جست‌وجوی استاد و پژوهشگر

Klaus Ostermannمشاهده پروفایل

استاد

• Functional Programming
• Programming Language Design and Implementation
• Type Systems
• +۷ مورد دیگر

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.

• Programming Language Theory
• Functional Programming
• Logic Programming
• +۳ مورد دیگر

Tom Schrijvers is a Professor at the Department of Computer Science, Faculty of Engineering Science, KU Leuven. His research focuses on programming language theory, functional programming, logic programming, and computational effects. Advancing multi-stage programming with computational effects (2024–2028) Generating Educational Feedback with Program Analysis (2024–2028) Programino: An Educational Programming Platform (2023–2027) eTeacher: Interactive web-based programming education platform (2023–2025) AmPERSand: Programming Education Runtime System (2023–2026) His recent publications emphasize bidirectional transformations, effect handlers, and programming education tools. He collaborates extensively with British institutions like Imperial College London and works on the book Language Engineering in Haskell with Dr. Nicolas Wu.

Anne Baanenمشاهده پروفایل

مدرس

• Formal Verification
• Type Theory
• Logic
• +۴ مورد دیگر

Anne Baanen is a Lecturer in the Department of Computer Science at the Faculty of Science, Vrije Universiteit Amsterdam. They recently completed their PhD in theoretical computer science under the supervision of Jasmin Blanchette and Sander Dahmen as part of the Lean Forward project. Their current teaching responsibilities include coordinating the Logic and Modelling course and supervising projects in Computer Assisted Proofs. Their educational background includes double majors in Computing Science and Mathematics for both Bachelor's and Master's degrees at Utrecht University. During their time at Utrecht, they were active in student organizations, serving as chair of the programming committee WebCie and the LGBT+ organization TrotCie, while also contributing to the student newspaper de Vakidioot. Dr. Baanen's research operates at the intersection of computing science and mathematics, spanning intuitionistic logic, type theory, formal verification, and functional programming. Their work heavily involves the Lean theorem prover, focusing on formalizing advanced mathematical concepts like algebraic number theory, Dedekind domains, and class groups. They are particularly interested in the design of morphisms and substructures in dependent type theory, as evidenced by their presentations on bundling in type theory. Analysis of their publication record shows a consistent focus on formalizing mathematical structures using the Lean theorem prover, with particular emphasis on algebraic number theory and the design of effective type class systems. Their work bridges theoretical computer science and advanced mathematics, contributing to both the formal methods community and mathematical research. Dr. Baanen is also active in sustainable ecology, LGBT+ rights advocacy, and software freedom movements. Their teaching portfolio spans from Logical Verification to Grondslagen van de Wiskunde (Foundations of Mathematics), demonstrating both breadth and depth in computer science education. They have presented at numerous international conferences including CPP, ITP, IJCAR, and ICFP, establishing themselves as an emerging researcher in formal methods. Based in Amsterdam, they maintain an active research profile while contributing to the academic community through teaching and conference organization, including co-organizing the Formalization of Cohomology Theories workshop at BIRS in Banff, Canada.

Ken Friis Larsenمشاهده پروفایل

دانشیار

• Programming Languages
• Security
• Privacy
• +۷ مورد دیگر

Ken Friis Larsen is an Associate Professor at the Department of Computer Science (DIKU), University of Copenhagen, specializing in programming languages, security, privacy, and functional programming. He contributes to projects like HIPERFIT (high-performance financial computing) and WallViz (visualization tools). Research Focus : Language design, formal methods, functional programming (Standard ML, Haskell, OCaml, Scheme), secure compilation, and performance optimization. Technical Leadership : Maintains Moscow ML (Standard ML implementation) and mGTK (functional GUI library). Key Publications : 2020: Hermes (secure compilation without side-channels) 2019: F (music composition language) 2016: Redomap (GPGPU performance in Futhark) Additional Contributions : Co-developed PaML (parser combinators in SML) Active participant in ICFP Programming Contest (2005, 2008, 2017) Advocate for rigorous testing practices (QuickCheck, Criterion) and type-driven design

