Eleanor Dickey is a Professor of Classics at the University of Reading. She has held academic positions at Columbia University, the University of Exeter, and the University of Ottawa. Her research focuses on Greek and Latin linguistics, classical literature, and ancient language use, with a particular emphasis on papyrology and historical pragmatics. She holds a D.Phil. in Literae Humaniores from the University of Oxford and has held fellowships at institutions including the Institute for Advanced Study in Princeton and All Souls College, Oxford. Education: BA (summa cum laude) and MA from Bryn Mawr College; M.Phil. and D.Phil. from Oxford University. Her research interests include the study of ancient language pedagogy, sociolinguistics in antiquity, and the analysis of Greek and Latin texts in papyri. She has authored several influential books, including Ancient Greek Scholarship and Latin Forms of Address . Her work explores the intersection of language, culture, and social dynamics in the ancient world. Key awards include the 2014 Fellowship of the British Academy and the 1996 Hellenic Foundation Prize. Her contributions to classical scholarship have been recognized through teaching accolades and research fellowships worldwide.
Dr. Tim Oates is a Professor in the Department of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County . His research spans machine learning, artificial intelligence, and brain-machine interfaces, with a focus on weakly supervised methods, human-in-the-loop reinforcement learning, and grounded policy development for robotics. Ph.D., Computer Science, University of Massachusetts, Amherst, 2000 M.S., Computer Science, University of Massachusetts, Amherst, 1997 B.S., Computer Science and Electrical Engineering, 1989 Current research threads include: Developing non-invasive brain injury severity assessment via medical time series Modeling human brain development through computational frameworks Designing algorithms for autonomous robotic learning Recent publications highlight AI security mechanisms (backdoor detection via tensor decomposition, matrix factorization) Medical applications (3D artery reconstruction, skin lesion diagnosis, EEG denoising) Neuro-symbolic integration (holographic representations, language-guided reinforcement learning) Mathematical reasoning (schema-based problem solving, subitizing algorithms) Contact: oates@cs.umbc.edu | Office: 336 Information Technology and Engineering (ITE) Building
Novi Quadrianto is a Professor of Machine Learning at the School of Engineering and Informatics, University of Sussex, where he joined as a Lecturer in February 2014. He is currently a Principal Investigator on three active EU grants: BayesianGDPR (ERC), TANGO (EU Horizon RIA), and Act.AI (ERC Proof of Concept). He also holds an Adjunct Professor position in Data Science at Monash University, Indonesia, and serves as Strategic Lab co-Leader of the BCAM Severo Ochoa Strategic Lab on Trustworthy Machine Learning in Bilbao, Spain. His educational background includes a PhD in Machine Learning from the Australian National University (2012) and a BEng in Electrical and Electronics Engineering from Nanyang Technological University, Singapore. During his PhD, he conducted research at multiple international institutions including HIIT-Finland, Yahoo! Research-US, University of Alberta-Canada, Fraunhofer IAIS-Germany, and IST Austria. From 2012-2014, he was a Newton International Fellow of the Royal Society at the University of Cambridge. Professor Quadrianto directs the Predictive Analytics Lab (PAL) since 2017, which focuses on "Responsible AI" research developing AI models that embed fairness, accountability, transparency, and trustworthiness. His research spans algorithmic fairness, federated learning, and computer vision, with applications in sustainable development, healthcare, and finance. His work has been funded by prestigious organizations including the European Research Council, EPSRC, and HM Treasury. His publications reveal a strong focus on addressing challenges in AI fairness, robustness, and privacy, particularly in dynamic environments and heterogeneous data settings. Recent work explores performative prediction, diversity-driven learning, and efficient vision transformer inference, demonstrating his leadership in cutting-edge machine learning research. European Research Council ERC Proof of Concept Grant (2023) Guarantor Researcher for BCAM Severo Ochoa Excellence Accreditation (2023) European Lab for Learning and Intelligent Systems (ELLIS) Scholar/Fellow (2020) European Research Council ERC Starting Grant (2019) Newton International Fellowship (2012) Microsoft Research Asia Fellowship (2009) Professor Quadrianto currently supervises six PhD students and five postdoctoral researchers. He has served as Action Editor for Transactions on Machine Learning Research since 2022 and as Associate Editor for IEEE Transactions on Pattern Analysis and Machine Intelligence since 2016. He has also been an Area Chair for major conferences including NeurIPS, ICML, and AAAI. His PAL laboratory hosts a team of 15 members focused on inter-disciplinary AI research with domain experts across various sectors. The PAL Lab operates three innovation strands: AI for Sustainable Development (supporting UN SDGs), AI for Healthcare (transforming health outcomes), and AI for Finance (personalized loan decision-making). The lab also leads initiatives in Diversity & Inclusion in AI and offers Pro-Bono Office Hours to organizations seeking guidance on machine learning aspects.
