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Michael Reichhardt HansenView profile

Associate Professor

• Formal Methods
• Embedded Systems
• Real-Time Systems
• +3 more

Michael Reichhardt Hansen is an Associate Professor at the Department of Applied Mathematics and Computer Science (DTU Compute) at the Technical University of Denmark. He holds a MSc in Engineering (1982) and a PhD in Computer Science (1987) from DTU. He has held postdoctoral and visiting roles, including a fellowship at IBM Research Center (1984–1985) and a guest professorship at Oldenburg University (1992–1993). His research focuses on formal methods, embedded systems, and real-time systems, emphasizing mathematically grounded software development. He has authored/co-authored three books and over 70 scientific articles. Research interests include model-based program construction, temporal logic, functional programming, and ontology alignment. He has led projects on ontology matching frameworks (e.g., MDMapper) and formal methods for real-time systems. Hansen has supervised PhD students in areas like data integration and genetic circuit synthesis. He has contributed to international conferences and serves as a reviewer/examiner for academic programs. His work bridges theoretical foundations with industrial applications, particularly in embedded systems and data management. He has collaborated internationally, with projects addressing ESG reporting standards and regulatory compliance through automated data traceability.

• Object-Oriented Programming
• Software Engineering
• Formal Methods
• +5 more

Bertrand Meyer is a renowned academic and software engineering expert affiliated with Constructor University in Switzerland. He previously held positions at ETH Zurich (2001-2016), the University of Toulouse (2015-2016), and Monash University. His research focuses on object-oriented programming, software engineering, formal methods, and programming languages. He is best known for developing the Eiffel programming language and pioneering the 'Design by Contract' paradigm. Meyer earned his PhD from the University of Nancy, France. His contributions include seminal textbooks like *Object-Oriented Software Construction* (1988, 1997), *Touch of Class* (2009), and *Agile!* (2014). He has received the ACM Software System Award (2006) for his work on Eiffel. His research emphasizes rigorous software design principles, formal verification, and practical software engineering practices. Key innovations include: Design by Contract methodology Advancements in object-oriented design patterns Contributions to component-based development Work on software testing and validation techniques Meyer has authored over 374 publications spanning journals, conferences, and books. His work bridges theoretical foundations and practical software development methodologies.

Fred PopowichView profile

Professor

• Natural Language Processing
• Artificial Intelligence
• Big Data
• +4 more

Fred Popowich is a Professor in the School of Computing Science at Simon Fraser University (SFU), Canada. He holds adjunct positions at Dalhousie University's Faculty of Graduate Studies and is an Associate Member of SFU's Department of Linguistics and Cognitive Science Program. His academic career began post-PhD (Cognitive Science/Artificial Intelligence, University of Edinburgh, 1989) and has spanned over three decades at SFU. Education: PhD in Cognitive Science/Artificial Intelligence (University of Edinburgh, 1989); M.Sc. and B.Sc. in Computing Science (Simon Fraser University and University of Alberta, 1985/1982). Research focuses on natural language processing (NLP), machine translation, intelligent systems, and big data applications. He directs SFU’s Big Data Initiative and leads the Natural Language Laboratory, supervising MSc/PhD students in computing science. His work includes developing systems for smart homes, toxic language detection in social media, and energy grid analysis. Industry roles include co-founding Axonwave Software (as CTO/President) and contributing to technology commercialization. Current projects address EV charging impacts, personalized learning systems, and real-time load monitoring. Publications span machine translation, sentiment analysis, and NLP applications in education and energy systems. His work bridges theoretical computer science with practical applications in healthcare, smart cities, and education.

• Semantic Web and Ontology Engineering
• Agent-Based Modeling
• Knowledge Graphs
• +4 more

Giovanna Di Marzo Serugendo is a researcher affiliated with the University of Geneva (Faculty of Social Sciences, Centre for Informatics) and the Institute of Information Service Science (ISS) . Her work spans semantic technologies, agent-based modeling, and sustainable systems. Research interests focus on Semantic knowledge graphs for regulatory compliance Ontology-driven resource management Self-organizing systems inspired by biological models AI applications in smart grids and urban mobility Digital agriculture platforms for smallholder farmers Recent publications highlight trends in ontology automation using LLMs, agent-based simulations for urban planning, and KG-enhanced compliance frameworks . She leads projects integrating digital twins with smart energy systems and develops bio-inspired coordination paradigms. Supervised works include 17 research projects in these domains. Current technical reports and conference papers explore cybersecurity-safety interdependencies in autonomous vehicles and decentralized event source detection in sensor networks.

