جست‌وجوی استاد و پژوهشگر

Lars-Henrik Erikssonمشاهده پروفایل

مدرس ارشد

• Formal Methods
• Logic in Computer Science
• Programming Language Theory
• +۷ مورد دیگر

Lars-Henrik Eriksson is a Senior Lecturer in the Department of Computer Science at Uppsala University, part of the Department of Information Technology. He holds a PhD and is recognized as an Excellent Teacher and educational mentor. He currently serves as the program director for the Master's program in Computer Science and has previously held leadership roles, including Head of the Department of Computer Science from 2004 to 2018. PhD in Computer Science Excellent Teacher Award Pedagogical Mentor at Uppsala University His research focuses on the applications of logic in computer science, particularly formal methods for software development. His work spans formal specification, verification, and synthesis, with strong emphasis on logic programming, interactive theorem proving, and logical frameworks. He has made significant contributions to the use of formal methods in safety-critical domains such as railway signaling. His current research includes modeling application domains within formal methods and formalizing concurrency theory using the Isabelle proof assistant. The recent publications reflect a sustained focus on modal logics for nominal transition systems, formal verification tools (e.g., GTO), and domain-specific applications of formal methods. These works demonstrate deep integration of theoretical logic and practical software engineering, especially in distributed and safety-critical systems. The recurring themes include concurrency, verification, and the use of domain models to enhance formal reasoning. Scientific Awards and Recognitions: Excellent Teacher Pedagogical Mentor Lars-Henrik Eriksson has advised numerous students through project supervision, thesis reviews, and course mentorship, though no formal list of advisees is provided. He has been involved in significant research management, including leading the department and directing a master’s program. He has also collaborated with industry, particularly in railway signaling, contributing to safety analysis and formal verification projects with Trafikverket and through companies he co-founded. He is a board member of Formal Methods Europe and served as program committee chair for the FME Symposium 2002 (part of FLoC’02). His work bridges academia and industry, especially in the application of formal methods to real-world engineering challenges.

Andreas Abelمشاهده پروفایل

مدرس ارشد

• Programming Languages
• Logic
• Type Theory
• +۷ مورد دیگر

Andreas Abel is a Senior Lecturer at the Department of Computer Science, Gothenburg University, with a focus on Programming Languages, Logic, and Type Theory. His work includes contributions to dependently typed programming, functional programming, lambda calculus, and formal verification. Research Interests Programming Languages Logic Types Projects Principal Investigator for Modal Dependent Type Theory (Vetenskapsrådet grant 2020-2024) Editor of the Theoretical Pearls column in the Journal of Functional Programming Senior developer of the dependently-typed language Agda His recent publications span graded type theory, normalization by evaluation, strong normalization, and formal verification using Agda. Key collaborations include Jean-Philippe Bernardy and Thierry Coquand. Scientific Awards Vetenskapsrådet grant 2020-2024 VR Grant 2014-04864 He has supervised numerous projects, developed software tools like the Backus Naur Form Compiler (BNFC), and contributed to international conferences as a PC member and author.

• Teacher Development
• Educator Continuum
• Teacher Induction
• +۳ مورد دیگر

Dr. Bryan Zugelder serves as the Associate Dean for Academic Excellence, Research, Innovation & Policy and Associate Professor in the Department of Learning, Technology, and Leadership Education at James Madison University. He holds a Doctor of Education in Organizational Leadership, Master of Science in Educational Leadership, and Bachelor of Science in Elementary Education. With over $44M in funded grants and 80+ scholarly contributions, his work focuses on teacher development, educator continuum systems, and university-based teacher induction. He leads initiatives such as a $4.8M annual project on systemic teacher induction and a widely adopted instructional coaching framework across 10 UNC System universities and 200+ schools. Education: Bachelor of Science, Elementary Education Master of Science, Educational Leadership Doctor of Education, Organizational Leadership Research Interests: Teacher Induction and Retention Pre-service and In-service Teacher Development Instructional Coaching Educator Leadership Rural Education Challenges Grants & Leadership: Principal Investigator for a $4.8M teacher induction project at East Carolina University Executive Director of Undergraduate Affairs and Partnerships at UCF Director of Clinical Experiences and Toni Jennings Institute His research emphasizes the impact of university-school partnerships on teacher effectiveness and student achievement. Key projects include a logic model with Stanford and NC State University studying teacher retention and a framework for trust-building in leadership roles. He has also contributed to state-level initiatives in Florida and North Carolina, focusing on rural teacher recruitment and literacy coaching.

