Carlo Angiuli is an Assistant Professor of Computer Science at the Department of Computer Science in the Luddy School of Informatics, Computing, and Engineering at Indiana University. His research focuses on programming languages and logic through the lens of type theory, particularly dependent types, proof assistants, and homotopy type theory. He is currently coauthoring a book on dependent type theory with Daniel Gratzer. Ph.D. in Computer Science from Carnegie Mellon University (CMU) Develops programming language foundations and computational interpretations of type theory Active in the HoTTEST Summer School organization and PL Wonks seminar group Recipient of multiple prestigious awards for type theory research His recent publications explore universe polymorphism, cubical type theory, and the intersection of category theory with programming language design. As a community builder, he organizes international research seminars and maintains experimental proof assistants like RedPRL. His teaching includes advanced courses on modern dependent types and foundational computer science topics. Scientific Awards : Best Paper Award (FSCD 2019) CMU School of Computer Science Distinguished Dissertation Award He contributes to proof assistant development and hosts the PL Wonks research group at Indiana University.
Fabrizio Falchi is a researcher at the Artificial Intelligence for Media and Humanities (AIMH) Lab of the Institute of Information Science and Technologies (ISTI) within Italy's National Research Council (CNR). He also maintains an associate position at the Biorobotics Institute of Scuola Superiore Sant'Anna. His work focuses on developing advanced multimedia retrieval systems, with the VISIONE platform being his most notable contribution, which has won international competitions including the Video Browser Showdown in 2024 and placed second in 2023. Falchi's educational background includes: Ph.D. in Information Engineering from University of Pisa (Italy) Ph.D. in Informatics from Faculty of Informatics of Masaryk University of Brno (Czech Republic) M.B.A. from Scuola Superiore Sant'Anna in Pisa His research spans deep learning, convolutional neural networks, deep features extraction, similarity search algorithms, distributed indexing systems, multimedia information retrieval, computer vision applications, and peer-to-peer systems. Falchi has made significant contributions to fine-grained visual understanding, cross-modal retrieval (particularly image-text matching), and robustness of deep learning systems against adversarial attacks. His work demonstrates a strong focus on practical applications of these technologies, particularly in video retrieval systems and safety monitoring solutions. Analysis of Falchi's recent publications reveals a strong focus on video and image retrieval systems, with the VISIONE platform being central to his work. His research shows increasing emphasis on fine-grained understanding in computer vision, cross-modal retrieval, and addressing practical challenges like cross-resolution face recognition. Recent work demonstrates innovation in making these systems more efficient through techniques like knowledge distillation (ALADIN) and leveraging virtual worlds for training data. His publications consistently bridge theoretical advances with practical applications in surveillance, safety monitoring, and multimedia search. Falchi's work has received significant recognition: Best paper award at CBMI 2024 for 'Is ClLIP the main roadblock for fine-grained open-world perception?' VISIONE 2024 won the Video Browser Showdown competition in Amsterdam VISIONE obtained second place at Video Browser Showdown 2023 in Bergen Best Paper Award for 'Learning Safety Equipment Detection using Virtual Worlds' at CBMI 2019 Falchi collaborates extensively with researchers at ISTI-CNR, particularly within the AIMH Lab. His work on VISIONE involves collaboration with Giuseppe Amato, Paolo Bolettieri, Fabio Carrara, Claudio Gennaro, Nicola Messina, Lucia Vadicamo, and Claudio Vairo. As co-chair of Ital-IA 2023, the 3rd National Conference on Artificial Intelligence, he plays an active role in the academic community. He is a member of ACM (since 2012), the Computer Vision Foundation, the Italian Association for Computer Vision Pattern Recognition and Machine Learning (CVPL), and the CINI Lab on Artificial Intelligence and Intelligent Systems. Falchi is a key member of the Artificial Intelligence for Media and Humanities (AIMH) Lab at ISTI-CNR, where he leads research on video retrieval systems. The lab has developed the award-winning VISIONE platform, which combines multiple scientific results in content-based video retrieval. His team focuses on developing systems that enable users to search for target videos using textual prompts, drawing objects and colors, or images as query examples. The lab's work demonstrates strong interdisciplinary collaboration, bridging computer science with practical applications in media, safety monitoring, and urban environments.