Tillman WeydeView profile

Academic

• Machine Learning
• Signal Processing
• Data Analysis
• +5 more

Dr. Tillman Weyde is a Reader in the Department of Computer Science at City, University of London , where he has been employed since 2021. He leads the Machine Intelligence and Media Informatics Research Group and is a member of the Machine Learning Group . Prior to this, he served as Senior Lecturer (2009–2021) and Lecturer (2005–2009) at City, and worked as a researcher at the University of Osnabrück (2001–2005), coordinating the MUSITECH project. His academic background includes PhD in Music Technology (2002), MSc in Computer Science (1999), and MSc in Mathematics, Music, Philosophy & Pedagogy (1994), all from the University of Osnabrück. Research Focus: Machine learning and signal processing methods for data analysis with applications in finance, audio, NLP, music, health, security, and education. His recent work emphasizes inductive biases in neural networks for rule-learning, extrapolation, generalization, and interpretability. Grants & Projects: Principal Investigator for the AHRC-funded Digital Music Lab (2012–2017) and Integrated Audio-Symbolic Model of Music Similarity (2017–present). Co-investigator in Innovate UK and EPSRC projects on safer gambling ( Advancing Consumer Protection , 2015–2018) and Raven (2012–2021). Collaborations: Affiliated with the Institute of Cognitive Science (Osnabrück), Intelligent Systems Research Laboratory (Reading), and the MPEG Ad-Hoc Group on Symbolic Music Representation. Awards: Co-author of the 2000 Comenius Medal-winning educational software Computer Courses in Music Ear Training and co-editor of the Osnabrück Series on Music and Computation . Publications: Over 150 peer-reviewed works including conference papers, journal articles, and book chapters, focusing on interdisciplinary applications of machine learning in music, health, and finance. Students: Supervised 13 PhD students across topics like grammar bias in neural networks, emotion recognition from audio, extrapolation behavior in neural networks, relation-based patterns, legal text parsing, and more.

Davide Di RuscioView profile

Professor

• Model Driven Engineering
• Model evolution
• Open Source Software
• +7 more

Davide Di Ruscio is a Full Professor at the Department of Information Engineering Computer Science and Mathematics of the University of L'Aquila (Italy), where he leads research in Model-Driven Engineering and Software Engineering. His work spans domain-specific modeling languages, model transformations, and recommender systems applied to open source software and autonomous systems. His research interests focus on Model Driven Engineering , Model evolution , Open Source Software , and Recommender Systems , with recent work exploring LLM applications in code analysis and fairness engineering. Key application domains include service-based systems, autonomous systems, and hybrid polystore systems. Di Ruscio actively contributes to the software engineering community through leadership roles in major conferences and journals. He serves on the steering committees of ICMT, SLE, SATTOSE, MiSE, and RoSE, and is on the editorial boards of SoSyM, IEEE Software, Journal of Object Technology, and IET Software. His work has been published in over 200 papers across top-tier venues. He has contributed to numerous European and Italian research projects since 2006, applying MDE concepts to real-world systems. Current teaching includes Software Engineering for Autonomous Systems and Software Engineering for the Internet of Things, with office hours on Tuesdays and Wednesdays from 11:30-13:30 at Edificio Alan Turing, Room 208.

Carlo AngiuliView profile

Assistant Professor

• Type Theory
• Programming Language Foundations
• Homotopy Type Theory
• +3 more

Carlo Angiuli is an Assistant Professor of Computer Science at the Luddy School of Indiana University . He is a leading researcher in type theory , with a focus on its applications to programming language design and logic . His work bridges theoretical foundations and practical implementations, particularly through dependent types , proof assistants , and homotopy type theory . His research interests include: Type Theory (foundational systems for programs and proofs) Programming Language Foundations (formal semantics and reasoning) Homotopy Type Theory (higher-dimensional structures) Dependent Types (expressive type systems) Proof Assistants (formal verification tools) Computational Logic (algorithmic reasoning) Angiuli actively contributes to the programming languages community as a POPL Program Committee member and co-author of a forthcoming textbook on dependent type theory. His students include Johnson He, Huang Xu, Kelton OBrien, and Ian Ray , who joined in Fall 2025. He has received significant recognition, including the Best Paper Award at FSCD 2019 and the School of Computer Science Distinguished Dissertation Award from Carnegie Mellon University. His current work explores advanced type-theoretic frameworks and their implementation in proof assistants like the red* family of tools. Scientific awards: Best Paper Award, FSCD 2019 (Junior Researchers category) School of Computer Science Distinguished Dissertation Award, Carnegie Mellon University He teaches courses such as Modern Dependent Types (CSCI-B619), Programming Language Foundations (CSCI-B522), and Introduction to Computer Science (CSCI-C211).