Michael Hicksمشاهده پروفایل

استاد

• Programming Languages
• Computer Security
• Quantum Computing
• +۷ مورد دیگر

Michael Hicks is a Professor in the Department of Computer and Information Science at the University of Pennsylvania and an Amazon Scholar. Previously, he was a Professor at the University of Maryland (2002-2021) and Senior Principal Scientist at Amazon Web Services (2022-2025). He co-founded the Programming Languages research lab (PLUM) at Maryland and was its director, as well as Director of the Maryland Cybersecurity Center (MC2). He is a Fellow of the Association of Computing Machinery (ACM), former Chair of ACM SIGPLAN, and Editor-in-Chief of Proceedings of the ACM on Programming Languages (PACMPL). His research focuses on programming languages and their application to software security , quantum programming , and formal verification . He has pioneered dynamic software updating techniques, developed tools like Checked C for memory safety, and co-designed the Cedar authorization policy language at AWS. In quantum computing, he works on verified compilers like VOQC and Qunity to ensure reliability and correctness. His recent work trends include quantum programming languages , secure multi-party computation (e.g., Wysteria , Symphony ), and fuzz testing methodologies . He has contributed to formal verification for quantum programs and language-based security frameworks. Scientific Awards include: ACM Fellow He has advised numerous PhD and Master’s students , including James Parker, Andrew Ruef, Kesha Hietala, and Aseem Rastogi, who now hold academic and industry positions. His lab, PLUM , has been instrumental in advancing programming languages research.

Xinyu Fengمشاهده پروفایل

استاد

• Programming Languages
• Formal Methods
• Program Verification
• +۴ مورد دیگر

Xinyu Feng is a Professor at the Department of Computer Science and Technology, Nanjing University, with research spanning programming languages, formal methods, and system software verification. His work focuses on developing rigorous frameworks for certifying low-level system programs, particularly those involving concurrency, preemptive threads, and hardware interrupts. Nanjing University, China Huawei (collaboration) Yale University, PhD in Computer Science (2007) Research Interests: His research integrates Separation Logic and Rely-Guarantee Reasoning to create modular verification techniques for concurrent systems. Key areas include: Formal verification of OS kernels and hypervisors Concurrency control in preemptive and interrupt-driven environments Parameterized memory models for relaxed concurrency semantics Certified compilation and proof-carrying code Optimistic concurrency algorithms and non-blocking data structures Modular verification of synchronization primitives Article Trends: His publications emphasize modular and compositional methods for concurrent program verification, with a strong focus on practical applications in system software. Recurring themes include integrating formal reasoning with real-world challenges like hardware interrupts, preemptive scheduling, and SDN programming. Scientific Awards: PLDI'19 Distinguished Paper Award Professional Leadership: Xinyu Feng has served on program committees for leading conferences (POPL, PLDI, ICFP, CAV) since 2005 and chairs sessions at events like PLDI and POPL. He actively contributes to advancing formal verification standards in the field.

Bernardo Toninhoمشاهده پروفایل

استادیار

• Type Theory
• Programming Languages
• Linear Logic
• +۵ مورد دیگر

Bernardo Toninho is an Assistant Professor at the School of Science and Technology, NOVA University of Lisbon, with a research focus on type theory and its applications to concurrent and distributed systems. He is affiliated with NOVA-LINCS and actively works on session types, linear logic, and program verification in languages like Go, Rust, and Haskell. Research interests include Type Theory, Programming Languages, Linear Logic, and Meta-programming Current teaching: Concurrent Programming Languages, Introduction to Programming (Fall 2022) Organizer of Programming Languages Mentoring Workshop (PLMW) at POPL 2019 Judge for Student Research Competition at SPLASH 2019 His work on Refinement Kinds (with Luís Caires) explores type-safe meta-programming by extending refinement types to the kind level. Articles highlight his contributions to session type theory, type systems for concurrency, and formal verification of channel-based communication. Scientific Awards Distinguished Reviewer Award (ESOP 2022) He has served on program committees for OOPSLA, ICFP, ESOP, and CONCUR, and contributed to foundational work in session types and linear logic. Projects include GOLEM (funded research) and Featherweight Go (formalization of Go's concurrency model).

