Jeremy Yallop is a researcher at the University of Cambridge specializing in programming languages, type systems, and compiler design. He actively contributes to academic conferences such as PLDI, POPL, ICFP, and GPCE, focusing on staged computation, generic programming, and language design. Key Research Areas: Functional Programming, Generative Programming, Type Systems, Partial Evaluation Conference Roles: PC Co-Chair (PEPM 2017), Steering Committee Chair (PEPM 2019), Session Chair (OCaml 2023, PEPM 2022), Tutorial Presenter Notable Contributions: Verified Scheme compiler via CakeML, Macros in OCaml (MacoCaml), Dependent Types in Defunctionalization, Algebraic Simplification (Frex) Recent Trends: 2026 work on TEAL (Verified Assembly Language), 2025 developments in Dependently Typed Algebraic Simplification Awards: No explicit honors mentioned in provided data
Danijela Tešendić serves as an Associate Professor in the Department of Mathematics and Informatics at the Faculty of Sciences, University of Novi Sad. Her office is located in the Information Technologies and Systems office (DMI&DF), second floor, room 50, with contact details including telephone (485)-2873 and email tesendic@dmi.uns.ac.rs. She maintains a professional presence through her website at http://www.is.pmf.uns.ac.rs/daca/. Her research demonstrates dual expertise in environmental monitoring systems and library information technology. Recent work (2022-2025) focuses on machine learning applications for airborne pollen classification using CNN architectures and domain adaptation techniques, contributing to standardization frameworks in environmental science. Earlier contributions (2013-2019) established foundational work in library management systems, particularly through the BISIS software platform, business intelligence integration, and mobile accessibility solutions for visually impaired patrons. Analysis of her publication trajectory reveals a strategic shift toward interdisciplinary environmental informatics while maintaining connections to information systems. Her pollen monitoring research bridges computer vision with ecological applications, emphasizing real-time processing and cross-device compatibility. Concurrently, her library science work pioneered cloud-based service models and inclusive design principles, showcasing adaptable technical frameworks across distinct domains. Scientific Awards No awards or honors were documented in the provided materials. Advising and Grants Student mentorship details are absent from the source text. No research grants or funding sources are explicitly referenced.
Cyril Faucher is an Associate Professor at the University of La Rochelle , associated with both the L3i Laboratory and the IUT of La Rochelle 's Computer Science department. He has served since 2013 as the head of the Integrator Developer (ID) course within the DUT Informatique program. His research focuses on Temporal Knowledge Modeling Model-Driven Engineering Semantic Web Applications Periodic Event Simulation Human Activity Modeling He has contributed to multiple research projects including ANR DéAIS (2014-2016), HOSEN (2013-2016), and Tourinflux (2013-2015). His work has been implemented in the RelaxMultiMedias ANR project (2009-2012) for cultural event modeling. Professor Faucher teaches across various IT domains including Database Systems (Oracle, MySQL) Web Development (PHP, JavaScript, jQueryMobile) Object-Oriented Programming (Java) Enterprise Architecture (UML, TOGAF) Software Project Management (Agility, SCRUM) Model-Driven Engineering He has developed several open-source tools for model engineering including Kermeta, OpenEmbeDD, and MDE Utils.