Yi LiView profile

Associate Professor

• Software Engineering
• Program Analysis
• Automated Reasoning
• +2 more

Yi Li is an Associate Professor at the College of Computing and Data Science, Nanyang Technological University (NTU), Singapore. He leads the Software Reliability and Security Lab (SRSLab@NTU) which focuses on program analysis and automated reasoning techniques for software engineering and security applications. Dr. Li received his BComp degree in Computer Science from the National University of Singapore in 2011, followed by MSc (2013) and PhD (2018) degrees in Computer Science from the University of Toronto. His educational background has positioned him at the forefront of software reliability research. His research interests span software engineering, program analysis, automated reasoning, and formal methods, with particular focus on software reliability, security, and smart contract analysis. Dr. Li's work develops practical solutions for constructing high-quality software systems that are both reliable and sustainable. His research has identified critical issues in API documentation, smart contract security, program termination, and library compatibility across multiple programming ecosystems. Dr. Li's publications demonstrate consistent contributions to software engineering research over the past five years, with recent work focusing on smart contract analysis, API documentation verification, and program termination detection. His research methodology often combines static and dynamic analysis techniques with machine learning approaches to address challenging problems in software reliability and security. Five ACM Distinguished Paper Awards at top conferences Two Best Artifact Awards recognizing research reproducibility Publications at premier venues including ASE, ISSTA, FSE, and ICSE Dr. Li actively contributes to the software engineering community through service on program committees of flagship conferences (ICSE, FSE, ASE, ISSTA) and co-chairing program committees for ICFEM'23, ICECCS'20, SEAIS'22, and ICFEM'19 Doctoral Symposium. His lab, SRSLab@NTU, has developed multiple influential tools including InvCon, DocCon, and EndWatch, while fostering research in software reliability and security for emerging technologies.

Eugene StarkView profile

Professor

• Operating Systems
• Programming Language Semantics
• Concurrency Theory
• +3 more

Eugene Stark is a Professor in the Department of Computer Science at Stony Brook University, affiliated with the College of Engineering and Applied Sciences. His work focuses on theoretical foundations and practical applications in systems and programming languages. Educational Background: He earned his Ph.D. in Computer Science from the Massachusetts Institute of Technology (MIT) in 1984. Research Interests: His primary areas include Operating Systems, Programming Language Semantics, Concurrency Theory, Distributed Algorithms Verification, and Functional Programming Languages. He explores formal methods to ensure correctness and efficiency in complex systems, leveraging category theory for rigorous semantic frameworks. His work often addresses challenges in indeterminate dataflow networks and probabilistic models. Publications Overview: Stark’s recent articles emphasize categorical structures (e.g., residuated transition systems, bicategories) and probabilistic I/O automata. They reflect a trajectory from foundational theory to tool development for concurrent system analysis. Academy of Teaching Scholars award Department Award for Undergraduate Teaching (2000) Advising & Grants: No formal advisees are listed in current records. His research projects include the Probabilistic I/O Automata framework, CARA Infusion Pump specifications, and SAMSON Network Memory Server initiatives. Grants and funding details are not explicitly mentioned. Labs/Teams: He is associated with the Laboratory for 體魯 Institute of (1988), though the lab name’s full English title remains unclear. Collaborations likely extend to interdisciplinary projects involving formal methods and systems engineering.

