Yurui Gao is a Research Professor of Biomedical Engineering at Vanderbilt University's School of Engineering. His work focuses on small animal and human MRI imaging, particularly diffusion/functional MRI, and medical image processing/analysis. He holds a Ph.D. from Vanderbilt University and M.S. and B.A. degrees from Southeast University. Research interests emphasize white matter BOLD signal dynamics, functional connectivity in aging and Alzheimer’s disease, and neuroimaging techniques. Recent work includes studies on white matter tract orientation, vascular geometry, and machine learning approaches for disease classification (e.g., BrainVAE model). Publications highlight advanced methods in spatial smoothing, functional correlation tensors, and connectome analysis. His work addresses Alzheimer’s biomarkers, cognitive decline mechanisms, and the integration of structural/functional brain networks. Affiliated with Vanderbilt’s Biomedical Imaging and Biophotonics group and Surgery/Engineering collaborations. No listed awards or grants, though active in large-scale imaging database preprocessing pipelines (e.g., automatic white matter fMRI analysis).
Eddy U is a Professor of Sociology and Director of East Asian Studies at the University of California, Davis. His research focuses on political sociology, social change, and Chinese socialism, particularly examining classification systems and societal structures in 20th-century China. Key works include Creating the Intellectual: Chinese Communism and the Rise of a Classification (2019) and Disorganizing China: Counter-Bureaucracy and the Decline of Socialism (2007). He holds a Ph.D. from UC Berkeley and has taught courses on global social change and contemporary China. His academic journey began in Hong Kong, leading to a career blending theoretical sociology with empirical analysis of Chinese history. Current research explores the Cultural Revolution’s dynamics. Eddy U’s affiliations include the College of Letters and Science, with offices at 1 Shields Ave. Contact: eu@ucdavis.edu. Despite no listed students or awards, his scholarly contributions span books, edited volumes, and journal articles analyzing Marxist class formations, bureaucratic organization, and knowledge production in modern China. Recent work addresses the reification of social categories and intellectual identity in revolutionary contexts.
Prof Nik Ruskuc is a Professor and Director of Research in the School of Mathematics and Statistics at the University of St Andrews. His roles include leading research initiatives and contributing to the academic administration of the school. He holds a B.Sc. in Mathematics from the University of Novi Sad and a Ph.D. from the University of St Andrews. His research focuses on combinatorial semigroup theory, transformation semigroups, group presentations, and computational algebra. Key interests include generating sets for semigroups, defining relations, subsemigroup properties, and algorithmic approaches in algebraic structures. Ruskuc's work bridges algebra and theoretical computer science, exploring automatic structures, decidability, and combinatorial patterns in permutations and words. His recent publications address coherency properties in monoids, congruences in transformation semigroups, and residual finiteness in graph products. He supervises multiple PhD students and has secured funding from EPSRC for projects on diagram monoids, semigroup representation theory, and computational algebra tools. His research has been presented at international conferences and workshops, showcasing advancements in semigroup theory and its applications. Ruskuc collaborates with institutions globally and is affiliated with the Centre for Interdisciplinary Research in Computational Algebra at St Andrews, emphasizing computational methods in algebraic research.