Kavita Bala is the 17th Provost of Cornell University and a Professor of Computer Science. She previously served as the inaugural Dean of the Cornell Ann S. Bowers College of Computing and Information Science, leading its transition to a degree-granting college by 2025, and as Chair of Cornell’s Department of Computer Science. Her academic leadership includes expanding faculty, establishing research programs like the Bowers CIS Undergraduate Research Experience (BURE), and securing a new research facility for computing and information science. Education: B.Tech (IIT Bombay), M.S. and Ph.D. (MIT, Computer Science) Bala’s research focuses on computer vision, artificial intelligence, and computer graphics , with groundbreaking work in material and style recognition using deep learning. Her innovations in crowdsourced training data and differentiable rendering have advanced visual search technologies and translucent material modeling, powering her startup GrokStyle. She pioneered AI techniques applied to environmental monitoring through projects like MONITRS and AllClear , addressing Earth observation challenges. Her scientific awards include: American Academy of Arts and Sciences (2025) SIGGRAPH Computer Graphics Achievement Award (2020) IIT Bombay Distinguished Alumnus Award (2021) ACM Fellow (2019) SIGGRAPH Academy Fellow (2020) As Provost, Bala drives strategic initiatives like the Cornell AI Initiative , creating interdisciplinary minors in AI and AI in Society, and establishing the Schmidt AI in Science postdoctoral program. She co-chaired a task force for generative AI guidelines in education.
Craig Knoblock serves as Keston Executive Director of the Information Sciences Institute (ISI) at the University of Southern California (USC), Vice Dean of the USC Viterbi School of Engineering, and Research Professor of Computer Science and Spatial Sciences. He also directs the Data Science Program and the Center on Knowledge Graphs at USC. His educational background includes a Ph.D. and M.S. in Computer Science from Carnegie Mellon University (1991, 1988) and a B.S. with honors in Computer Science from Syracuse University (1984). Knoblock's research focuses on data semantics , specializing in source modeling, schema and ontology alignment, entity and record linkage, data cleaning, Web data extraction, and knowledge graph construction. His work bridges computer science, geospatial analysis, and artificial intelligence to solve complex data integration challenges. Recent projects emphasize historical map digitization, geospatial knowledge graphs, and smart city applications. His 300+ publications demonstrate consistent contributions to knowledge graphs and geospatial data integration, with a growing emphasis on historical map analysis and urban applications. The research trajectory shows increasing interdisciplinary collaboration across computer vision, geoinformatics, and domain-specific applications. IEEE Fellow (2020) ACM Fellow (2017) AAAI Fellow (2004) Robert S. Engelmore Memorial Lecture Award (2014) Donald E. Walker Distinguished Service Award (IJCAI, 2018) Use-Inspired Research Award (USC Viterbi, 2018) As Executive Director of ISI, Knoblock oversees one of USC's premier research centers with significant federal funding. His leadership extends to directing the Center on Knowledge Graphs and the Data Science Program. While specific grant details aren't provided, his extensive publication record and leadership roles indicate substantial research funding across data integration, knowledge representation, and geospatial applications. His work bridges theoretical computer science with practical applications in historical preservation, urban planning, and resource management through collaborative projects with government agencies and industry partners. Knoblock leads the Center on Knowledge Graphs at USC, focusing on developing techniques for building and utilizing knowledge graphs across diverse domains. His team combines expertise in artificial intelligence, geospatial analysis, and data integration to tackle challenges in historical map digitization, urban applications, and resource discovery. The research group maintains strong connections with both academic and government partners through the Information Sciences Institute's extensive network.