Pierre Laforcade is a researcher at the University of Le Mans, affiliated with the IEIAH (Laval) laboratory. His work focuses on applying Model-Driven Engineering (MDE) principles to Technology-Enhanced Learning (TEL), with a particular emphasis on serious games, gamification, and adaptive learning scenarios for children with Autism Spectrum Disorder (ASD). He develops domain-specific modeling methodologies and graphical instructional design languages to create specialized editors for educational applications. His research spans three decades, with recent publications (2023-2025) exploring frameworks for generating personalized training games, mapping declarative knowledge to gameplay mechanics, and enhancing system maintainability through uncertain model transformations. Earlier work (2005-2021) concentrated on formalizing instructional design languages for Learning Management Systems (LMS) like Moodle, meta-modeling approaches, and visual scenario design using UML4LD. Current research: Serious games for declarative knowledge, roguelite-based educational frameworks, MDE-driven TEL systems Key collaborations: Bérénice Lemoine, Sébastien George, Youness Laghouaouta Notable contributions: Domain-specific modeling tools, adaptive scenario generation, LMS instructional language formalization
Mihhail Matskin is a Professor at the Royal Institute of Technology (KTH) within the Department of Software Logic & Computer Systems. He specializes in cloud computing, big data pipelines, machine learning, and distributed systems. His work emphasizes optimizing cloud resource allocation, developing graph-based cost models, and advancing AI-driven systems like SQL recommendation engines and relation extraction frameworks. He actively contributes to KTH's educational mission through roles as examiner and course manager in advanced computer science and engineering courses, including Distributed AI, Cloud Storage Optimization, and Big Data Workflow Design. His research spans over two decades, focusing on scalable data management solutions, edge computing applications in healthcare, and semantic analysis of social media. Notable projects include the DataCloud initiative for big data pipeline orchestration and the DEF-PIPE DSL visualization framework. Matskin’s work bridges theoretical advancements with practical implementations, addressing challenges in reproducibility of LLM-based systems, containerized edge computing, and constraint programming for robotics. His academic contributions include pioneering studies on cloud cost modeling, rule-based storage tiering, and contrastive learning for NER tasks. He has advised numerous advanced-level degree projects across computer science, embedded systems, and communication technologies. Matskin’s lab focuses on innovative solutions at the intersection of distributed systems, AI, and data engineering.
Saverio Perugini is a Professor of Mathematics and Computer Science at Ave Maria University, leading the computer science program since 2022. Previously, he spent 18 years as a faculty member at the University of Dayton, where he held roles including undergraduate program director. He earned his Ph.D. in Computer Science from Virginia Tech in 2004. His research focuses on functional programming, engineering interactive computing systems, and applying programming language concepts to novel domains like human-computer interaction. Perugini is a Senior Member of the ACM and IEEE Computer Society. He has published extensively, including a textbook Programming Languages: Concepts and Implementation (2023), and co-authored a NSF-funded project (2017–2022) on active learning in computer science education. His work emphasizes practical, hands-on teaching, integrating programming with problem-solving and computational thinking. He has advised numerous students and contributed to curriculum development, including courses on programming languages, operating systems, and artificial intelligence. Perugini’s funded research includes a $299,864 NSF grant for active learning in STEM education. He also leads initiatives like the Ave Maria Computer Science program, emphasizing ethical and humanistic approaches to technology. His research and teaching align with Catholic educational values, fostering intellectual curiosity and moral integrity in students.
Prof. Dr. Thomas Baar is a Professor at HTW Berlin, specializing in cyber-physical systems, formal verification, and model-driven engineering. His research focuses on hybrid systems, automated driving platforms like CeCar, and improving usability of verification tools such as KeYmaera. He contributes to software engineering education and legacy system modernization through domain-specific languages (DSLs) and graphical editors. Baar's work spans academia and industry, with collaborations in aerospace safety, multiagent systems, and cybersecurity for control systems. His research interests include formal methods for hybrid systems, software reliability, and educational platforms for autonomous systems. He has published extensively on topics like verification frameworks, syntax improvements for formal tools, and safety analysis methodologies. His interdisciplinary approach bridges theoretical computer science with practical applications in aerospace, automotive, and industrial automation. Key contributions include the CeCar platform for autonomous driving research, modularization enhancements for KeYmaera, and DSL-based solutions for legacy software maintenance. Baar collaborates with institutions like the IFAF Berlin and participates in EU-funded projects focusing on smart cities and sustainable technologies. His publications reflect a strong emphasis on verification techniques, with over 15 peer-reviewed articles since 2015. He is affiliated with the HTW Berlin's Wilhelminenhof Campus and actively engages in knowledge transfer initiatives to bridge research and industry needs.
Shih-Hsi (Alex) Liu is a Professor in the Department of Computer Science at Fresno State. He holds a Ph.D. from the University of Alabama at Birmingham (2007), an M.S. from the University of Houston (2002), and a B.S. from National Chiao-Tung University, Taiwan (2000). His research focuses on software engineering, meta-heuristics, evolutionary algorithms, and service-oriented architectures. Dr. Liu leads the Cloud Agility Lab and has published over 30 articles with 3,000+ citations. He serves on the editorial board of Applied Soft Computing (impact factor 7.2) and has mentored over 30 student projects. His work explores algorithmic optimization, QoS-driven systems, and domain-specific languages implementation through service-oriented technologies. Education: Ph.D., Computer Science, University of Alabama at Birmingham, 2007 M.S., Computer Science, University of Houston, 2002 B.S., Computer Science, National Chiao-Tung University, 2000 Research emphasizes balancing exploration/exploitation in evolutionary algorithms, improving compiler generation for DSLs, and addressing challenges in swarm intelligence. Recent work critiques algorithm stopping criteria and proposes memory-assisted optimization techniques. His articles address topics like MIoT applications, artificial bee colony parameter tuning, and QoS-aware service composition. Grant and advising activities remain centralized through student project supervision, with no specific grants mentioned in the text. The Cloud Agility Lab focuses on advancing cloud computing and software agility in distributed systems.
