, network science, and civil infrastructure engineering to address complex urban challenges. His research has particular relevance for cities facing climate change impacts and seeking to build more equitable and resilient communities. Taylor leads the Network Dynamics Lab at Georgia Tech, where he mentors PhD students and postdoctoral researchers. His lab has produced significant work on human-infrastructure interaction, particularly during disasters and extreme events. The lab's research combines computational modeling, data analytics, and field studies to understand and improve urban systems. His work has been applied to real-world challenges including river emergency response systems, urban heat exposure forecasting, and disaster response optimization. Taylor has collaborated with city officials and agencies to implement systems that have demonstrable community benefits, such as the AI-enabled camera system for drowning prevention on the Chattahoochee River and crime reduction systems using mobile cameras guided by AI algorithms.

Michael FlowerView profile

Professor

• Greek Historiography
• Ancient Greek History
• Greek Religion
• +5 more

Michael Flower is the David Magie '97 Class of 1897 Professor of Classics at Princeton University, where he has been a core faculty member since 2003 after previously teaching at Franklin and Marshall College from 1986-2003. His position reflects his significant scholarly contributions to the field of Classics. Flower received his B.A. in Classical Languages from the University of California at Berkeley (1978), followed by a second B.A. in Classics from University College, Oxford University (1981), where he specialized in ancient history and philosophy. He completed his Ph.D. in Classics from Brown University in 1986. His research spans Greek historiography, history, and religion with particular emphasis on adapting methodologies from modern history, anthropology of religion, and literary criticism. Flower has made significant contributions to understanding Spartan society, panhellenism as political ideology, and the role of divination in ancient Greece. His interdisciplinary approach connects historical analysis with literary and religious studies, creating innovative pathways for understanding ancient Greek civilization. Flower's publications reveal a consistent focus on the intersection of history, literary criticism, and religious studies, with particular attention to how political ideology and religious practice shaped ancient Greek society. His work on Spartan success, panhellenism, and seers demonstrates how ancient Greeks constructed and maintained cultural and political identities through historical narratives and religious practices. Old Dominion Professor (2018-19) Flower has been actively involved in departmental initiatives, notably co-creating Princeton's pre-doctoral fellowship designed to diversify the field of Classics by supporting promising young Classicists from underrepresented backgrounds. This fellowship provides both preparation for and admission to Princeton's Ph.D. program, reflecting Flower's commitment to expanding access to the discipline. He has also co-organized significant academic events including the "Racing the Classics" conference and participated in department-wide diversity training initiatives. Flower maintains an active research agenda focused on historical fiction in ancient Greece, as evidenced by his Old Dominion Professor project "The Art of Historical Fiction in Ancient Greece," which continues his longstanding interest in how ancient historians constructed narratives that blended fact and literary artistry.

• Computational Linguistics
• Psycholinguistics
• Language Processing
• +4 more

Richard Futrell is an Associate Professor at the University of California, Irvine (UCI), affiliated with the Department of Language Science. He leads the Language Processing Group, focusing on computational models of human and machine language processing. His work bridges information theory, Bayesian cognitive modeling, and natural language processing (NLP) interpretability. University of California, Irvine Department of Language Science Language Processing Group leader His research examines how linguistic structures emerge from cognitive and communicative pressures. Key areas include dependency locality, surprisal theory in sentence processing, and efficiency-driven language evolution. He investigates how memory constraints, predictability, and information density shape syntactic and morphological patterns across languages. Recent publications analyze code-switching efficiency, syntactic priming, ERP component modeling, and agent-based language contact simulations. His work frequently employs Bayesian modeling, neural network analysis, and cross-linguistic corpora to uncover universal principles in language processing. ACL Best Paper Award (2024) Best Paper Award for Computational Modeling of Language (2023) Marr Prize for Best Student Paper (2017) He has developed datasets like SPACER for error repair analysis and contributed to phonotactic learning frameworks. His collaborations span cognitive scientists, computational linguists, and neuroscientists, advancing understanding of language production, comprehension, and structural optimization.