Dzeroski Sasoمشاهده پروفایل

استاد

• Computer Science
• Artificial Intelligence
• Machine Learning
• +۸ مورد دیگر

Saso Dzeroski is a Professor and Department Head at the Department of Knowledge Technologies, Jožef Stefan Institute, Slovenia. He holds concurrent roles as a guest professor at the Faculty of Computer and Information Science, University of Ljubljana, and a full professor at the Jožef Stefan International Postgraduate School. His primary affiliation is with Jožef Stefan Institute, where he has served as Scientific Councillor since 2006 and Department Head since 2020. Former roles include Professor at the School of Environmental Sciences, University of Nova Gorica (1999-2014). Education: PhD (1995 - youngest in Computer Science in Slovenia), MSc (1991), and BSc (1989) in Computer Science from the University of Ljubljana. Research focuses on machine learning, data mining, and their applications in environmental and life sciences. Key areas include constraint-based mining, ensemble learning, inductive logic programming, and predictive modeling. He has coordinated major EU projects such as MAESTRA (FET Open, ranked 1st/318 proposals), HBP’s SARSCARUB subproject (ranked 1st/87), and LANDMARK (H2020). Awards: ECCAI Fellow (2008), Jožef Stefan Golden Emblem Prize (1996), ERCIM Fellowship (1995-1996). Leadership: General/Program Chair for ECML/PKDD 2017, ICML 2005/1999, and other major conferences. Editorial board member of journals like Machine Learning, Journal of Machine Learning Research, and Ecological Modelling.

• Automata Theory
• Formal Methods
• Tree Automata
• +۴ مورد دیگر

Christof Löding is an Adjunct Professor at the Department of Logic and Theory of Discrete Systems (Computer Science 7) at RWTH Aachen University. His research focuses on automata theory, formal verification, and logical foundations of computer science, with significant contributions to Büchi automata, tree automata, and stochastic games. Academic affiliation: RWTH Aachen University, Germany Research areas: Automata theory, Formal methods, Game theory, Logic in computer science Contact: loeding@informatik.rwth-aachen.de His recent work spans deterministic parity automata construction, finite-valued transducers, and algorithmic solutions for infinite games. Publications emphasize theoretical foundations and practical applications in program verification and XML processing. Articles analyze automata learning, uniformization problems, and lookahead degrees in infinite games, showing interconnections between automata theory and formal verification.

Nathanaël Fijalkowمشاهده پروفایل

پژوهشگر

• Games
• Machine Learning
• Automata Theory
• +۹ مورد دیگر

Nathanaël Fijalkow is a Researcher at CNRS in LaBRI (Bordeaux) and a Research Fellow at The Alan Turing Institute in London. His primary research fields include games , machine learning , automata theory , and dynamical systems , with a focus on synthesizing programs from logical specifications and probabilistic models. Research Interests span program synthesis (programming by example), controller synthesis (temporal logic specifications), games on graphs (parity/mean payoff games), probabilistic automata (bounded ambiguity), and invariants for linear dynamical systems. He bridges formal methods with machine learning through projects like DeepSynth . Scientific Contributions include: Undecidability results for probabilistic automata Advances in parity game algorithms (quasi-polynomial lower bounds) Foundations of probabilistic modal logics Efficient synthesis techniques using SMT solvers and distributional learning Supervision involves guiding postdocs and PhD students such as Guillaume Lagarde, Antonio Casares, and Pierre Ohlmann. He has secured grants like the Momentum DeepSynth project (2019-2021) , aiming to merge formal methods with ML for program synthesis.

• Automata Theory
• Formal Verification
• Logic in Computer Science
• +۳ مورد دیگر

Christof Löding , currently an Adjunct Professor at the Lehrstuhl für Logik und Theorie diskreter Systeme (Informatik 7) department of RWTH Aachen University , is a leading researcher in Automata Theory , Formal Verification , and Logic in Computer Science . His work bridges theoretical foundations with practical applications in software verification, automata minimization, and game theory. Research Interests include automata theory, formal verification, logic, tree automata, game theory, and computational models. Publications span topics like Finite-valued Streaming String Transducers , Deterministic Parity Automata , and Stochastic Game Strategies . Collaborations with researchers like Emmanuel Filiot , Sarah Winter , and León Bohn highlight his contributions to automata and verification. Email : loeding@informatik.rwth-aachen.de He has actively published in venues such as ICALP , LICS , and STACS , focusing on deterministic automata, transducers, and logic-based computational systems. His work on Hyperlogic for Strategies in Stochastic Games (2025) and Minimal History-Deterministic Automata (2025) showcases his ongoing influence in formal methods and automata theory.