Prof Ian Gent is a Professor in the School of Computer Science at the University of St Andrews. His research focuses on combinatorial search problems in artificial intelligence, particularly integrating computational group theory with constraint programming for applications like scheduling and timetabling. He holds academic qualifications including an M.A. in Mathematics from the University of Cambridge, an M.Sc. in Knowledge-Based Systems from the University of Edinburgh, and a Ph.D. in Computer Science from the University of Warwick. He supervises PhD student Mustafa Abdelwahed and has contributed to projects such as the development of the CONJURE tool for automated constraint model generation. His work spans constraint satisfaction, puzzle-solving AI, and interdisciplinary research between AI and mathematics. Notable publications include advancements in tabulation techniques (TabID) and explanations for pen-and-paper puzzles using MUSes. He is affiliated with the Centre for Research into Equality, Diversity & Inclusion and the Centre for Interdisciplinary Research in Computational Algebra. Education: M.A. in Mathematics, University of Cambridge M.Sc. in Knowledge-Based Systems, University of Edinburgh Ph.D. in Computer Science, University of Warwick Research Interests: Constraint programming and automated modelling Applications of AI to puzzles and games Interdisciplinary computational methods Key Projects: CONJURE: Automatic generation of constraint models Integration of computational group theory with constraint programming Development of tools for puzzle-solving explanations
Rasmus Steinkrauss is an Assistant Professor at the University of Groningen, affiliated with the Faculty of Arts and the Department of English Linguistics / German Literature and Culture . He serves as Programme coordinator for the MA-track Applied Linguistics, Board member (Treasurer) of the International Association of Applied Linguistics (AILA), and Co-Editor of the Dutch Journal of Applied Linguistics . His research focuses on language development (L1/L2), usage-based and cognitive linguistics methodologies, bilingual/multilingual learning trajectories, and educational assessment strategies. Key projects include studies on international adoption's impact on language development and language instruction in plurilingual settings. Dr. Steinkrauss teaches courses in applied linguistics, language learning, and research methods at both bachelor's and master's levels. His work emphasizes dynamic system theory and its application to language acquisition, including analyses of syntactic/lexical complexity and teaching approaches. He has organized international conferences such as the 19th AILA World Congress and actively collaborates with institutions like the University of Jyväskylä. His address is at Oude Kijk in 't Jatstraat 26, Room 1315.288, Groningen, Netherlands. Research Contributions: Over 37 publications, including works on open access publishing challenges, L2 fluency measures, and translanguaging in heritage language classes. Supervised Students: Co-promoted 8 PhD candidates focusing on topics like multilingualism, language attrition, and instructional methodologies. Projects: Leaded projects on language development in international adoptees, early English learning in plurilingual contexts, and Finnish L2 acquisition dynamics.
Johan Karlsson is a Professor in the Department of Mathematics at KTH Royal Institute of Technology, Sweden. He serves as Associate Director Executive Research at Digital Futures, a cross-disciplinary research center focusing on digital technologies for societal challenges. He holds a PhD in Optimization and Systems Theory from KTH (2008) and an MSc in Engineering Physics (2003). His research focuses on inverse problems, optimization, model reduction, and their applications in remote sensing, signal processing, and control theory. He leads the Decision-making in Critical Societal Infrastructures (DEMOCRITUS) project and collaborates on initiatives like the Lindquist Symposium in Systems Theory. Teaching includes advanced courses such as Optimal Control and Convexity and Optimization in Linear Spaces . He supervises PhD students and has authored/co-authored numerous papers in journals like SIAM Journal on Control and Optimization and IEEE Transactions on Automatic Control . His work integrates optimal transport theory, control systems, and computational methods to address complex engineering and environmental challenges. Key affiliations include KTH’s Department of Mathematics and Digital Futures, with collaborations across academia and industry. His research group actively engages in workshops, conferences, and interdisciplinary projects to advance theoretical and applied aspects of optimization and systems theory.
Okan Bulut is a Professor in the Measurement, Evaluation, and Data Science program at the University of Alberta's Faculty of Education. He is also a researcher at the Centre for Research in Applied Measurement and Evaluation (CRAME). Bulut holds a PhD in Educational Psychology from the University of Minnesota (2013) and has held academic roles since 2014, advancing to his current rank in 2024. His research focuses on AI-driven educational systems, learning analytics, and psychometrics. **Education:** Bachelor of Arts in Elementary Education (Adnan Menderes University, 2006) Master of Arts in Educational Psychology (University of Minnesota, 2010) PhD in Educational Psychology (University of Minnesota, 2013) **Research Interests:** Bulut’s work bridges AI, data mining, and educational assessment. He develops intelligent systems for adaptive learning and uses machine learning to analyze student performance. He regularly publishes in journals like Educational and Psychological Measurement and co-authored the CRC Press Handbook of Educational Measurement and Psychometrics Using R . **Teaching:** Courses include computational psychometrics, machine learning, and statistical modeling. He also designs workshops on data analysis tools (R, SAS, Python). **Labs/Teams:** Active contributor to CRAME, advancing applied measurement research.
Asgeir Johan Sørensen is a Professor of Marine Control Systems at NTNU's Department of Marine Technology, Faculty of Engineering. He also serves as an adjunct professor at UiT the Arctic University of Norway. His roles include Director of NTNU VISTA CAROS and former Director of NTNU AMOS (2013-2023). Sørensen holds an MSc (1988) and PhD (1993) in Marine Technology and Engineering Cybernetics from NTNU. He has extensive industry experience, co-founding companies like Marine Cybernetics AS, Eelume AS, and Zeabuz AS. His research focuses on marine robotics, autonomous systems, and hybrid power systems. He leads labs such as the Marine Cybernetics Laboratory (MC-Lab) and Applied Underwater Robotics Laboratory (AUR-Lab), emphasizing innovation and entrepreneurship. Over 280 publications and 153 students (41 PhDs) reflect his scholarly impact. Current projects include Oppdrag Mjøsa, aiming to map freshwater ecosystems via autonomous systems. Education: MSc (Marine Technology, NTNU, 1988), PhD (Engineering Cybernetics, NTNU, 1993) Research: Autonomous marine operations, underwater robotics, marine cybernetics, and zero-emission propulsion systems Labs: MC-Lab, AUR-Lab, NTNU AMOS His work bridges fundamental research with practical applications, driving advancements in marine autonomy and sustainability.