Christiane C. SchubertView profile

Assistant Professor

• Medical Education
• Healthcare Systems
• Patient Work Systems
• +6 more

Christiane C. Schubert is an Assistant Professor in Medical Education at the School of Medicine and an Assistant Professor in Interdisciplinary Studies at the School of Behavioral Health at Loma Linda University. Her dual appointments reflect her interdisciplinary approach to healthcare research and education, bridging medical education with behavioral health perspectives. Dr. Schubert's educational background includes: PhD from Loma Linda University (2008) MS from Northern Arizona University (1999) BS from Northern Arizona University (1997) Her research program focuses on understanding healthcare systems through multiple lenses. She investigates how patients with chronic illnesses navigate self-care within complex healthcare environments, with particular attention to macroergonomic factors that influence patient work systems. Dr. Schubert examines resilience in healthcare settings, exploring how both patients and providers adapt to challenges in clinical environments. Her work addresses cultural factors in healthcare, particularly examining how acculturation affects health-promoting behaviors among Arab Americans. Through her studies on novice-expert differences in emergency medicine, she contributes to understanding cognitive work processes in high-stakes clinical settings. Her interdisciplinary approach integrates insights from medical education, behavioral health, and systems engineering to address complex healthcare challenges. Dr. Schubert's scholarly output from 2012-2017 demonstrates consistent contributions across healthcare resilience, patient work systems, medical education, and cultural competence. Her publications reveal a trajectory of increasingly sophisticated systems thinking applied to healthcare delivery challenges, with a particular emphasis on understanding patient experiences and clinician cognition within complex healthcare environments. Dr. Schubert has maintained an active research and publication record since completing her PhD in 2008. Her work demonstrates a commitment to improving healthcare delivery through better understanding of patient experiences, clinician cognition, and system-level factors that influence healthcare outcomes. Her interdisciplinary appointments position her to bridge traditional academic boundaries in addressing complex healthcare challenges.

Paul RaysonView profile

Professor

• Natural Language Processing
• Corpus Linguistics
• Semantic Multilingual NLP
• +7 more

Professor Paul Rayson is a Professor of Natural Language Processing in the School of Computing & Communications at Lancaster University, UK. He serves as Director of the UCREL (University Centre for Computer Corpus Research on Language) interdisciplinary research centre and is affiliated with multiple research institutes including Security Lancaster, the Lancaster Centre for Digital Humanities, and the Data Science Institute. Education: PhD in Computer Science, Lancaster University (2003) BSc (Hons) Computer Science and Mathematics, Lancaster University (1990) Professor Rayson's research focuses on semantic multilingual Natural Language Processing (NLP) in challenging linguistic environments with noisy language data, including historical texts, learner language, speech, email, and other computer-mediated communication. His work spans applications in dementia detection, mental health analysis, online child protection, cyber security, learner dictionaries, and text mining of biomedical literature, historical corpora, and financial narratives. He has developed semantic tagging tools like USAS (UCREL Semantic Analysis System) and Wmatrix for corpus analysis. Major Awards and Honors: FHEA (Fellow of the Higher Education Academy) MBCS (Member of the British Computer Society) Professor Rayson has supervised numerous PhD students in NLP and corpus linguistics, with eight current students and seven completed doctorates. He has led or co-investigated multiple major research projects including the £3.5m ESRC-funded Centre for Corpus Approaches to Social Science (CASS), the National Corpus of Contemporary Welsh, and projects related to mental health forums, financial narrative analysis, and cyber security. His research has been supported by ESRC, EPSRC, and other funding bodies. As Director of UCREL, he oversees research in corpus linguistics and NLP. He is also active in the Cyber Security Research Centre, Digital Health Group, and multiple Data Science Institute initiatives. His lab has developed several widely-used NLP tools including CLAWS for English POS tagging, USAS semantic analysis system, Wmatrix corpus analysis tool, and the Variant Detector (VARD) for historical texts.

