Prof. Dr. Hans Michael Gerndt is a leading academic at the Technical University of Munich (TUM) , affiliated with the TUM School of Computation, Information and Technology . Since 2000, he has headed the Parallel Computer Architecture group within the Faculty of Computer Science, focusing on tools for optimizing parallel supercomputers and cloud applications. His research emphasizes automatic performance analysis and optimization , particularly through the Periscope Tuning Framework . He has contributed to energy efficiency in computing systems, autoscaling mechanisms for cloud environments, and multi-aspect tuning frameworks for HPC applications. His work bridges theoretical advancements with practical tools for computational efficiency. Key publications include studies on energy tuning (2018), autoscaling measurement tools (2018), and MIMD-parallelization for supercomputing (1987). Notable awards include the Virtual Institute for High Productivity Supercomputing (VI-HPS) admission (2009) and Eclipse Innovation Award (2005) .
Gagandeep Singh is a tenure-track Assistant Professor in the Department of Computer Science at the University of Illinois Urbana-Champaign (UIUC), with affiliations at VMware Research. His research focuses on integrating Machine Learning , Formal Methods , and Systems to build intelligent systems with formal safety guarantees. Programming Languages Formal Methods Artificial Intelligence Machine Learning Systems His publications (e.g., PRIMA , Incremental Verification of Neural Networks ) emphasize scalable neural network certification, abstract interpretation, and automatic differentiation. Work includes domain-specific languages for verification and convex hull approximations to improve precision. Scientific recognition includes the NEAT (Notable Experience Track Artifact) award for ConstraintFlow . He has served on program committees and as session chairs for conferences like PLDI, POPL, and SPLASH. He has no listed advisees or grants in the provided texts but maintains an active role in research leadership through committee memberships and invited talks.
Professor Ekaterina Lapshinova-Koltunski serves as Full Professor (W3) in Multilingual Technical Specialized Communication at the University of Hildesheim since October 2022. She is affiliated with the Institute for Translation Studies & Specialized Communication within Department 3: Linguistics and Information Sciences. Previously, she held positions as Akademische Oberrätin (equivalent to Associate Professor) at Saarland University (2017-2022) and served as Interim Professor at the University of Hildesheim (2020-2021). Her educational background includes: Habilitation in Linguistics, Translation Studies and Corpus Linguistics (2016) from Saarland University PhD in Computational Linguistics (2011) from University of Stuttgart Postgraduate studies in Language Data Processing (2003-2006) from Georg August University of Göttingen Diploma in Translation, Interpreting and Intercultural Communication (1997-2002) from Volgograd State University Professor Lapshinova-Koltunski's research focuses on the intersection of translation studies, corpus linguistics, and artificial intelligence, with particular emphasis on machine translation, plain language communication, and multilingual technical communication. Her work bridges theoretical linguistics with practical applications in healthcare communication, accessibility, and translation technology. She has made significant contributions to understanding cohesion and coherence in translation, cross-linguistic variation, and the cognitive aspects of translation processes. Her recent publications (2024-2025) demonstrate a strong shift toward AI applications in translation, particularly in health communication and plain language translation. These works examine how large language models can support the creation of accessible medical information, analyze gender representation in machine translation, and develop practical frameworks for integrating AI tools into editorial workflows. Her research shows increasing focus on practical applications of translation technology to address real-world communication challenges, especially in healthcare contexts. She actively serves as a reviewer for major funding organizations including DFG and Research Foundation – Flanders, and for numerous prestigious journals and conferences in computational linguistics and translation studies. Her current grant portfolio includes: Project B7 'Translation as Rational Communication' in SFB1102 (2022-2026) 'AI-supported health communication in Plain language' funded by the Ministry of Science and Culture of Lower Saxony (May 2024-August 2025) 'Use of AI tools in intralingual translation of health communication' with Wort & Bild Verlag (October 2023-April 2024) 'Data triangulation in translation process research' startup grant from University of Hildesheim (August 2023-January 2024) Professor Lapshinova-Koltunski holds multiple administrative roles including membership in various examination committees for master's programs in International Communication and Translation, Barrier-free Communication, and Technical Communication, as well as serving on the Faculty Council and Research Committee for Department 3.
