Kino Zhao is an Assistant Professor in the Department of Philosophy at Simon Fraser University. His research focuses on the philosophy and methodology of the social sciences, emphasizing the interplay between philosophical analysis and scientific practice. He holds a PhD from the University of California, Irvine, an MA from Simon Fraser University, and a BA from the University of British Columbia. Education: PhD in Philosophy (Logic and Philosophy of Science), UC Irvine, 2021 MA in Philosophy, Simon Fraser University, 2015 BA in Psychology and Philosophy, University of British Columbia, 2013 Research interests include methodological challenges in social sciences, statistical assumptions, measurement validity, and the philosophical implications of machine learning and game theory. His work often bridges technical philosophy with empirical scientific practices. Notable contributions include critiques of traditional sampling methods in social sciences and advocacy for validity-first frameworks in measurement. Beyond academia, he co-founded Wonder Philosophy to support underrepresented students in philosophy graduate programs.
Cezary Z. Janikow is an Associate Professor and former Chair of the Department of Mathematics and Computer Science at the University of Missouri–St. Louis (UMSL), where he conducts research in artificial intelligence, evolutionary computation, and machine learning. He is the developer of FID (Fuzzy Inference Decision tree), a system for generating fuzzy decision trees that handle missing, noisy, and continuous data. His research is supported by NIH, NSF, and NASA/JSC, and he has contributed significantly to the field of genetic programming, particularly in constrained and adaptable representations (ACGP). Ph.D. in Computer Science, University of North Carolina at Chapel Hill, 1991 His research interests center on evolutionary algorithms , fuzzy decision trees , and symbolic machine learning . He explores how genetic programming can adapt representations and incorporate constraints to improve search efficiency and solution quality. His work on FID has advanced fuzzy logic applications in classification and data analysis. The recent publications reflect a sustained focus on genetic programming , particularly Adaptable Constrained Genetic Programming (ACGP) , heuristics in evolutionary search , and fuzzy decision systems . His work spans theoretical development, algorithm design, and practical implementation, with applications in optimization and machine learning. Dr. Janikow has delivered corporate training in software development and served as an expert witness in software-related legal cases. He has also organized academic workshops and presented tutorials on evolutionary algorithms. Co-PI, NIH: Statistical Methods for Recursively Partitioned Trees NSF Support: Fuzzy Decision Trees NASA/JSC Collaboration: Constrained Genetic Programming He leads the FID project, a software system for fuzzy decision tree generation, which includes a GUI and supports cross-validation and noise simulation. This tool reflects his integration of research and software development.
Donato Posa is a Full Professor in Statistics at the Department of Economic Sciences, University of Salento. He holds the academic position of Professor Ordinario (Full Professor) in the field of Statistics (SECS-S/01) and is actively engaged in research and academic leadership. His work bridges economics, environmental science, and advanced statistical modeling. University: University of Salento Department: Department of Economic Sciences Academic Rank: Professor Email: donato.posa@unisalento.it Office: Centro Ecotekne Pal. C, S.P. 6, Lecce - Monteroni, LECCE (LE) Phone: +39 0832 29 8737 Donato Posa earned his degree in Physics, cum laude, from the University of Bari with a thesis conducted at CERN, Geneva, and completed a specialization in Physics. His international academic experience includes extended research stays at Stanford University (USA), the University of Arizona, and the University of North Carolina. His research focuses on spatial and spatio-temporal statistics, with major contributions in geostatistics, multivariate geostatistics, stochastic simulation, and time series analysis. He has developed theoretical and applied models for environmental monitoring, pollution assessment, and socioeconomic data analysis. His work has been applied in risk mapping, environmental policy, and urban planning. The 15 most recent articles reflect a consistent trend in spatio-temporal modeling and geostatistical innovation. They span theoretical developments in covariance modeling and variogram analysis to practical applications in environmental monitoring, pollution dispersion, and ecosystem well-being. The research demonstrates a strong interdisciplinary focus, integrating statistical theory with environmental, economic, and computational sciences. His scientific recognition includes multiple CNR and NATO research grants, CERN awards, and an International Diploma of Honour from the American Biographical Institute for contributions to geostatistics. He has served on editorial boards, chaired international conferences (e.g., GeoEnv 2012), and participated in national scientific qualification committees. Posa has supervised numerous research projects funded by CNR, MIUR, Fondazione Caripuglia, and EU programs. He has acted as a scientific referee for leading journals such as Stochastic Environmental Research and Risk Assessment and Computational Statistics and Data Analysis . He has also led educational initiatives in statistical methods and GIS for environmental and cultural heritage applications. He has been actively involved in academic governance, serving as President of the Research Observatory at the University of Salento (2013–2017) and as a member of national evaluation committees. He has chaired international conferences and contributed to major scientific associations including the Bernoulli Society, the International Association for Statistical Computing, and the American Statistical Association.