Axel MecklingerView profile

Professor

• Neurocognition of Memory and Language
• Executive Functions
• Spatiotemporal Brain Imaging
• +7 more

Prof. Dr. Axel Mecklinger is a leading cognitive neuroscientist at Saarland University , specializing in the neurocognition of memory and language through spatiotemporal brain imaging (EEG/MEG/fMRI). His career spans over three decades, with significant contributions to understanding visual working memory , associative recognition , and memory development . Key research areas: Memory binding, ERP subsequent memory effects, novelty detection, and cognitive aging Major grants: DFG Research Groups, Collaborative Research Centers, and international collaborations with the Chinese Academy of Sciences Scientific leadership: Organized conferences, edited journals, and served as speaker for research training groups His recent work explores unitization in memory formation , cross-cultural differences in memory processing , and theta neurofeedback interventions . Awards include the Early Career Award of the German Psychophysiology Society (1992) and the European Federation of Psychophysiology Societies' Federation Prize (1994). Current projects investigate the neural mechanisms of semantic surprisal and memory plasticity in aging populations.

• Artificial Intelligence
• Cognitive Science
• Human-Agent Interaction
• +5 more

Prof. Dr.-Ing. Stefan Kopp is a faculty member at Bielefeld University's Faculty of Engineering and serves as Research Group Leader of the Cognitive Systems and Social Interaction Group . He also holds administrative roles as Vice Dean and Deputy CITEC Coordinator . His work focuses on Artificial Intelligence , Cognitive Systems , and Socio-Technical World research areas. Research Group Leader: Cognitive Systems and Social Interaction Group Vice Dean: Faculty of Engineering Deputy Coordinator: Center for Cognitive Interaction Technology (CITEC) Project Manager: TRR 318 "Constructing Explainability" subprojects His research explores human-agent interaction , multimodal conversational agents , and social AI through projects like 39-Inf-11 Human-Machine Interaction and 39-M-Inf-VKI Virtual Humans and Conversational Agents . Publications address topics including adaptive explanation generation , gesture synthesis , and social cognition in dynamic environments. Current research topics span cooperative AI , explainable decision-making , and sensorimotor grounding in artificial systems.

• Computer Vision
• Image Analysis
• Machine Learning
• +5 more

Serge Belongie is a Professor at the Department of Computer Science (DIKU) at the University of Copenhagen, where he holds dual affiliations with the Pioneer AI research section and the Image Analysis, Computational Modelling, and Geometry section. His academic position places him at the forefront of interdisciplinary research connecting computer vision with language models, geospatial analysis, and cultural understanding. Professor Belongie's research program encompasses several critical domains in modern artificial intelligence: Advanced computer vision and image analysis techniques Vision-language model integration and multimodal systems 3D point cloud processing and semantic segmentation Geospatial representation learning for environmental applications Fine-grained object recognition and detection Cultural context understanding in AI systems His recent publication record reveals a sophisticated trajectory toward developing precise control mechanisms for vision-language models, with applications spanning forensic analysis, cultural heritage preservation, and social media understanding. The research demonstrates increasing sophistication in handling cultural context and enabling fine-grained manipulation of visual content through natural language interfaces. Professor Belongie maintains an active research group producing significant scholarly output, with over 280 research publications documented in his academic profile. His work is supported by research funding that enables cutting-edge exploration in multimodal AI systems with practical societal impact. He plays a key role in the Pioneer AI center at the University of Copenhagen, which focuses on advancing artificial intelligence through interdisciplinary collaboration and innovative research approaches that bridge theoretical computer science with real-world applications.