Lisa Beinborn is a Professor for Human-Centered Data Science at the University of Göttingen, leading the Human-Centered Data Science group. Her research bridges natural language processing with cognitive science, focusing on multilingual models and interpretability. PhD in Computer Science (2016), Technische Universität Darmstadt MSc in Computational Linguistics (2010), Saarland University & Bolzano, Italy BSc in Computational Linguistics (2008), Saarland University & Barcelona, Spain Her research explores cognitive plausibility in NLP, analyzing how language models process language differently from humans. Key areas include multilingual model interpretability, semantic drift, eye-tracking, and readability prediction. Recent work examines input representation stability in neural models, cross-lingual transfer of complexity, and aligning language models with human cognitive patterns. Her team has presented findings at EMNLP, CoNLL, ACL, and CoLING. VENI Grant for "Interpretability of Transfer in Multilingual Models" Early Career Partnership by Royal Dutch Academy of Science "Most Interesting Paper" Award at BabyLM Challenge "Best Project Award" by Network Institute She has taught courses like Language as Data and Advanced NLP at University of Göttingen, VU Amsterdam, and TU Darmstadt. Her group collaborates with institutions like Gemeente Amsterdam and NT2 on multilingual text simplification and learner correction.
Maria Gendron is an Assistant Professor in the Department of Psychology at Yale University, where she directs the Affective Science and Culture Lab. Her research examines how emotions emerge through dynamic interactions between social, cognitive, and cultural systems, challenging universalist perspectives on emotion. She employs multidisciplinary methodologies including neuroimaging meta-analyses, cross-cultural fieldwork with indigenous communities, and ambulatory physiological assessments. Research Focus : Dr. Gendron investigates: The role of conceptual/semantic systems in constructing emotional experiences Cultural variation in emotion perception across diverse societies Bio-behavioral synchrony in emotion development Linguistic influences on affective processing Her work integrates frameworks from affective neuroscience and cultural psychology to understand emotion diversity. Publication Trends : Her 15 most recent articles (2010-2025) focus on deconstructing emotion universality through cross-cultural comparisons, with recurring themes of: Cultural relativity in facial/vocal emotion interpretation Language as a contextual framework for emotion Conceptual and semantic mechanisms underlying affect Methodological innovations for studying emotion diversity Lab Leadership : She directs the Affective Science and Culture Lab at Yale, advancing research on emotion perception using multimodal approaches including behavioral experiments, physiological monitoring, and fieldwork.
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.
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.
Prof. dr. Enoch O. Aboh is Professor of Linguistics at the University of Amsterdam , Faculty of Humanities, Department of Literature and Linguistics. His office is located at Spuistraat 134, room 647, and he can be contacted at e.o.aboh@uva.nl . Research Interests: Prof. Aboh’s work lies at the intersection of formal syntax, language contact, and learnability. He investigates creole formation , multilingual ecologies , Gbe and Kwa syntax , cartographic approaches to clause structure , and sign language morphosyntax . A recurring theme is the emergence and evolution of grammatical systems under contact, approached through both descriptive fieldwork and formal theoretical modelling. His publications reveal a methodological breadth spanning experimental studies with kindergarteners on statistical learning, computational detection of loanwords, and fine-grained syntactic analyses of serial verb constructions, predication patterns, and determiner systems. This spectrum underscores his commitment to integrating cognitive, typological, and formal perspectives on language. Awards & Recognition: While no specific prizes are listed in the current material, Prof. Aboh’s extensive editorial and collaborative work—evidenced by numerous co-edited volumes and Festschrift contributions—attests to his standing in the field. Students & Grants: Details on PhD advisees or funded projects are not provided in the source text. Labs & Teams: No dedicated laboratory or research group names are mentioned, yet his affiliation with the Amsterdam Center for Language and Communication (ACLC) can be inferred from the institutional context.