Peisen Yaoمشاهده پروفایل

پژوهشگر

• Program Analysis and Verification
• Program Synthesis and Optimizations
• Logic and Automated Reasoning
• +۲ مورد دیگر

Peisen Yao is an academic researcher affiliated with Zhejiang University in China. His work spans programming languages, software engineering, and cybersecurity, with a focus on developing techniques to enhance software security, usability, and performance. He actively contributes to premier conferences as a committee member (e.g., PLDI, ICSE, ASE, ISSTA, OOPSLA, SAS). Research Focus: Yao's research integrates program analysis, verification, synthesis, and optimization. Key areas include: Advanced static analysis for security vulnerabilities (e.g., buffer overflows, divide-by-zero errors) Efficient symbolic abstraction and SMT solver testing Context-sensitive program analysis using formal language theory Automated invariant generation and code synthesis Publication Trends: His 15 most recent articles (2021–2025) emphasize scalable program analysis techniques, security validation, and practical tools for industry applications. Common themes include static analysis optimizations, formal verification, and novel testing methodologies for complex systems.

• Hardware Design
• FPGA Programming
• Parallel Computing
• +۵ مورد دیگر

Satnam Singh is a Professor at Newcastle University's School of Electrical and Electronic Engineering, UK. With a research career spanning over three decades from 1989 to present, Singh has established himself as a leading expert in hardware design, FPGA programming, and parallel computing systems. His research interests focus on hardware-software co-design , reconfigurable computing , and functional programming applications for hardware design. Singh has pioneered work in using functional languages like Haskell for hardware description and verification, particularly through his contributions to the Lava hardware description language. His work bridges theoretical computer science with practical hardware implementation challenges. Analysis of his publication history reveals a clear evolution from early work on formal verification and FPGA design in the 1990s, through substantial contributions to parallel programming models in the 2000s, to more recent applications of machine learning techniques in diverse domains including cheminformatics and sensory systems. His 2022-2025 publications demonstrate continued innovation in specialized processor programming, AI applications for olfactory systems, and health hazard classification using deep learning. Singh has maintained extensive collaborations throughout his career, notably with Krishna R. Pattipati (15 joint publications), Anuradha Kodali (8 publications), and David J. Greaves (5 publications), reflecting his ability to bridge theoretical computer science with practical engineering applications. His work spans multiple prestigious venues including FPGA, FCCM, ICFP, and IEEE Transactions on Systems, Man, and Cybernetics, demonstrating both theoretical depth and practical impact across computer architecture, programming languages, and applied machine learning domains.

Eric Medvetمشاهده پروفایل

دانشیار

• Evolutionary Computation
• Machine Learning
• Grammatical Evolution
• +۳ مورد دیگر

Eric Medvet is an Associate Professor of Computer Engineering at the Department of Engineering and Architecture (DIA), University of Trieste, Italy. He leads the Evolutionary Robotics and Artificial Life Lab and co-leads the Machine Learning Lab. His research focuses on Evolutionary Computation, Machine Learning, and their applications to robotics, including Grammatical Evolution, Genetic Programming, and soft robotics. He received the Google Faculty Research Award 2019 for a project on modular soft robots and co-authored a best paper at EuroGP 2024. His recent work emphasizes interpretable control policies, quality-diversity optimization, and evolutionary learning of formal specifications. Medvet teaches advanced courses on machine learning, evolutionary robotics, and programming, consistently updating curricula to reflect cutting-edge research. His labs are hubs for interdisciplinary projects, blending theory with practical implementations in robotics and AI. Research Interests: Medvet’s research spans evolutionary algorithms applied to robotics, with a focus on modular systems. He explores how genetic programming and grammatical evolution can optimize robotic designs and controllers. His work on ‘totipotent neural controllers’ and ‘body-brain co-evolution’ exemplifies efforts to create adaptable, specialized robots. He also investigates formal methods (e.g., STL specifications) for system validation and interpretable AI models. Recent trends in his publications reflect a shift toward practical applications, such as wearable movement analysis and sim-to-real transfer in robotics. Awards: Google Faculty Research Award 2019, EuroGP 2024 Best Paper Award Labs: Evolutionary Robotics and Artificial Life Lab, Machine Learning Lab Teaching: Courses include Advanced Programming, Introduction to Machine Learning, and Evolutionary Robotics, with a focus on Java and practical software development. Medvet’s approach integrates theoretical rigor with hands-on experimentation, emphasizing open-source tools like JGEA and 2D-VSR-Sim. His work bridges computational intelligence and real-world robotics challenges, driving innovation in both fields.