Yun-Nung ChenView profile

Professor

• Natural Language Processing (NLP)
• Dialogue Systems
• Machine Learning
• +3 more

Professor Yun-Nung Chen works at the Department of Computer Science and Information Engineering , National Taiwan University , focusing on Natural Language Processing and Dialogue Systems . With a Ph.D. from Carnegie Mellon University , their research bridges Machine Learning and Language Understanding in conversational AI. Education Ph.D. in Language Technologies, Carnegie Mellon University (2015) M.S. in Computer Science, National Taiwan University (2011) B.S. in Computer Science, National Taiwan University (2009) Research Trends Recent work emphasizes Retrieval-Augmented Generation , Knowledge Editing in LLMs , and Temporal Modeling for dialogue systems. Key themes include cross-modal understanding , semantics-driven dialogue , and robust language modeling across domains. Scientific Recognition Best Student Paper, IEEE ASRU 2013 Best Student Paper, IEEE SLT 2010 Distinguished Master Thesis, ACLCLP 2011 Best Paper Finalist, ISCA INTERSPEECH 2012 Current projects involve StreamBench for continuous agent improvement and Taiwan LLM for culturally aligned language models.

Raul Castro FernandezView profile

Assistant Professor

• Data Management
• Data Science
• Databases
• +6 more

Raul Castro Fernandez is an Assistant Professor of Computer Science at the University of Chicago, where he researches data ecology, a concept he created to study how data shapes our world and how we can shape it back. He is the faculty co-lead of the Data Science Institute's Data Ecology Research Initiative and a member of ChiData, the data systems research group at the University of Chicago. He is also co-founder and Chief Research Officer at invocate and co-runs Chicago Data Night, a forum connecting industry and academia in Chicago. Castro Fernandez's research focuses on data ecology, data discovery, data markets, and data integration. He develops both theory and systems that help people and organizations find, evaluate, and use data effectively. His work often uses techniques from data management, statistics, and machine learning. He has pioneered concepts in data market design, understanding the economics of data, and building platforms to support markets of data. His research on data ecology frames how data moves through and transforms technological, economic, and social systems—and how to design interventions to make those ecosystems more valuable, equitable, and resilient. His publications reveal a strong focus on data markets, data discovery, and LLM applications for data management. Recent work includes Pneuma (leveraging LLMs for tabular data), Solo (data discovery using natural language), and Nexus (correlation discovery for spatio-temporal data). His research spans theoretical foundations of data value to practical systems for data sharing and discovery. SIGMOD Test of Time Award (2023) NSF CAREER Award (2024) Sloan Research Fellowship (2025) Castro Fernandez has advised numerous PhD, Master's, and undergraduate students who have gone on to pursue PhDs at institutions like University of Washington and Stony Brook, joined companies like Google, Anthropic, and Citadel, or founded startups. His teaching includes courses on The Value of Data, Ethics in Data Science, and Introduction to Databases. He serves on program committees for major conferences including SIGMOD, VLDB, and CIDR, and has been recognized as a Distinguished Reviewer by multiple venues.

• Software Engineering
• Reverse Engineering
• Program Understanding
• +7 more

Ken Wong is an Associate Professor in the Department of Computing Science at the University of Alberta's Faculty of Science. He also serves as Associate Chair within the same department. Holding a PhD in Computer Science from the University of Victoria (1999), his research focuses on software engineering challenges such as reverse engineering, program understanding, and software visualization. He emphasizes improving software evolution through tools like architecture recovery and root cause analysis, with applications in web/mobile platforms and diverse system understanding. Teaching highlights include developing Massive Open Online Courses (MOOCs) via Coursera, including the 'Software Product Management Specialization' and courses on Agile practices, client needs analysis, and software metrics. His recent publications (2023–2025) span AI-driven healthcare innovations (e.g., medical imaging, photoacoustic tomography) and advanced computer vision techniques (e.g., diffusion models, video inpainting). Notable collaborations include EVAREST studies on heart failure management and lung transplantation outcomes. His work bridges software engineering theory and practical applications in healthcare technology, with contributions to federated learning frameworks (e.g., FedLPPA) and AI-augmented clinical decision support systems. Research also extends to autonomous driving (DriveGPT4-V2) and 3D human avatar generation (DreamAvatar), showcasing interdisciplinary impact.