Dr. Sofia Meacham is a Professor and Principal Academic in Computing & Informatics at Bournemouth University. She holds a PhD from the University of Patras (Greece, 2000) and a Diploma in Computer and Informatics Engineering (1994). Her research focuses on embedded systems design, domain-specific modeling, IoT applications in education, and cloud computing. She has extensive experience in EU-funded projects and industry collaborations (e.g., INTRACOM Telecommunications Solutions), with over 25 years of teaching in the UK and Greece. Education PhD in Computer Science, University of Patras, Greece (2000) Diploma in Computer and Informatics Engineering, University of Patras, Greece (1994) Research Interests Dr. Meacham's work spans system-level design for embedded telecommunication systems, hardware-software co-design, and formal refinement techniques. She has recently expanded into educational technology, developing frameworks for personalized online education, AI-driven learning systems, and domain-specific languages (DSLs) for clinical protocols and physics simulations. Her work on cloud computing includes fair resource allocation algorithms and autonomic cloud management. Grants & Projects MDENET: Evaluation of a DSL for Chronic Kidney Disease protocols (EPSRC, 2023) "Towards Explainable AI" (Match-funded with BT, 2018) "Self-aware and Self-adaptive Systems" (BT, 2016) Labs & Collaborations She collaborates with medical professionals to co-create DSLs for clinical protocols and leads projects integrating IoT into educational systems. Her work with low-code platforms aims to democratize app development for healthcare.
Todd Austin is the S. Jack Hu Collegiate Professor of Electrical Engineering and Computer Science at the University of Michigan's College of Engineering. His research focuses on secure computer architecture and hardware-software co-design for security-critical systems. His primary research interests include computer architecture , hardware security , secure system design , and side-channel protection . Austin's work emphasizes practical solutions for real-world security challenges through hardware-software co-design and formal verification techniques. Recent publications (2022-2025) demonstrate a strong focus on data-oblivious execution , moving target defenses , and hardware-based security primitives . Key themes include eliminating side-channel leakage through program transformations, sequestered encryption techniques, and architectural support for vulnerability-tolerant systems. Austin maintains active research engagement through his Austin-Lab and open-source contributions, including the widely-forked bringup-bench repository for CPU and system validation. Contact: austin@umich.edu | Office: 4637 BBB, 2260 Hayward Avenue, Ann Arbor, MI 48109-2121 | Phone: 734-936-0370
Klaus Ostermann is a Professor of Programming Languages and Software Technology at the Department of Computer Science, Faculty of Science, University of Tübingen, Germany. He leads a research group focused on programming language design, functional programming, and software modularity. Research Interests: His work spans functional programming, type systems, effect handlers, software architecture, and domain-specific languages. He investigates the duality between data and codata, the safe integration of effects in typed languages, and the modularity of software systems. His research often bridges theoretical foundations with practical implementations in languages like Scala and Haskell. The recent publications highlight a strong trend in effect systems, continuation-passing, and the symmetry between data and codata. His group develops the Effekt language and explores advanced compilation techniques for effect handlers, contributing to both theoretical understanding and practical language design. Scientific Awards: Most Influential Paper Award at GPCE 2018 for 'Polymorphic Embedding of DSLs' (2008 paper) He actively supervises PhD and master’s students, including Philipp Schuster, Marius Müller, and Jonathan Brachthäuser. His group has received funding for research in programming language foundations, effect systems, and software modularity, though specific grants are not listed. He serves on the program committees of top conferences such as POPL, ICFP, PLDI, and OOPSLA, reflecting his active role in the programming languages community. The research is conducted within the Uroboro project, which explores duality in programming language constructs, and involves collaboration with both national and international researchers. The team also engages in educational projects, including thesis supervision on topics ranging from probabilistic programming to music notation visualization.