Andrew SalchView profile

Associate Professor

• Algebraic Topology
• Stable Homotopy Theory
• Number Theory
• +3 more

Andrew Salch is an Associate Professor in the Department of Mathematics at Wayne State University's College of Liberal Arts and Sciences. His research bridges algebraic topology, number theory, and data science, with a focus on stable homotopy theory, formal groups, and topological methods for fMRI analysis. He mentors graduate students and develops computational tools for mathematical research. Education: Ph.D. in Mathematics, University of Rochester (2008) M.A. in Mathematics, University of Rochester (2005) B.S. in Mathematics, Portland State University (2003) Research Interests: Salch's work explores the interplay between homotopy theory and number theory, particularly via L-functions, Iwasawa theory, and formal modules. He also applies topological data analysis (TDA) to neuroscience, developing tools for fMRI data. His computational projects include Sage scripts for Morava stabilizer group actions and persistent homology workflows. Publication Trends: His articles primarily address algebraic topology (e.g., Morava stabilizer groups, cobordism) and number-theoretic connections (e.g., zeta-functions, Iwasawa invariants). Recent work expands into fMRI data analysis using persistent homology and statistical inference, reflecting interdisciplinary collaboration. Advising and Collaborations: He advises students like Mohammad Behzad Kang and collaborates with labs (e.g., Diwadkar Lab at WSU Medical School) on fMRI projects. His pure mathematics collaborations include work with Luca Candelori on topological modular forms and with Gabe Angelini-Knoll on homotopy limits. Tools and Software: Salch develops open-source tools for topological data analysis (e.g., fMRI pipelines) and computational topology (e.g., Sage scripts for formal group laws). His seminar notes on modular forms and L-functions are publicly shared.

Assia MahboubiView profile

Researcher

• Formal Methods
• Type Theory
• Interactive Theorem Proving
• +12 more

Assia Mahboubi is a tenured researcher at Inria in the Gallinette team , Nantes, France, and an endowed professor in the Algebra and Number Theory section at Vrije Universiteit Amsterdam , Netherlands. Her work bridges formal methods, type theory, and computer-aided mathematics. Research Interests: Her research centers on the formalization of mathematics in dependent type theory and the automated verification of mathematical proofs. She is particularly interested in the interplay between computer algebra and formal proofs, and in how formal representations enhance understanding of mathematical objects. She is a lead developer of the Mathematical Components libraries and a key user of the Coq proof assistant. Recent Research Trends: Her recent publications focus on diagram chasing in category theory, continuity in constructive type theory, proof transfer mechanisms (e.g., Trocq), and the formal verification of advanced mathematical results such as the irrationality of ζ(3) and the unsolvability of the quintic. These works demonstrate a consistent emphasis on foundational rigor, automation, and scalability in formal proofs. ERC Consolidator Grant: FRESCO (Fast and Reliable Symbolic Computation) Advising and Grants: Mahboubi supervises PhD students including Enzo Crance, Martin Baillon, and postdoc Matthieu Piquerez. She leads the FRESCO project funded by an ERC grant, supporting research in symbolic computation and formal verification. Team Affiliation: She is a core member of the Gallinette team at Inria, which focuses on the intersection of proofs and programs, promoting the development of reliable and verifiable software and mathematical systems.

Anya Helene BaggeView profile

Associate Professor

• Programming Language Design and Implementation
• Software Language Engineering
• Semantics of Programming Languages
• +8 more

Anya Helene Bagge is an Associate Professor in the Department of Informatics at the University of Bergen, where she is a researcher at the Bergen Language Design Laboratory. Her work focuses on programming languages and software language engineering, with strong ties to education and tool development. Research Interests: Programming language design and implementation Software language engineering Semantics of programming languages Domain-specific languages and language extensions Program transformation using Rascal, MPL, and Stratego/XT Aspect-oriented programming, especially Domain-Specific Aspect Languages Her recent publications reflect a consistent focus on software language engineering, refactoring, microservice security, and programming education. Themes across her work include language design, program analysis, and the development of educational tools and methodologies. Scientific Awards: The Realist Committee's Teaching Award 2016/17 Lecturer of the Year in Computer Science (Spring 2015) Anya Bagge actively supervises students, including PhD and Master’s candidates such as Tero Hasu, Kristoffer Haugsbakk, and Nina Andersen. She has been involved in numerous academic activities, including organizing the OOPSLE workshop and serving on program committees for conferences like SLE, HILT, and WCRE. She has also taught core courses including INF101, INF225, and INF328, demonstrating a strong commitment to both research and teaching. Labs and Teams: She is affiliated with the Bergen Language Design Laboratory , collaborating with researchers such as Magne Haveraaen, Eva Burrows, and Tero Hasu.