• Russian and comparative literature
• the interaction of religion and culture
• the construction and dynamics of literary tradition
• +3 more

Professor Pamela Davidson is a distinguished scholar of Russian Literature at University College London's School of Slavonic and East European Studies (SSEES). With over four decades of academic experience, she has held various leadership positions including Head of the Russian Department (2003-2006), Head of Teaching and Graduate Tutor (2012-2014), and currently serves as Admissions Tutor for Languages & Cultures programmes. Her scholarly work has significantly shaped the field of Russian literary studies, particularly in areas of Russian Symbolism, literary prophecy, and the interaction between religion and culture. Doctor of Philosophy, University of Oxford, 1984 Undergraduate studies in Russian, French and Italian, Newnham College, Cambridge Professor Davidson's research spans several interconnected areas within Russian and comparative literature. Her work on the "construction and dynamics of literary tradition" examines how Russian writers positioned themselves within broader cultural and historical contexts. She has made significant contributions to understanding "the interaction of religion and culture," particularly through her edited volume "Russian Literature and Its Demons," which opened up new interdisciplinary research avenues. Her long-standing interest in "Silver Age poetry" has focused extensively on Viacheslav Ivanov, whose work she has studied through multiple lenses including his engagement with Dante and classical antiquity. Most notably, she has developed an extensive body of work on "the representation of the writer as prophet in Russia," tracing this tradition from its biblical and classical roots through to the Soviet period. Professor Davidson's recent publications reveal a consistent focus on the prophetic dimension of Russian literature, with particular attention to Viacheslav Ivanov and Fedor Glinka. Her scholarship demonstrates a sophisticated interweaving of literary analysis, religious studies, and cultural history. Over the past decade, her work has increasingly examined how Russian writers engaged with biblical and classical traditions, often reinterpreting them within specifically Russian contexts. The recurring themes across her publications include the tension between Athens and Jerusalem in Russian thought, the role of the writer as moral authority, and the complex relationship between religious tradition and literary innovation. Her comparative approach frequently bridges Russian literature with Western European intellectual traditions, revealing unexpected connections and influences. Travelling Junior Research Fellowship at Queen's College Leverhulme Research Fellowship (2019-2021) Director of the CEELBAS Centre for Doctoral Training (2020-2021) Member of the AHRC Peer Review College of Assessors (2003-2007) As an academic mentor, Professor Davidson has supervised numerous doctoral students in Russian literature and thought, with particular expertise in 19th and early 20th century literature, Silver Age poetry, and comparative literature. Her leadership roles have included serving as Graduate Tutor and Chair of BA and MA Examination Boards at SSEES. In terms of research funding, she has successfully secured competitive grants including the Leverhulme Research Fellowship that supported her recent work on literary prophecy. Her collaborative projects have often involved international partnerships, particularly with Russian academic institutions including the Institute of Russian Literature (IRLI) in St Petersburg. Professor Davidson has also contributed to major scholarly initiatives such as the 12-volume academic edition of Ivanov's collected works. While Professor Davidson's work is primarily in humanities rather than laboratory-based research, she has been instrumental in building academic networks and collaborative projects. She served as Director of the CEELBAS Centre for Doctoral Training, liaising with the Arts and Humanities Research Council (AHRC) and consortium members at Cambridge, Manchester and Oxford. Her long-standing collaboration with the St Petersburg Institute of Russian Literature has been particularly significant, resulting in the completion of the first comprehensive bibliography of Viacheslav Ivanov's works. Professor Davidson has also been active in the international scholarly community through her membership on the Board of Directors of the Foundation "Centro Studi e Ricerche Vjacheslav Ivanov" in Rome.