Andrew Pitts is a Professor at the University of Cambridge Computer Laboratory, specializing in the theory and semantics of computation, with a focus on nominal sets and dependent type theory. He is a Fellow of the Royal Society (FRS) and has made significant contributions to the mathematical foundations of programming languages. Research Interests: His work bridges theoretical computer science and mathematical logic, emphasizing nominal techniques, category theory, and homotopy type theory. He explores abstract syntax, inductive types, and the formal verification of computational models. Key Trends in Recent Publications: Recent articles emphasize category theory, type theory, and formal methods, with specific attention to quotient types, modal type theory, and cubical type theory. These works often involve collaborations with researchers in programming language foundations and mathematical logic. Scientific Awards: Fellow of the Royal Society (FRS)
Zachary Kincaid is an Associate Professor in the Department of Computer Science at Princeton University. His research focuses on program analysis , logic , and programming languages , with emphasis on making analysis compositional and robust . PhD, University of Toronto (2016) BSc, Western University Research Interests Dr. Kincaid develops algebraic program analysis frameworks combining symbolic methods with abstract interpretation. His work addresses challenges in: Compositional analysis of concurrent and recursive programs Termination analysis for loops with complex control flow Non-linear numerical invariant generation Strategy synthesis for logical games Parameterized program verification Publication Trends His research output spans program analysis (2024-2010), formal verification (2018-2010), concurrency (2016-2010), and automated synthesis (2013-2012). Recent work (2024) explores polynomial ideals and nonlinear ranking functions , while foundational contributions include vector addition systems and recurrence-based invariants . Scientific Engagement Dr. Kincaid contributes to the academic community through: Program Committee service (PLDI, POPL, CAV, IJCAI, LICS, FMCAD, ESOP, etc.) Co-developing the Duet analyzer for unbounded concurrency Collaborative work with leading researchers (Tom Reps, Azadeh Farzan, Jason Breck) Advising & Grants He advises PhD students and leads research funded by the ONR grant N00014-19-1-2318 . Current advisees include Jake Silverman and Shaowei Zhu, while former student Charlie Murphy (PhD 2023) now holds a postdoctoral position at University of Wisconsin-Madison. Labs & Teams Dr. Kincaid co-developed the Duet program analyzer and contributes to tools like Srk and SimSat . His work integrates SMT solvers (MathSAT, Z3) and mathematical frameworks (rational vector addition systems, recurrence relations) for robust program analysis.
Andreas Abel is a Senior Lecturer in the Department of Computer Science and Engineering at Gothenburg University, with additional affiliation at Chalmers University of Technology. He is a senior developer of the Agda programming language and maintains the Backus Naur Form Compiler (BNFC). His educational background includes a Computer Science diploma (1999), PhD (2006), and Habilitation (2013), all from Ludwig-Maximilians-University (LMU) Munich. His career spans positions at LMU, INRIA Paris, and Chalmers before his current role at Gothenburg University since 2013. Abel's research focuses on dependently typed programming , type theory , and verified software development . His work bridges theoretical foundations with practical implementations, particularly in the Agda proof assistant. His interests span from foundational aspects of lambda calculus and normalization to practical applications in programming language design. His publications demonstrate a consistent focus on type theory foundations and practical implementations, with recent work exploring applicative functors, cubical type theory, modalities in type systems, and formalizations of algebraic structures. His research often combines deep theoretical insights with concrete implementations in proof assistants. Distinguished Paper Award at ICFP 2019 (4 out of 39 accepted papers) Editor of Theoretical Pearls column, Journal of Functional Programming Member of IFIP WG 1.3 on Foundations of System Specification Abel actively supervises students through the Initial Types Club and Master's thesis projects, focusing on advanced topics in programming languages and type theory. He teaches Programming Language Technology and Advanced Functional Programming, emphasizing both theoretical foundations and practical implementation. His current research is supported by a Vetenskapsrådet grant for the project 'Modal Dependent Type Theory' (2020-2024), continuing his long-standing contributions to programming language theory and formal verification.