Dr. Hua Xu is the Robert T. McCluskey Professor of Biomedical Informatics and Data Science at Yale School of Medicine. He serves as Vice Chair for Research and Development in the Department of Biomedical Informatics and Data Science and as Assistant Dean for Biomedical Informatics at Yale School of Medicine. Dr. Xu leads the Clinical NLP Lab and is Chair of the NLP working group at the Observational Health Data Sciences and Informatics (OHDSI) program. Dr. Xu received his PhD in Biomedical Informatics from Columbia University, an MS in Computer Science from New Jersey Institute of Technology, and a BS in Biochemistry from Nanjing University. Dr. Xu is a renowned researcher in clinical natural language processing (NLP), having developed novel algorithms for important clinical NLP tasks such as entity recognition and relation extraction. His work has been top-ranked in over a dozen international biomedical NLP challenges. He has developed CLAMP, a comprehensive clinical NLP toolkit that has been successfully commercialized and adopted by hundreds of healthcare organizations worldwide. His research focuses on applying NLP technologies to diverse clinical and translational studies to accelerate clinical evidence generation using electronic health records data. Recently, he has been utilizing NLP to harmonize metadata of biomedical digital objects to promote FAIR principles in biomedicine, and his lab is actively working on developing large language models (LLMs) for diverse biomedical applications. Dr. Xu's recent publications demonstrate a clear trend toward leveraging large language models for biomedical applications. His work spans from benchmarking LLMs for clinical NLP tasks to developing specialized architectures like BiomedRAG (retrieval augmented LLMs for biomedicine). His research addresses critical healthcare challenges including adverse event extraction, oncology clinical trial analysis, and EHR-based association studies, showing how NLP can bridge the gap between unstructured clinical text and actionable medical insights. Dr. Xu's lab has achieved top rankings in numerous NLP challenges, including multiple #1 positions in i2b2 Temporal information extraction, SemEval Disease-modifier extraction, BioCREATIVE Chemical-induced disease extraction, and other prestigious competitions. His contributions to clinical NLP have significantly advanced the field's ability to extract meaningful information from complex medical texts. As the leader of the Clinical NLP Lab at Yale, Dr. Xu oversees research that forms a complete ecosystem: developing novel NLP methods, building robust software tools, and applying these technologies to clinical and translational research. His lab's work closes the loop between methodological innovation and practical healthcare applications, ensuring that advances in NLP directly benefit patient care and medical research.
Kai R. Larsen is a Professor at the Organizational Leadership and Information Analytics division within the Leeds School of Business , University of Colorado Boulder . He holds courtesy faculty appointments in the Department of Information Science at the College of Media, Communication and Information , serves as a Research Advisor to Gallup , and is a Fellow of the Institute of Behavioral Science . Education: Ph.D., Information Science, University at Albany, SUNY Candidatus Magisterii (Software Engineering), The National College for Teachers of Commerce, Norway Adjunkt (Education), The National College for Teachers of Commerce, Norway Diplomkandidat, NHI College of Computer Science, Norway His research focuses on Information Systems , particularly addressing the Jingle Fallacy and developing the Semantic Theory of Survey Response . He leads the Federally Supported Human Behavior Project , creating transdisciplinary frameworks using Large Language Models and Natural Language Processing to predict human behaviors across technology utilization, investor decisions, voter behaviors, and cancer prevention. His scientific awards include INFORMS ISS Design Science Award (2019) Best Prototype Award at WITS (2019) Herbert A. Simon Award (2020) David B. Balkin Innovative Teaching Award (2023) Kolb Teaching Award (2022) National Institutes of Health $355,000 Grant (2022-2023) Larsen's grant funding and mentorship achievements include NIH grant for stress ontology research Outstanding Faculty Mentor Award (2021-2022) Technology Challenge Award (2016) He also maintains the Theories Used in IS Wiki and developed the TheoryOn award-winning ontology-based search engine used by thousands.