• Software Architecture
• Domain-Specific Languages
• Model-Driven Software Development
• +۳ مورد دیگر

Dr. Michael Szvetits is a Lecturer and Researcher at the Institute of Computer Sciences at the University of Applied Sciences Wiener Neustadt. He holds a PhD in Computer Science from the University of Vienna (2019), an MSc in Computer Science (2012), and a BSc in Information Technology (2010), all from the University of Applied Sciences Wiener Neustadt. His research focuses on software architecture, domain-specific languages, model-driven software development, functional programming, logic programming, and compiler construction. He has contributed to projects such as 'Care about Care' (C^C), which aims to enhance home care through ICT solutions, and 'CARU cares,' which integrates emergency call systems with care documentation tools. His publications span topics like runtime event analysis, model-driven engineering, and software architecture decisions. He collaborates on initiatives funded by the FFG and Active Assisted Living Programme. Dr. Szvetits is actively involved in research projects targeting healthcare technology, software systems optimization, and innovation in assistive living solutions.

Sándor Darányiمشاهده پروفایل

استاد

• Digital Libraries
• Information Retrieval
• Digital Preservation
• +۵ مورد دیگر

Sándor Darányi is a Professor at the Swedish School of Library and Information Science, University of Borås (since 2011), with a career spanning over four decades in information science, digital libraries, and cultural heritage preservation. He also holds an Honorary Professorship at Szeged University, Hungary. His research focuses on advanced access to digital libraries, automatic indexing, information visualization, digital preservation, narrative genomics, and quantum interaction models for semantics. Education: Candidate of Science (CSc) in Ethnography, Hungarian Academy of Sciences (1994) PhD in Information Science, Eötvös Loránd University (1989) MA in Library and Information Science, Eötvös Loránd University (1985) MSc in Agricultural Sciences, University of Agriculture (1975) Research Interests: Darányi’s work bridges computational methods with cultural studies, including: - Formalization of folk narratives for big data analysis - Quantum-inspired models of semantic change - Haptic interfaces for accessibility in museums - Evolving semantics in digital ecosystems - Cultural heritage digitization projects Professional Activities: Editorial Board Member of Journal of Information Science Education Organized major conferences such as SEMANTiCS, IC-ININFO, and AMICUS workshops Supervised doctoral students in computer science and information studies Co-developed the PERICLES project on digital preservation Labs/Teams: His research groups have pioneered projects like the MuseIT inclusive museum initiative and the SHAMAN digital preservation framework, leveraging high-performance computing and cloud technologies.