Axel Mueller is a Teaching Professor in the Department of Philosophy at Northwestern University's Weinberg College of Arts and Sciences. He holds a Ph.D. from the University of Frankfurt and specializes in philosophy of language, philosophy of natural science, American pragmatism, and Kantian philosophy. Ph.D., University of Frankfurt His research explores semantic externalism, democratic legitimacy, and the intersection of pragmatism and realism, with a focus on disarming skepticism via pragmatic contextualism. Recent publications address populism, supranational governance, and Kantian mental content externalism. Key trends in his work include: Pragmatism and analytic philosophy Philosophy of science and mind Political theory and democratic institutions Historical analysis of pragmatic/naturalistic traditions He has occupied visiting positions at institutions in Madrid, Mexico, Santiago de Chile, and Flensburg, and is currently engaged in expanding his analysis of Kant's semantic externalism and political philosophy.
Klaus Kaiser is a Professor of Mathematics at the University of Houston, where he has been affiliated since 1969. He holds a PhD from the University of Bonn (1966) and a Habilitation from Darmstadt (1973). His research focuses on Mathematical Logic, Universal Algebra, Lattice Theory, and Logic Programming, with notable collaborations on quasi-universal model classes and non-standard lattice theory dedicated to Abraham Robinson. Editorial Roles: Associate Editor of Zeitschrift für Mathematische Logik und Grundlagen der Mathematik (1980–1992), Managing Editor of the Houston Journal of Mathematics (since 1996) Conference Contributions: Presented at ICM Beijing 2002, co-organized sessions at AMS-SMM Houston 2004 and JMM San Diego 2013 His work explores the intersection of mathematical research and publishing challenges, addressing technical, business, and legal aspects of electronic journal access. He has contributed to conferences on electronic publishing in mathematics, including publications in Springer LNCS and FIZ Karlsruhe proceedings. Kaiser has advised PhD students like Mai Gehrke (University of Nice) and Matt Insall (UMR), and his research legacy includes foundational work in model theory such as the Kaiser hull, which connects algebraic closedness to inductive hulls. Contact: Email klaus@math.uh.edu or write to Department of Mathematics, University of Houston, Houston, TX 77204-3476.
Dr. Marina De Vos is a Senior Lecturer in the Department of Computer Science at the University of Bath. She leads research in knowledge representation and normative systems, with affiliations to multiple research centers including the Centre for Mathematical Biology and UKRI CDT in Accountable AI. Education: Postgraduate Certificate in Learning and Teaching in Higher Education, University of Bath (2010) Doctor of Science in Computer Science, Vrije Universiteit Brussel (2002) Master of Computing, Vrije Universiteit Brussel (1998) Research focuses on declarative programming paradigms, particularly Answer Set Programming (ASP) and normative multi-agent systems. Her work enables intuitive problem description in knowledge representation languages, with applications spanning structural engineering, music composition, legal reasoning, and policy modeling. Additional research interests include inductive machine learning, explainable AI, hybrid AI systems, and game theory. Recent publications demonstrate strong focus on norm synthesis in multi-agent systems, contextual reasoning, and governance frameworks for autonomous systems. This reflects a consistent pattern of applying formal computational methods to social and ethical dimensions of AI. Professional activities include keynote presentations at international conferences, workshop chair roles for major AI events, and external PhD examination responsibilities across European institutions.