Shuhao Fu is a Program Postdoctoral Fellow at the Santa Fe Institute (SFI) researching the intersection of machine learning and cognitive science. He completed his Ph.D. in Psychology at UCLA under advisors Hongjing Lu and Ying Nian Wu, following a B.S. in Computer Science and Mathematics from Hong Kong University of Science and Technology. His research examines human-like relational reasoning in AI systems through cognitive modeling and computational approaches. Research focuses on: Bridging human-machine reasoning gaps via analogical mapping Developing explicit relational representations in vision models Structural cognitive modeling for compositional understanding Multimodal reasoning and scene interpretation Relational knowledge representation in biological and artificial systems Publication trends show concentrated work in computational cognitive science (2021-2025), with evolving focus from visual analogy fundamentals to applications in 3D recognition, social interaction modeling, and mental health diagnostics. Recent work demonstrates increased emphasis on transformer architectures, multimodal integration, and human-AI comparative studies. Professional experience includes research internships at Google X and Mineral.ai, with prior affiliation at Johns Hopkins University's CCVL lab under Alan Yuille. Currently serves as reviewer for ICML, ICCV, and Cognitive Science Society conferences.
Lisa Nathan is an Associate Professor and current PhD Program Chair at the University of British Columbia's School of Information, situated on unceded Musqueam territory. Her academic home resides within the Department of Library, Archival and Information Studies under the Faculty of Arts, where she directs doctoral studies and teaches specialized courses in information ethics and climate justice. Her research examines the critical intersection of information policy, sustainability, and Indigenous knowledge systems, exploring how information ecosystems shape societal values through frameworks like climate justice and multi-lifespan design. Nathan's work consistently centers on disrupting colonial information practices while developing ethical alternatives through community-engaged scholarship, particularly evident in her collaborations with Indigenous communities on language preservation and cultural protocols. Analysis of her recent publications reveals a strong trajectory toward decolonial computing and environmental justice, with increasing emphasis on Indigenous-led information initiatives and the inclusion of 'other-than-human' participants in design processes. Her scholarly output spans high-impact journals including Journal of Documentation and First Monday, alongside influential books like Digital Technology and Sustainability: Engaging the Paradox. Outstanding Information Science Teacher Award (2017) Honorable Mention Paper Award at ACM CSCW (2016) Leadership in ACM SIGCHI Sustainability initiatives British Columbia Library Association Climate Action Committee Nathan actively supervises doctoral research through UBC's Indigenous Information Studies pathway, currently mentoring Rodrigo dos Santos while having guided recent graduates including Shaffer, Shankar, and Kaczmarek to completion. Her service includes chairing the First Nations Curriculum Concentration (2010-2018) and developing innovative courses like LIBR 564: Information Practice and Protocol in Support of Indigenous Initiatives. As Director of the Centre for Climate Justice research cluster, she fosters interdisciplinary collaborations addressing information policy's role in environmental crises.
Verena Wagner is a Professor of Philosophy of Mind at Humboldt University of Berlin and the Berlin School of Mind and Brain. Her academic work spans cognitive philosophy with a particular focus on suspension of judgment, belief formation, and cognitive neutrality. She maintains an active research profile with numerous presentations at major European academic institutions. Wagner's research interests center on epistemological questions related to cognitive states and doxastic attitudes. Her work explores the philosophical implications of suspending judgment, cognitive neutrality, and the relationship between belief and inquiry. She has developed a taxonomy of cognitive neutrality that appears to be a significant contribution to contemporary philosophy of mind. Her recent publications and presentations demonstrate a clear trajectory toward understanding how cognitive neutrality functions within epistemic frameworks, with particular attention to applications in machine learning contexts and political discourse. Her work bridges traditional philosophical inquiry with contemporary technological and social challenges. Wagner has presented her research at numerous prestigious institutions including Central European University, University of Heidelberg, University of Tübingen, and Free University Berlin. Her work has been featured in specialized workshops on epistemology, philosophy of mind, and cognitive science.