Christian Meilickeمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Knowledge Graphs
• Ontology Matching
• +۵ مورد دیگر

Christian Meilicke is a Researcher at the Data and Web Science Group (DWS) within the School of Business Informatics and Mathematics at the University of Mannheim. His work focuses on artificial intelligence, ontology matching, and knowledge graph completion, with recent contributions to rule-based methods and their applications in business process modeling. He is heavily involved in teaching, coordinating courses such as 'Modeling Business Processes' and 'Artificial Intelligence.' His research interests include the integration of open and structured knowledge, probabilistic reasoning frameworks, and improving the efficiency of knowledge base systems. He has explored topics like inductive logic programming, automated debugging of ontologies, and the use of Markov Logic Networks for root cause analysis in IT systems. In terms of trends, his recent publications emphasize combining symbolic rule-based approaches with machine learning for knowledge graph tasks, such as activity recommendation and link prediction. He also investigates explainability in embeddings and temporal forecasting in knowledge graphs. His work often bridges theoretical advancements with practical applications in business informatics and data integration. No scientific awards have been explicitly mentioned. Christian has advised no formal students listed here but has contributed to teaching and mentoring through his courses and tutorials. His research and teaching are closely tied to the DWS Group, which focuses on data-centric AI and semantic technologies.

Selmer Bringsjordمشاهده پروفایل

استاد

• Artificial Intelligence
• Cognitive Science
• Computational Logic
• +۹ مورد دیگر

Selmer Bringsjord is a Professor of Cognitive Science, Computer Science, Logic & Philosophy, and Management & Technology at Rensselaer Polytechnic Institute (RPI). He serves as Director of the Rensselaer AI & Reasoning (RAIR) Lab and Graduate Program Director in Cognitive Science. His research spans AI, cognitive science, formal logic, and ethics, with a focus on machine ethics, computational creativity, and conscious AI. Bringsjord has authored 6 books, over 260 refereed papers, and secured $28M+ in sponsored research. He has supervised 20 PhD and 19 MS students. Notable contributions include founding machine ethics, developing Psychometric AI, and the Λ measure for cognitive consciousness. His work bridges philosophy, computer science, and robotics, with media appearances across global platforms. Education: PhD in Philosophy from Brown University (1987), BA in Philosophy from the University of Pennsylvania (1981). Administrative roles include Department Chair of Cognitive Science (2002–2016) and Director of RAIR Lab since 2002. Awards include patents, grants, and a Best Paper Award at AGI 2024. Teaching spans 40 years in formal logic and AI. Ongoing projects include ethical AI frameworks, AGI, and cognitive consciousness models.

Marta Ariasمشاهده پروفایل

دانشیار

• Machine Learning
• Data Mining
• Design and Analysis of Algorithms
• +۳ مورد دیگر

Marta Arias is an Associate Professor in the Computer Science Department at Universitat Politècnica de Catalunya (UPC), Barcelona, and a member of the LARCA research group. She has held academic positions since 2007, including roles at Columbia University and the University of Edinburgh. Her research focuses on Machine Learning, Data Mining, Algorithm Design, and Logic in Computer Science. She teaches advanced courses in Machine Learning, Information Retrieval, and Complex Networks at undergraduate and master's levels, including the Erasmus Mundus program in Data Mining and Knowledge Management. Educations: PhD in Computer Science from Tufts University (2000-2004), Postgraduate Studies at University of Edinburgh (1999-2000), B.Sc. in Computer Science from UPC (1992-1997). Professional experience includes software engineering and research roles in New York and Barcelona. Research highlights include developing algorithms for real-time ranking systems, Twitter-based financial forecasting, and causal network analysis. Notable contributions include the 'Best Paper Award' at AIPESW@ECAI 2020 and a 3rd place award in football performance research. Her work spans theoretical foundations (e.g., Horn clause learning) and applied domains like cybersecurity, healthcare analytics, and energy systems. Teaching responsibilities include labs and lectures on Machine Learning, Information Retrieval, and Programming, with active involvement in curriculum design and pedagogical innovation. Ongoing projects include enterprise risk analysis, synthetic data generation, and network modeling.

Kino Zhaoمشاهده پروفایل

استادیار

• Philosophy of Science
• Philosophy of Social Science
• Philosophy of Statistics
• +۶ مورد دیگر

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. Janikowمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Evolutionary Computation
• Genetic Algorithms
• +۹ مورد دیگر

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.

• Statistics
• Spatial Statistics
• Spatio-Temporal Modeling
• +۷ مورد دیگر

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.

• Theory and Semantics of Computation
• Nominal Sets
• Dependent Type Theory
• +۴ مورد دیگر

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 Kincaidمشاهده پروفایل

دانشیار

• Program Analysis
• Logic
• Programming Languages
• +۷ مورد دیگر

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.