Dr. Yvonne Yu-Hsuan Chen is a Professor at the University of California, Los Angeles (UCLA) School of Medicine, Department of Microbiology, Immunology, and Molecular Genetics. She earned her B.S. in Chemical Engineering from Stanford and a Ph.D. from Caltech, followed by postdoctoral training at Harvard Medical School and Seattle Children’s Research Institute. At UCLA since 2013, she co-directs the Tumor Immunology and Immunotherapy Program at the Jonsson Comprehensive Cancer Center and is a Parker Institute member. Education: Stanford (BS), Caltech (PhD), Harvard Medical School (Postdoc) Key research areas: Synthetic Biology, CAR-T cell engineering, tumor immunology, gene therapy Dr. Chen pioneers next-generation CAR-T therapies, focusing on overcoming tumor microenvironment challenges like hypoxia, antigen escape, and immune suppression. Her work integrates synthetic biology to reprogram T cells for enhanced specificity and metabolic compatibility with tumors. Recent studies highlight bispecific CARs, transgene silencing solutions, and metabolic reprogramming without antigen stimulation. Her publications span top journals like Nature Metabolism , Cell , and Cancer Discovery , emphasizing clinical translation. Collaborations include institutions like UCSF, Caltech, and Yale. Her lab trains future scientists, with alumni now at companies like Kite Pharma and institutions like Yale. Scientific awards: NIH Early Independence, ACGT Young Investigator, NSF CAREER Dr. Chen’s team includes PhD students and postdocs working on CAR-T trafficking, cytokine regulation, and tumor targeting. She leads clinical trials and translational research, aiming to improve CAR-T safety and efficacy for both hematologic and solid tumors.
Maria Christakis is a Full Professor at TU Wien's Faculty of Informatics where she leads the Rigorous Software Engineering Group. Her research develops methods and tools for building reliable software through formal methods, automated test generation, and program verification. She directs several projects including Sherlock (a framework for testing program analyzers), Minotaur (constraint-based program generator), and SmartACE (compositional verifier for smart contracts). Her group focuses on improving software robustness while enhancing developer productivity. Awards include the Distinguished Paper Award at ICSE 2016 and Best Presentation Award at ESEC/FSE 2020. She currently advises 5 PhD students and teaches courses in Advanced Software Engineering and Software Engineering Research.
Stefania Monica is an Associate Professor at the Department of Engineering Sciences and Methods, University of Modena and Reggio Emilia. She specializes in Artificial Intelligence, Multi-Agent Systems, Robotics, and Programming Languages. Her research focuses on topics such as agent interaction protocols, indoor positioning algorithms, and agent-oriented programming (Jadescript). She teaches courses on Artificial Intelligence, Data Science, Web Technologies, and IoT. Recent work includes studies on stigmergic interactions in multi-agent systems and 3D indoor positioning using optimization algorithms. Her contributions span theoretical frameworks (e.g., kinetic models) and practical implementations (e.g., Jadescript language enhancements for robustness and interoperability). Research interests emphasize synergy between AI and robotics, with applications in localization, swarm intelligence, and neural-symbolic learning. Teaching responsibilities include managing engineering courses on data science, information systems, and IoT development. She actively contributes to academic conferences and journals, curating special issues on computational logic and agent-based systems.
Cynthia Kop is an Associate Professor in the Software Science group at Radboud University Nijmegen. Her research focuses on term rewriting systems and their applications in computational complexity, software verification, and program analysis. She leads the CHORPE and ICHOR research projects and coordinates multiple academic courses including Automated Reasoning and GiPHouse programs. Education: PhD in Computer Science from Vrije Universiteit Amsterdam (2012) Master's degree from Radboud University Nijmegen (2007) Research Interests: Cynthia's work bridges theoretical foundations with practical applications, particularly in higher-order term rewriting systems, constrained rewriting, program equivalence verification, and complexity analysis. She develops analysis tools like WANDA and Cora to automate verification processes. Publication Trends: Her recent articles demonstrate a strong focus on higher-order systems complexity analysis, termination proofs, program equivalence methods, and practical tool implementations for rewriting systems. Work frequently combines theoretical computer science with applied verification techniques. Grants and Projects: Principal Investigator for NWO VIDI project CHORPE (2021-2026) Principal Investigator for NWO TOP project ICHOR (2019-2023) Marie Curie Fellowship for HORIP project (2015-2017) Research Group: Leads a team including PhD students Liye Guo, Kasper Hagens, and Deivid Vale. The group develops formal methods for program analysis through constrained higher-order rewriting systems.