Kathryn Stolee is an Associate Professor in the Department of Computer Science at North Carolina State University. She received her Ph.D. in Computer Science from the University of Nebraska-Lincoln under Sebastian Elbaum after graduating from the Jeffrey S. Raikes School of Computer Science and Management. Her research spans multiple perspectives in software engineering: technical (program analysis), human (human aspects of software engineering, software product management), and educational (comparative comprehension of algorithms). Notable contributions include work on regular expression refactoring for improved comprehension, constraint solvers for code reuse identification, and cross-language code-to-code search to aid developers learning new languages. Dr. Stolee has secured over $2,000,000 in federal grants, including an NSF CAREER award. Her research combines analysis techniques (refactoring, semantic code search, code-to-code search) with human factors (comprehension, reuse, learning). Her scholarly contributions have been recognized with a National Science Foundation Faculty Early CAREER Award (2018) and a Best Paper Award at the International Symposium on Empirical Software Engineering and Measurement (ESEM, 2011). Actively engaged in the software engineering research community, Dr. Stolee serves as an author, reviewer, and organizer at top conferences. She is committed to mentoring the next generation of computer scientists and has developed educational interventions focused on software testing and code comprehension.
Franziska Klügl is a Professor in Computer Science at Örebro University's Faculty of Business, Science and Engineering, affiliated with the Center for Applied Autonomous Sensor Systems (AASS). She currently leads the KKS-funded TeamRob project on Human-Robot Teamwork and serves as Deputy Dean of the faculty since January 2023, chairing the academic appointment committee. Previously, she headed the Computer Science department (2020-2022) and served on the faculty board (2019-2022). Her research focuses on: Multi-agent systems : Development of languages, processes, and tools for agent-based simulation Interdisciplinary applications : Transportation, economics, epidemics, production, and mining simulations Simulation engineering : Integrating AI, machine learning, and formal methods to create accessible modeling tools for domain experts She created SeSAm , a visual programming tool for agent-based simulation that enables rapid prototyping of complex models. Analysis of her recent publications reveals three dominant themes: Human-robot collaboration frameworks and intention recognition systems Economic impacts of automation on labor markets and engineering services Advanced simulation methodologies using affordance theory and reinforcement learning She teaches software engineering, multi-agent systems, and agent-based modeling across multiple programs, including the WASP AI&ML PhD course. She leads research groups at the Machine Perception and Interaction Lab and oversees the TeamRob human-robot teamwork project.
Eduard Kamburjan is a Researcher at the University of Oslo , affiliated with the Reliable Systems (PSY) and Data and Knowledge Systems (DKM) research groups. His work bridges formal methods , digital twin engineering , and knowledge graph applications . Research interests include: Formal verification of hybrid systems using deductive methods Digital twin architecture with compositional correctness guarantees Semantic lifting and ontology-driven modeling for complex systems Concurrency analysis and non-determinism in program verification Interactive visualization as serious games for formal methods His 2024-2023 publications demonstrate expertise in digital twin reconfiguration , semantic interoperability , and knowledge-based runtime enforcement . Key contributions include Crowbar for active object verification and ABS simulator toolchain for model-driven engineering. Collaborations span institutions like Springer , ACM , and IEEE , with work featured in Lecture Notes in Computer Science (LNCS) , Software and Systems Modeling (SoSyM) , and Science of Computer Programming . His research integrates RDF data management , behavioral contracts , and modular analysis for distributed systems.