Mylène Bédard is a Full Professor in the Department of Mathematics and Statistics at Université de Montréal. She holds a Ph.D. from the University of Toronto (2006) and oversees the graduate programs in statistics. Her research focuses on computational statistics, Bayesian methods, and Markov Chain Monte Carlo (MCMC) algorithms, with emphasis on optimal scaling, algorithm efficiency, and robust statistical inference. She has collaborated on topics such as MALA algorithms, hierarchical models, and risk theory in actuarial science. Her teaching spans advanced courses in actuarial science (e.g., risk theory, financial mathematics) and statistical theory (e.g., Bayesian inference, survival analysis). She has supervised over 20 graduate students, many of whom have received prestigious awards including the Prix Serge-Tardif and Prix Constance-van Eeden. Her work integrates theoretical advancements with practical applications in finance, climatology, and healthcare. Key research themes include adaptive MCMC methodologies, Bayesian robustness, and computational techniques for high-dimensional data. Recent projects involve regional adaptive algorithms, non-stationary phase analysis of MALA, and geometric approaches to Bayesian marginalization. Her contributions bridge statistical theory and computational innovation, addressing challenges in sampling efficiency and algorithmic convergence.
John Bargh is the Susan Nolen-Hoeksema Professor of Psychology and Cognitive Science at Yale University, with a secondary appointment in Management. He leads the Automaticity in Cognition, Motivation, and Evaluation (ACME) Lab, focusing on unconscious influences on social judgment, motivation, and behavior. His research explores embodied cognition (e.g., physical experiences affecting social attitudes), automatic goal pursuit, and the neural bases of social behavior. Recent work addresses how physical sensations (e.g., warmth, cleanliness) influence abstract social concepts like trust or prejudice. Education: Ph.D. in Psychology, University of Michigan (1981). His research spans cognitive, social, and clinical psychology, with notable contributions to priming effects and implicit processes. Awards include the 2014 APA Distinguished Scientific Contribution Award. Key themes in his work include the unconscious roots of motivation, the role of physical experiences in shaping social judgments (e.g., 'immunization influencing immigration attitudes'), and the implications of automatic processes for real-world behavior. His lab emphasizes real-life environmental triggers of unconscious mental processes.
Tamar Szabó Gendler is the Dean of the Faculty of Arts and Sciences at Yale University and holds the Vincent J. Scully Professorship in Philosophy. She also has secondary appointments in the Department of Psychology and in the Humanities and Cognitive Science Programs. Her academic leadership includes former roles as Chair of the Philosophy Department and Deputy Provost for Humanities and Initiatives at Yale. Education: BA summa cum laude, Yale University (1987), with Distinction in Humanities and in Mathematics & Philosophy PhD in Philosophy, Harvard University (1996) Gendler's research centers on philosophical methodology, epistemology, imagination, belief, and implicit bias. She is best known for introducing the concept of alief —a mental state distinct from belief that underlies automatic, habitual responses. Her work bridges philosophy with cognitive science, psychology, and education, exploring how imagination and intuition function in reasoning and moral judgment. She has made significant contributions to understanding thought experiments, self-deception, and imaginative resistance. Her recent publications reveal a consistent interdisciplinary focus on the cognitive mechanisms underlying philosophical intuition, moral psychology, and educational self-regulation. Themes include the limits of imagination in fiction, the epistemic harms of implicit bias, and the structure of self-control in children. Scientific Awards and Fellowships: Yale College-Sidonie Miskimin Clauss ’75 Prize for Excellence in Teaching in the Humanities Mellon New Directions Fellowship National Endowment for the Humanities Fellowship National Science Foundation Fellowship American Council of Learned Societies/Ryskamp Fellowship Collegium Budapest Institute for Advanced Studies Fellowship Selected by Philosopher’s Annual (2008) for 'Alief and Belief' Gendler has advised numerous students and contributed to academic service through co-editing Oxford Studies in Epistemology and authoring influential textbooks such as The Elements of Philosophy . She has received grant support from major institutions including the NSF and NEH. While not explicitly mentioning a lab, her work is deeply embedded in cognitive science and interdisciplinary research initiatives at Yale. She is actively engaged in public scholarship, with several courses and lectures available online, including her widely viewed freshman address 'Keeping Inconsistency in Your Pockets.'