Matti Järvisalo is a Professor in the Department of Computer Science at the University of Helsinki, Finland, holding the title of Docent and serving as Supervisor for the Doctoral Programme in Computer Science. He is affiliated with the Helsinki Institute for Information Technology (HIIT), a leading collaborative research institute between the University of Helsinki and Aalto University. His research centers on computational logic and constraint-based reasoning, with core expertise in Boolean optimization, SAT/MaxSAT solving, and argumentation frameworks. He develops declarative approaches for combinatorial problems in computational social choice, judgment aggregation, and fair division, emphasizing certified algorithms and preprocessing techniques. His work bridges theoretical computer science with practical implementations in optimization and AI. Recent publications (2024-2025) reveal a strong focus on multi-objective optimization, certified reasoning, and argumentation under incomplete information. Key trends include symmetry-aware core learning for Pseudo-Boolean optimization, Pareto-optimality certification in MaxSAT, and novel algorithms for manipulation analysis in judgment aggregation, demonstrating his leadership in advancing SAT-based AI methods. Professor Järvisalo's significant contributions have been recognized by prestigious awards: IJCAI-JAIR Best Paper Prize (2019) Best Researcher Award from University of Helsinki Department of Computer Science (2011) CP 2017 Distinguished Paper Award ECAI 2016 Runner-Up Best Student Paper Award Honorary Mention at ICCMA 2015 He actively mentors the next generation of researchers and secures major research funding: Supervision: 6 doctoral theses and 6 Master's/Licentiate theses Active Grant: Academy of Finland project 'Next-generation Unsatisfiability-based Declarative Optimization' (2023-2027) Past Projects: 'Symbolic Techniques for Formally Verified and Explainable AI' (2020-2022), 'Declarative Boolean Optimization: Pushing the Envelope' (2019-2023) As a core member of HIIT, he collaborates within Finland's premier information technology research ecosystem, contributing to the institute's mission of advancing fundamental and applied IT research through interdisciplinary teamwork and international partnerships.
Ivan Chorbev, Ph.D. is an Assistant Professor at the Institute for Computer Science and Engineering , Faculty of Electrical Engineering and Information Technologies (FEIT), Ss. Cyril and Methodius University in Skopje, North Macedonia. Since 2009 he has taught courses ranging from Structured Programming to Computer Animation and consulted on numerous EU and national ICT projects. Education B.Sc., Faculty of Electrical Engineering, Skopje, 2004 M.Sc., Faculty of Electrical Engineering, Skopje, 2006 Ph.D., Faculty of Electrical Engineering and Information Technologies, Skopje, 2009 Research Interests His work integrates combinatorial optimization and machine learning to solve complex real-world problems. Core themes include designing heuristic algorithms and constraint programming models for scheduling, resource allocation and telemedicine systems, developing medical expert systems that leverage knowledge extraction and predictive modeling, and creating web-based platforms for e-health, smart living and educational services. Publication Trends Over 70 peer-reviewed works (2005-2014) reveal a clear trajectory from foundational optimization and constraint-solving research toward interdisciplinary applications in telemedicine , social media analytics , and assistive technologies . A notable 2011-2014 surge focuses on cloud-supported e-health systems, 3-D printing for assistive devices, and mining social media for epidemiological insights. Scientific Awards Golden engineering ring – awarded by the Organization of Engineers of Macedonia for best student of his generation. Projects & Funding Risk Assessment for Customs in Western Balkans – FP6 COST IC0602 Algorithmic Decision Theory – management committee member (FP6) COST IC1002 MUMIA – management committee member (FP7) E-HFISN – e-Health applications using folksonomy & social networks (FP7) TEMPUS – Innovation and Knowledge Management toward eStudent Information System Laboratory & Team He conducts research within the Institute for Computer Science and Engineering laboratories, supervising graduate projects in optimization, medical informatics and smart environments.