Anand NatarajanView profile

Assistant Professor

• Quantum Computing
• Theoretical Computer Science
• Complexity Theory
• +3 more

Anand Natarajan is an Assistant Professor at the Massachusetts Institute of Technology (MIT), affiliated with the Theory of Computation research group. His work focuses on quantum computing, complexity theory, and theoretical computer science, particularly exploring quantum verification, nonlocal games, and the intersection of quantum information with computational complexity. He is a key contributor to foundational results like the MIP*=RE theorem, which resolved longstanding questions in quantum complexity theory. Research Interests: Quantum Verification and Cryptography Quantum Complexity Classes (QMA, MIP*) Nonlocal Games and Tsirelson's Theorem Quantum Error-Correcting Codes Oracle Separations in Complexity Theory Recent Work Trends: His publications from 2020-2024 emphasize advancing our understanding of quantum advantage, noise resilience in quantum protocols, and bridging quantum computing with classical complexity theory. Notable contributions include resolving the quantum PCP conjecture via game-theoretic frameworks and analyzing the computational limits of interactive proof systems involving entangled provers. Lab/Team Affiliation: Core member of MIT's Theory of Computation group under Vinod Vaikuntanathan, collaborating on algorithms, security, and programming languages research.

Kevin BaumView profile

Researcher

• Explainable AI
• AI Ethics
• AI Fairness
• +4 more

Kevin Baum is a computer scientist currently serving as the deputy head of the Neuro-Mechanistic Modelling (NMM) department at the German Research Center for Artificial Intelligence (DFKI) since January 2023, and head of the Centre for European Research in Trusted AI (CERTAIN) at DFKI since December 2023. Based at the Saarland Informatics Campus in Saarbrücken, Germany, he completed his doctorate in philosophy in March 2024, combining technical expertise with philosophical depth. His work bridges computer science with ethics, focusing on making AI systems transparent and accountable to human users. Dr. Baum's research program centers on interdisciplinary questions concerning the explainability and transparency of AI systems. His work spans multiple significant projects including the Explainable Intelligent System (EIS) initiative and project E7 of the Transregional Collaborative Research Centre 248 "Foundations of Perspicuous Software Systems" (CPEC). He has developed frameworks for understanding stakeholder perspectives on explainable AI and investigated how different information types about automated systems affect user perceptions of fairness and justice. His approach consistently combines theoretical foundations with practical implementations across diverse contexts. Analysis of his publication trends reveals a clear trajectory from theoretical foundations in machine ethics toward practical implementations of explainability requirements in real-world contexts. His work demonstrates increasing focus on human oversight effectiveness, fairness monitoring, and ethical considerations across various AI applications. He has made significant contributions to both academic discourse and practical AI development guidelines, with publications spanning computer science, philosophy, psychology, and human-computer interaction venues. Award for Ethics for Nerds lecture series As a research leader, Dr. Baum contributes to shaping AI development practices through his departmental leadership and interdisciplinary collaborations. His current work with CERTAIN focuses on establishing European research standards for trusted AI development and deployment, emphasizing the practical implementation of ethical requirements in AI systems. He maintains active collaborations across multiple institutions and disciplines, reflecting his commitment to bridging technical and philosophical considerations in AI development. At DFKI, he leads research that combines neuroscientific insights with AI development to create more interpretable systems. The NMM department focuses on both theoretical research on explainable AI foundations and practical applications in various domains, with particular attention to how different stakeholders understand and require explanations from AI systems.

Larissa SamuelsonView profile

Professor

• Cognitive Development
• Early Word Learning
• Language Development
• +5 more

Larissa Samuelson is a Professor in the School of Psychology at the University of East Anglia, specializing in developmental cognitive science with a focus on early word and category learning. She holds administrative roles including Director of Research (2018–present). Her research integrates neural network models with empirical studies to understand how children process information and learn language. Education: BS (Honors) in Psychology, Indiana University (1993) PhD in Psychology & Cognitive Science, Indiana University (2000) Research Interests: Cognitive development in early childhood Word learning mechanisms and neural models Executive function development Cross-cultural language processing Awards: American Psychological Association Distinguished Scientific Award (2010) European Research Council Grant (2025–2031) Recipient of Leverhulme Trust funding (2025–2029) Projects: System of shape representations in cognition Neural process theory of vocabulary variability Language processing in deaf individuals Lab & Teams: Leads the Developmental Dynamics Laboratory , focusing on precision science of word learning and ensuring equitable early language potential for toddlers.