France Gheeraert is an Associate Professor in Mathematics at the University of Picardie Jules Verne, France, since September 2024. They are affiliated with the SymPA research team at the Laboratoire Amiénois de Mathématique Fondamentale et Appliquée (LAMFA) and organize the dyna-proba seminar. Previously, they were a Postdoctoral Researcher at Radboud University (Netherlands) and an FNRS Research Fellow at the University of Liege (Belgium), focusing on combinatorics on words and symbolic dynamics. Education Bachelor and Master in Mathematics with Computer Science focus from the University of Liege Research Interests Combinatorics on Words (core work on dendric words, generalizing Sturmian words) String Attractors in data compression Symbolic Dynamics and numeration systems Applications of morphisms in word structures Connections to group theory and algorithmic complexity Recent Publications 2024: String attractor-based complexities for infinite words 2024: String attractors in bi-infinite sequences 2023-2022: Studies on dendric words, S-adic systems, and morphic fixed points Scientific Awards FNRS Research Fellow (Belgium, 2020-2024) Labs & Teams SymPA team, LAMFA (University of Picardie) Discrete Mathematics team, University of Liege (2020-2024)
Jakub Konieczny is a Senior Research Associate at the University of Oxford's Department of Computer Science, with an upcoming transition to faculty at KSE. His institutional affiliation places him within Oxford's computational mathematics research community. His research centers on combinatorial number theory with particular emphasis on ergodic theory applications . His doctoral work investigated additive properties of nil-Bohr sets of integers that naturally emerge in higher order Fourier analysis. More recently, he has expanded his research scope to include sequences derived from digital expansions, specifically automatic sequences $$q$$-multiplicative sequences His work represents an intersection of theoretical computer science and advanced number theory, focusing on structural properties of integer sequences and their analytical representations. Currently preparing to join KSE's faculty, Konieczny's research trajectory shows increasing diversification within combinatorial structures while maintaining strong connections to harmonic analysis frameworks. His methodological approach integrates dynamical systems perspectives with classical number theory problems.
Professor Manabu Okumura is affiliated with the Advanced Information Processing Division at Tokyo Institute of Technology, leading the Precision and Intelligence Laboratory. His research focuses on natural language processing (NLP), automated text summarization, and speech dialogue systems, emphasizing real-time, user-friendly interaction. Key areas include incremental language understanding, robustness in ill-formed input analysis, and semi-automatic lexical acquisition. His work addresses challenges like syntactic-semantic integration using case frame analysis, ellipse resolution in Japanese, and associative lexical relations extraction from corpora. Research projects include communication assistive technologies for disabled individuals and natural language-driven animation control. Publications span foundational NLP topics such as word sense disambiguation via semantic networks, zero pronoun resolution using centering theory, and incremental discourse processing. The lab collaborates on bilingual corpus analysis for lexicon development and maintains a focus on practical applications of theoretical advances.
Taesoo Kim is a Professor at Georgia Tech's College of Computing, jointly affiliated with the School of Cybersecurity and Privacy and the School of Computer Science. He serves as Director of the GTS3 lab and leads research in systems security, operating systems, programming languages, and distributed systems. His work emphasizes foundational security principles and practical tools for system resilience. Education: PhD in EECS from MIT (2014), SM from MIT (2011), BS in Computer Science/Electrical Engineering from KAIST (2009) Affiliations: Georgia Tech's School of Computer Science, School of Cybersecurity and Privacy, ML@GT, and Online Master of Science in Computer Science program Kim's research focuses on building secure computing systems through formal system design, implementation analysis, and trusted component isolation. Notable contributions include tools for automatic vulnerability detection, intrusion recovery frameworks, and secure enclave technologies like SGX-Tor. His work has secured grants from ONR, NSF, DARPA, and industry partners. Awards include the 2015 Internet Defense Prize and a finalist placement in the DARPA Cyber Grand Challenge. Key projects include QSYM (concolic execution engine), RAIN (attack tracing), and FREEDOM (DOM fuzzer). Kim teaches courses on information security and blockchain technologies. His lab (SSLab) collaborates with industry on critical security challenges, including hardware-software co-design for trusted execution environments.