Ben Greenman is an Assistant Professor at the University of Utah's Department of Computer Science. He has affiliations with institutions including Cornell University (BS, M.Eng), Northeastern University (PhD), and Brown University (CIFellows 2020). His work spans programming language design, type systems, formal methods, and human factors in software development. His research focuses on Gradual typing and type soundness Language design with emphasis on usability Formal methods education tools Empirical studies of type system usage Recent work analyzes temporal logic misconceptions, privacy-respecting telemetry for type errors, and macro systems without traditional syntax barriers. His publications reveal trends in Gradual type migration Runtime monitoring and profiling Visual formal methods Developer-centric language design He has received the CIFellows 2020 award and serves on program committees for SPLASH, Scheme, and other conferences. His work addresses both theoretical and practical aspects of programming language design.
Daniel W. Barowy is an Associate Professor in the Department of Computer Science at Williams College . His research focuses on programming languages , particularly end-user programming , crowdsourcing , and spreadsheet debugging . He integrates program analysis with statistical techniques to improve software usability and robustness. Current affiliations: Williams College (2017-present) Education: University of Massachusetts Amherst (PhD, 2017) His research explores language abstractions for human-computer integration , with notable projects like ExceLint (spreadsheet error detection), FlashRelate (spreadsheet data extraction), and Riker (incremental build systems). He emphasizes artifact verification , securing PLDI 2015 Distinguished Artifact Award and USENIX ATC 2022 Best Paper . Recent publications demonstrate trends in spreadsheet reliability , crowdsourcing frameworks , and scalable educational tools . He has received "Artifact Verified" badges for multiple projects and actively contributes to software tool development , including AutoMan , ExceLint , and CheckCell . USENIX ATC 2022 Best Paper PLDI 2015 Distinguished Artifact Award Multiple "Artifact Verified" badges As an educator, he teaches CSCI 334: Principles of Programming Languages and CSCI 331: Computer Security . His work bridges theoretical PL research with practical applications in spreadsheet programming and crowdsourcing platforms .
Gregor Kiczales is a Professor of Computer Science at the University of British Columbia , with a career spanning over three decades. His work focuses on programming language design, modularity, and aspect-oriented programming (AOP). Primary affiliation: University of British Columbia Verification email: gregor@cs.ubc.ca Kiczales' research centers around modularity and aspect-oriented programming , with significant contributions to understanding crosscutting concerns, developing AOP frameworks like AspectJ, and exploring novel abstractions for software systems. His work includes: Foundational research in AOP semantics and implementation Studies on code-design alignment and software architecture Developing registration-based abstractions and late-binding mechanisms Investigating scalability challenges in AOP systems
Bernhard Rumpe is a full Professor at RWTH Aachen University, where he leads the Chair of Software Engineering (Department of Computer Science 3). His research focuses on model-based software and systems engineering (MBSE), domain-specific languages, and generative development techniques to improve software quality and development efficiency. His research interests include: Model-Based Software Engineering (MBSE) Domain-Specific Languages (DSLs) and language workbenches like MontiCore Model-driven digitalization and digital twins Agile integration with formal modeling Applications in embedded systems, AI, automotive, IoT, and cloud systems His team has developed MontiCore, a powerful language workbench used in both academia and industry for creating and processing DSLs, supporting code generation and static analysis. Research projects span theoretical foundations and industrial applications, with over 100 successfully completed projects celebrated recently. The recent publications reflect a strong trend in model-driven engineering, emphasizing formal modeling, automation, and scalability. Key themes include DSL design, variability modeling, digital twins, and integration of MBSE with agile practices. The work bridges theoretical rigor with practical implementation, especially in safety-critical and complex systems. Scientific contributions and leadership are evident through: Founding and leading a major research chair in software engineering Supervising PhD students such as Sage Binder and Brooke Burson Securing and managing over 100 research projects with industrial partners Developing widely used tools like MontiCore He also actively promotes academic careers, inviting applications for PhD and postdoctoral positions in software engineering, including opportunities for habilitation. The research is conducted within the Software Engineering group at RWTH Aachen, which fosters collaboration between students, researchers, and industry partners, focusing on innovation in software development processes and tools.