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.
Timothy Williamson is a prominent Professor of Philosophy at the University of Oxford, holding the prestigious Wykeham Professorship of Logic. His academic career spans several decades with continuous contributions to analytic philosophy, particularly in epistemology, metaphysics, and philosophical logic. His work has positioned him as one of the leading philosophers of his generation. Williamson's research interests concentrate on epistemology (particularly his influential knowledge-first approach), metaphysics, philosophy of language, and philosophical logic. His work on vagueness champions epistemicism—the view that vague predicates have sharp boundaries that we cannot know. His book Knowledge and its Limits revolutionized epistemological thinking by placing knowledge rather than belief at the center of epistemological theory. Williamson has also made significant contributions to modal metaphysics, higher-order thought, and the philosophy of logic. His publication record reveals consistent engagement with foundational philosophical problems across several decades. His most recent work continues his exploration of knowledge-first epistemology while expanding into moral epistemology and methodological questions in philosophy. Williamson's articles demonstrate a distinctive blend of logical precision and philosophical depth, often using formal methods to address traditional philosophical problems. His work frequently intersects with debates in philosophy of language, metaphysics, and philosophical methodology. Williamson has been actively engaged in scholarly debate through numerous replies to critics, demonstrating his commitment to rigorous philosophical dialogue. His publications span major philosophy journals including Synthese , Canadian Journal of Philosophy , Analysis , and Philosophy and Phenomenological Research . Throughout his career, Williamson has mentored numerous graduate students and collaborated with leading philosophers across the globe. His methodological approach emphasizes the value of formal modeling in philosophical inquiry, arguing that philosophy can benefit from the model-building approaches common in natural sciences.
Prof. Bart Streumer is a Professor of Ethics at the University of Groningen, Netherlands. Previously, he held positions at the University of Reading and Fitzwilliam College, Cambridge. His research focuses on metaethics, particularly the error theory regarding normative judgments, arguing that such judgments cannot be believed yet are likely true. He serves as an Associate Editor for the Journal of Moral Philosophy and is a Board member of Stichting Jazz in Groningen. Streumer has authored influential works like Unbelievable Errors , exploring skepticism about moral and normative truths. His teaching includes courses on metaethics, free will, and property metaphysics. Education: Research Fellow at Fitzwilliam College, Cambridge; Lecturer/Reader at University of Reading. Research Interests: Metaethics, error theory, normative judgments, moral skepticism. Key Publications: Unbelievable Errors (2017), articles in Noûs , Philosophy and Phenomenological Research , and Analysis . Teaching (2024-25): Courses on Free Will and Responsibility, Metaethics, Advanced Metaethics, and the Metaphysics of Properties. Ancillary activities include editorial work and jazz-related community involvement.
Gemma Boleda is an ICREA Research Professor at Universitat Pompeu Fabra in Barcelona, Spain, where she co-directs the Computational Linguistics and Linguistic Theory (COLT) research group. Her research focuses on understanding how humans convey meaning through language, investigating the formal properties that support communication, and exploring how languages are shaped by cognitive and communicative factors. Her primary interests include lexical semantics, cross-linguistic variation, and the integration of linguistic theory with computational methods. She employs interdisciplinary approaches combining linguistics, artificial intelligence, and cognitive science, utilizing large-scale data analysis to study universal patterns and variations across languages. Boleda's publications demonstrate a consistent focus on computational semantics, lexical variation, and language evolution. Her recent work explores the intersection of symbolic and neural approaches to language processing, lexical creativity across development and evolution, and computational models of semantic phenomena like colexification and polysemy. She teaches Computational Semantics in the Master's in Theoretical and Applied Linguistics program and has secured significant research funding including ERC Starting Grants. Her work has contributed valuable linguistic resources such as the ManyNames dataset and Database of Catalan Adjectives.