• Compiler Design
• Static Analysis
• Programming Languages
• +۵ مورد دیگر

Michael Petter is a faculty member at the Technische Universität München (TUM), affiliated with the School of Computer Science II (Informatik 2) and the Department of Languages and Description Structures in Computer Science. He specializes in compiler design, static analysis, and formal verification, with a focus on developing tools like the Goblint framework for multi-threaded C programs. His teaching spans courses such as Compiler Construction, Program Optimization, and Functional Programming, reflecting his expertise in programming languages and software engineering. His research interests include static analysis techniques, concurrency control, and abstract interpretation frameworks. He has contributed to advancements in flow-sensitive analysis, context-sensitivity management, and precision recovery in program analysis. Recent work emphasizes improving static analysis tools for industrial benchmarks and enhancing their usability through incremental methods. Petter’s publications highlight innovations in numerical abstract domains (e.g., octagons), non-local jump misuse detection, and thread-modular analysis for multi-threaded systems. His involvement in projects like the DFG Research Training Group ConVeY underscores his commitment to advancing continuous verification in cyber-physical systems. He advises thesis projects on topics like quantum computing at compile time and program synthesis, fostering interdisciplinary collaboration. While actively engaged in academic events and editorial roles, he maintains a lab focused on cutting-edge compiler and static analysis research.

• Deep Neural Networks
• Compiler Design
• Program Verification
• +۵ مورد دیگر

Thirimadura Charith Yasendra Mendis serves as an Assistant Professor at the University of Illinois Urbana-Champaign with dual appointments in the Siebel School of Computing and Data Science and the Department of Electrical and Computer Engineering. He maintains a strong affiliation with the Coordinated Science Lab, where he conducts interdisciplinary research bridging computer architecture, compilers, and artificial intelligence systems. His research program centers on deep neural networks, compiler design, and program verification, with significant contributions to soundness verification of DNN certifiers, domain-specific language development for neural network certification, and hardware-aware compiler optimizations. His work in parallel computing and graph neural networks specifically targets efficiency bottlenecks in AI infrastructure through novel vectorization and level parallelism techniques. Recent 2025 publications reveal a cohesive research trajectory focused on enhancing AI system reliability through formal methods and compiler innovation. Key themes include automated verification frameworks for tensor operations, declarative approaches to neural network certification, and GPU-optimized code generation for sparse attention mechanisms in transformer architectures—collectively advancing trustworthy AI deployment. Dr. Mendis has earned two prestigious national awards: DARPA Young Faculty Award (2024) NSF CAREER Award (2024) These competitive grants fund his research program investigating foundational aspects of AI safety and compiler technology, likely supporting graduate student mentorship in systems and programming languages research. Within the Coordinated Science Lab ecosystem, Mendis collaborates with cross-disciplinary teams on projects spanning hardware acceleration, programming language design, and neural network verification—leveraging this environment to drive innovation in computing systems reliability and performance.

Carina Soledad González Gonzálezمشاهده پروفایل

استاد

• Artificial Intelligence in Education
• Human-Computer Interaction
• Educational Technology
• +۱۲ مورد دیگر

Carina Soledad González González es una Profesora en la Universidad de La Laguna, España, con un doctorado en Informática (2001) enfocado en Sistemas Tutor Inteligentes para educación especial. Líder del Grupo de Investigación i-TED (Interacción, TIC y Educación) y actual Presidente de la Red Universitaria de Campus Virtuales, ha destacado en la aplicación de inteligencia artificial a la educación, adaptación de interfaces y gamificación educativa. Doctora en Informática (ULL, 2001) Líder del Grupo i-TED Presidente de Red Universitaria de Campus Virtuales Directora de Cátedra de Cultura Digital Interactiva Su investigación abarca: Integración de perspectiva de género en tecnología Desarrollo de MOOCs colaborativos y gamificados Plataformas de rehabilitación física y cognitiva (TANGO:H) Instrumentos de evaluación emocional para niños (EMODIANA) Sistemas recomendadores basados en conocimiento y reputación Tendencias de investigación en artículos recientes: Enfoques sistemáticos en políticas europeas de género en STEM Aplicación de gamificación en materiales educativos Adaptación de tecnologías para educación inclusiva Desarrollo de plataformas autónomas de aprendizaje Innovación en sistemas de recomendación para e-learning Actualmente trabaja en: Consolidación de redes internacionales de campus virtuales Desarrollo de ecosistemas tecnológicos interoperables Formación del profesorado en tecnologías emergentes Evaluación de calidad en educación virtual