Danh Le Phuoc is a Principal Computer Scientist at Technical University of Berlin, leading research at the PICOM.AI lab where his team develops autonomous information systems for robotics, autonomous vehicles, and IoT systems through pervasive intelligence in complex networks. With over 70 publications and significant academic impact (6811 citations, H-index 31), he has established himself as a notable researcher in semantic technologies. His educational background isn't explicitly detailed in the provided text, but his research expertise spans multiple domains requiring advanced technical knowledge. Le Phuoc's research focuses on bridging theoretical concepts with practical system implementation, particularly in RDF Stream Processing, Semantic Web technologies, and IoT middleware. His work emphasizes building real-world systems that process linked streams and data in real-time, enabling applications in intelligent transportation systems and connected vehicles. His research trajectory shows consistent innovation from foundational work on semantic mashups (2009) through to advanced stream processing frameworks (2017). His publications reveal strong trends toward processing real-time semantic data streams, with increasing focus on scalability, performance optimization, and integration of IoT systems with knowledge graphs. The progression shows movement from basic semantic web pipes to complex, elastic cloud-based stream processing systems. 22 Awards, Honours, Fellowships and Grants 10+ awards for innovative Semantic Web applications Multiple honors for IoT applications As an obsessive builder, Le Phuoc has developed numerous influential systems including The Graph of Things, CQELS (Continuous Query Evaluation over Linked Streams), Semantic Web Pipes, and Linked Sensor/Stream Middleware. His current focus is on ASAP (Autonomous Semantic Stream Processing), a platform for connected vehicles and intelligent transportation systems. His lab appears to maintain active GitHub repositories for several of these systems, suggesting ongoing development and community engagement.
Jieh Hsiang is a Distinguished Professor at National Taiwan University , with affiliations in the Department of Computer Science and Information Engineering, the Digital Archives and Automatic Inference Laboratory, and the Digital Humanities Research Center. He holds concurrent roles at the Institute of Information Science, Academia Sinica, and the Higher Education Research & Development Office, National Taiwan University. Education PhD in Computer Science, University of Illinois at Urbana-Champaign (1979–1982) BS in Mathematics, National Taiwan University (1972–1976) Research Interests Hsiang's work spans automated reasoning , digital libraries , digital humanities , and information retrieval . His research focuses on integrating computational methods with cultural heritage preservation , particularly through tools like DocuSky and databases such as the Taiwan Historical Digital Library . He explores AI applications in patent analysis , historical text mining , and semantic relationships in legal documents . Recent Trends in Publications His recent articles highlight advancements in BERT and GPT-2 fine-tuning for patent classification , LARGE language models for legal automation , and GIS-based analysis of historical archives . Themes include digital preservation , AI-driven legal text analysis , and cross-disciplinary computational tools for humanities scholars. Scientific Awards 2019 Ministry of Science and Technology Distinguished Research Fellow 2009 National Taiwan University Outstanding In-House Service Award 2008 Chinese Library Association Special Contribution Award 2006 IEEE Test-of-Time Award 1997 & 1999 National Science Council Outstanding Research Award 1997 Ministry of Education Outstanding Industrial-Academic Collaboration Award 1998–2001 Founder and First Chair of IFIP WG1.6 Labs and Collaborations Hsiang leads the Digital Archive and Automatic Inference Laboratory , developing platforms like DocuSky for digital humanities, Taiwan Historical Digital Library , and QGIS Cloud Maps for spatial analysis. His team collaborates internationally on projects involving historical document digitization , patent automation , and cross-domain knowledge integration .
Ali Hamie is a Senior Lecturer at the School of Architecture, Technology and Engineering (University of Brighton, UK), specializing in formal methods in software engineering and ontology modeling. With over 35 publications, his work bridges theoretical formalisms like UML, OCL, and JML with practical implementation validation. BSc in Pure Mathematics (Lebanese University, 1982) Postgraduate Diploma in Computing (University of Essex, 1986) MSc in Computer Science (University of Essex, 1987) PhD in Computer Science (University of Essex, 1991) His research focuses on formal aspects of software development , including specification patterns, design by contract, and translation between formal notations (OCL to JML). Recent work examines diagrammatic reasoning in ontology engineering and hybrid modeling approaches combining formal and agile methods. Studies show his publications span formal methods , ontology modeling , and constraints validation , with recurring themes in OCL-JML interoperability, diagrammatic notations, and user-centric formalism evaluation. Awards include Fellow of the Higher Education Academy (2017) . He supervises research in formal computing, with past topics covering concept diagrams and ontology modeling. His academic career includes postdoctoral roles at Newcastle University and EPSRC-funded work at Imperial College.