Dr. Sasha Rubin is a Senior Lecturer and leader of the Computational Logic for AI (LOGIC-AI) group at the School of Computer Science, The University of Sydney. He holds a PhD in Mathematics and Computer Science from the University of Auckland and previously worked at the University of Naples Federico II. His research focuses on logic foundations of AI, including synthesis, planning, formal methods, and multi-agent systems. He teaches courses like Models of Computation and supervises students in topics like probabilistic systems and reinforcement learning. Research Interests: Mathematical Logic, Formal Verification, Temporal Logic Synthesis, Automated Reasoning, and Multi-Agent Systems. He has published extensively in top venues like IJCAI, AAAI, and ACM Transactions. His work includes verification of agent navigation, strategy logic, and planning under uncertain environments. Awards: Recognized as an Australian Research Field Leader in Theoretical Computer Science (2020). He serves on editorial boards for JAIR and conferences like KR, and organizes events such as the Australasian Association for Logic Conference (2024). Supervision and Grants: Current students include Ethan HIRSCHOWITZ and Kunal OSTWAL. Past supervision spans MPhil/PhD projects on probabilistic systems, ML classifier fairness, and symbolic automata. His grants include studies on logic and robots in anonymous graphs. Professional Activities: Member of EATCS, ACM, and mentor for the Sydney Summer Innovation Programme. He leads the LOGIC-AI lab and collaborates internationally, notably with Giuseppe De Giacomo at Sapienza University of Rome.
Dr. David Cock is a Senior Lecturer and Senior Researcher at ETH Zürich's Department of Computer Science, affiliated with the Systems Group. He holds a PhD from UNSW (2014) and a B.Sc. (hons) from UNSW (2004). His research focuses on formal verification, trustworthy systems, and hardware-software co-design, with notable contributions to projects like Enzian (a CPU/FPGA platform) and seL4 (formally verified kernel). He teaches Advanced Operating Systems and Informal Methods courses. Key achievements include the ACM Software System Award (2022) for seL4 and leadership in projects addressing hardware complexity and security. Research interests include formal methods for hardware modeling (Sockeye project), runtime verification, and mitigating timing channels. His work bridges theoretical foundations with practical systems, emphasizing secure and reliable computing platforms. Projects like Trustworthy BMC aim to enhance baseboard management systems' assurance. Collaborations span academia and industry, with open-source contributions to hardware designs and formal tools. Publications span formal verification, hardware modeling, and secure systems, with recent focus on heterogeneous computing and declarative hardware specifications. Teaching emphasizes practical formal techniques and OS design, leveraging real-world hardware (e.g., Barrelfish). His lab, the Systems Group, explores cutting-edge challenges in systems software and architecture.
Jisun An is an Assistant Professor at the Luddy School of Informatics, Computing, and Engineering, Indiana University Bloomington (IUB), leading the Social Data and AI (SODA) Lab. Previously, she held positions at Singapore Management University (SMU) and the Qatar Computing Research Institute (QCRI). She earned a Ph.D. in Computer Science from the University of Cambridge (2015), supported by EPSRC, and received the Google European Scholarship. Her research focuses on computational social science, leveraging NLP and machine learning to analyze social media, political communication, health informatics, and journalism. Education: Ph.D. in Computer Science (University of Cambridge, 2015). Notable roles include Associate Editor of EPJ Data Science and PC member for conferences like ICWSM, ACL, and AAAI. She co-organized the News and Public Opinion (NECO) workshop (2016-2020). Teaching includes courses on Performance Analytics and Computational Social Science. Research highlights include studies on media attention patterns, user engagement, hate speech detection, and public health campaigns. Her work bridges interdisciplinary gaps, combining theoretical foundations with practical computational methods. Recent projects explore discursive power in media systems and predictive modeling of collective behavior. Awards: Google European Scholarship Key Projects: Discursive Power in Media, Precision Public Health Campaigns, and Algorithmic Bias Analysis Labs/Teams: SODA Lab at IU, previously contributed to QCRI's research initiatives