• Programming Theory
• Algebraic Methods in Software Development
• Programming Language Design
• +12 more

Magne Haveraaen is a Professor in the Department of Informatics at the University of Bergen, where he leads the Bergen Language Design Laboratory (BLDL). He is actively engaged in research on programming theory, formal methods, language design, and high-integrity systems. His work centers on algebraic specifications, generic programming, domain engineering, and the design of the Magnolia programming language. He has been a long-standing instructor of key courses such as INF220 (Program Specification) and INF222 (Programming Languages), and contributes to national and international academic forums. University: University of Bergen School: Faculty of Mathematics and Natural Sciences Department: Department of Informatics Academic Rank: Professor Email: magne.haveraaen@uib.no His research interests include programming language design, formal specifications, generic and mouldable programming, multicore and GPU computing, and algebraic methods in software development. He emphasizes correctness, reuse, and high-integrity software through theoretical and practical innovations. He has contributed extensively to the literature on algebraic reasoning, array programming, and domain-specific abstractions. The recent publications highlight a consistent focus on algebraic semantics, language design (especially Magnolia), array programming, and formal verification. Themes across these works include correctness by design, specification-driven development, and adapting programming models for modern architectures. His involvement in workshops like ARRAY, WGP, and CALCO underscores his leadership in programming language theory. No scientific awards are listed in the provided texts. He advises students and welcomes collaboration in programming theory, language design, and formal methods. He has led funded projects such as MoSIS and SHIP and is involved in the High Integrity Systems Forum. He organizes and participates in key conferences including NWPT, GPCE, and SCAM. He leads the Bergen Language Design Laboratory (BLDL), which focuses on experimental language design, and contributes to the SAGA initiative on scientific computing with algebraic abstractions. His work integrates theory with practical tooling and language implementation.

François PottierView profile

Researcher

• programming languages
• functional programming
• type systems
• +5 more

François Pottier is a senior researcher at Inria in Paris, France, where he leads the Cambium research team. He is affiliated with the Gallium research group and has maintained an active research profile spanning several decades in programming languages and formal methods. His research focuses on programming languages , particularly functional programming and OCaml, type systems design and implementation, program verification using separation logic, and compiler construction . His work bridges theoretical foundations with practical implementation, evidenced by numerous open-source software tools he has developed. Pottier's publication record shows consistent contributions to top programming languages conferences (POPL, ICFP, ESOP) with recent work emphasizing separation logic frameworks, resource analysis, and formal verification of OCaml systems. His research demonstrates a clear trajectory from foundational type theory toward practical verification techniques for real-world programming languages. He has advised numerous PhD students including Remy Seassau, Tiago Soares, Clément Allain, and Alexandre Moine, among others, many of whom have gone on to research positions at institutions like New York University, Imperial College London, and Inria itself. Pottier maintains active service roles in the programming languages community as a member of IFIP Working Group 2.8 on Functional Programming and IFIP Working Group 2.16 on Language Design, and serves on program committees for major conferences including upcoming roles for JFLA 2026 and ITP 2026. He leads the Cambium research team at Inria, which focuses on programming language theory and implementation, particularly around OCaml and formal verification. The team develops both theoretical frameworks and practical tools that have influenced the broader programming languages ecosystem.

Ayana T. ArceView profile

Associate Professor

• Particle Physics
• High Energy Physics
• Collider Physics
• +5 more

Ayana T. Arce serves as Associate Professor of Physics within the Department of Physics at Duke University's Trinity College of Arts & Sciences, a position she has held since 2016 after advancing from Assistant Professor (2010-2016). Her research centers on experimental particle physics using the ATLAS detector at CERN's Large Hadron Collider, focusing on phenomena beyond the Standard Model including Higgs boson properties and jet substructure analysis. Education: Ph.D. in Physics, Harvard University (2006) B.S. in Physics, Princeton University (1998) Research Focus: Dr. Arce's work bridges theoretical predictions and experimental verification through precision measurements of proton-proton collisions. Her expertise spans trigger system development, heavy resonance searches, and calibration of large-radius jets—critical for identifying new physics signatures. She actively contributes to advancing analysis techniques for boosted objects and diboson resonances. Publication Trends: Her 15-year publication record (2008-2024) demonstrates consistent leadership in ATLAS collaboration efforts, evolving from foundational detector studies to cutting-edge Run 3 trigger systems. Recent work emphasizes real-time data processing for high-luminosity operations while maintaining rigorous statistical validation of Standard Model predictions. Grant Funding: Secured major support including: National Science Foundation REU Sites (2022-2027, 2018-2022, 2015-2019, 2009-2015) for undergraduate nuclear physics research Department of Energy grant (2013-2025) for High Energy Physics at Duke Brookhaven National Laboratory project (2024-2025) for ITK Module Assembly Collaborations: As a core ATLAS collaboration member at CERN, she participates in international data analysis working groups and contributes to detector upgrade projects for future LHC runs. Her external relationship with CERN is formally documented through Duke University's conflict of interest management system.