Dr. Martin Schmidt-Daffy is a Researcher in the Division of School and Teaching Research at the Department of Education and Psychology, Freie Universität Berlin. He has been a permanent scientific staff member since 2018, following prior roles as a specialized teaching instructor and researcher at the same institution and at Technische Universität Berlin. His work bridges educational psychology and neuroergonomics, focusing on motivation, self-regulated learning, and pedagogical diagnostics. PhD in Philosophy (Psychology), Freie Universität Berlin, 2006 Diplom in Psychology, Technische Universität Berlin, 1999 His research centers on learning and teaching motivation , particularly how self-determined motivation can be fostered in teacher training. He investigates pedagogical diagnostics , feedback mechanisms , and learning progress assessment . A significant portion of his earlier work explores driver behavior , focusing on goal conflicts , fear and anxiety , and threat detection in traffic contexts using psychophysiological measures. The 15 most recent publications reflect a shift from neuroergonomics and emotion research toward educational applications. Early works focus on cognitive and emotional processing in driving, threat detection, and facial expression recognition. More recent articles emphasize data-based decision-making and motivational interventions in teacher education, indicating an applied focus on improving teaching practices through psychological research. He has held various institutional roles, including membership in the Dahlem School of Education council and serving as an accreditation officer for educational science modules in the teacher training master's program. He has supervised numerous theses in psychology and human factors. Project: 'Development of learning-accompanying online exams to promote self-regulated competence acquisition in teacher education' (funded by Stifterverband under 'Prüfung hoch III Drei') Previously led internal and DAAD-funded research projects on driver behavior, goal conflicts, and emotional strain Dr. Schmidt-Daffy teaches courses on promoting learning and teaching motivation , pedagogical diagnostics , and feedback and evaluation for both Bachelor's and Master's students in teacher education. His teaching spans from 2011 to 2022, showing sustained engagement in academic instruction.
Anna Mittermair is a researcher at the Chair of Computer Architecture & Parallel Systems at the Technical University of Munich . She is actively involved in teaching and research related to High-Performance Computing (HPC) systems. Teaching Roles : Lab Course Computer Architecture (IN0005), Aspects of Low-Level Programming for Games Development (IN0035) Current Projects : SEANERGYS (EuroHPC), PlasmaPEPS, OpenCUBE, ScalNEXT, and others focused on HPC, quantum computing, and AI hardware. Research Focus : Her work emphasizes automatic distributed memory parallelization and communication optimization for CPUs and GPUs , particularly in ocean models and HPC infrastructure. She supervises thesis topics centered on latency hiding schemes and code block order analysis for performance optimization. Collaborations & Infrastructure : Anna contributes to software projects like QMPI , MOVE-II , and SWEET , leveraging hardware such as CAPS Cloud and HimMUC . She is also affiliated with organizations like the MPI Forum Virtual Institute and Eurolab4HPC .
David Monniaux is a senior researcher (directeur de recherche) at CNRS and an adjunct professor at École polytechnique. He works at VERIMAG, a computer science laboratory jointly operated by CNRS and the University of Grenoble. Dr. Monniaux obtained his PhD in 2001 from Université Paris Dauphine under Professor Patrick Cousot, with a dissertation on the static analysis of probabilistic programs by abstract interpretation. He later earned his habilitation in computer science in 2009 from Université Joseph Fourier, Grenoble, and also holds an agrégation in mathematics. Monniaux's research focuses on program verification, with particular emphasis on proving software correctness. His work spans theoretical foundations in computability theory and practical applications in safety-critical systems. He has made significant contributions to abstract interpretation, static analysis, and the verification of numerical properties in programs. His research bridges computer science theory with practical engineering challenges, particularly in the context of critical embedded systems where software failures can have severe consequences. His work connects to diverse fields including game theory, algebra, and convex optimization. His recent publications demonstrate a strong focus on improving the precision and efficiency of static analysis techniques. Key themes include polyhedral approximation, program analysis with local policy iteration, abstraction of arrays and maps, synthesis of ranking functions, and computing worst-case execution times. These works collectively advance the field of program verification by addressing challenges in handling nonlinear constraints, branching, and complex data structures while maintaining computational feasibility. Monniaux has supervised several students including Julien Henry, Alexis Fouilhé, George (Egor) Karpenkov, and Alexandre Maréchal (now at LIP6), with current students Hang Yu and Valentin Touzeau. He has led significant research projects including VERASCO (2012-2015), which aimed at integrating a static analyzer into the CompCert certified compiler, and STATOR (2012-2017), an ERC starting investigator grant exploring advanced techniques for automatic inference of program invariants. At VERIMAG, Monniaux is part of a vibrant research community focused on critical systems. His work connects with broader efforts in formal methods, with applications in aviation, automotive systems, and other safety-critical domains where software reliability is paramount.
Xavier Rival serves as Research Director at INRIA Paris and Director of the Computer Science Department at École Normale Supérieure (ENS) in Paris, which is part of PSL University. He also holds the position of Adjunct Professor at ENS/PSL. Previously from 2012 to 2024, he led the ANTIQUE (ANalyse staTIQUE) research group at INRIA Paris located at ENS Paris. His research focuses on abstract interpretation and software verification through static analysis, with particular emphasis on symbolic abstractions including trace partitioning abstraction, shape analysis, separation logic, and memory abstract domains. He has been instrumental in the design, implementation, and industrial transfer of the Astrée analyzer, a static analysis tool capable of verifying safety properties for industrial-scale safety-critical software. Currently, he leads the MemCAD ERC project aimed at developing a library of abstract domains for describing complex memory states. Rival's publication record demonstrates consistent contributions to the field of programming languages and static analysis, with his most recent work exploring probabilistic program verification, shape analysis for complex data structures, and applications to embedded systems. His research bridges theoretical foundations with practical applications, particularly in safety-critical domains. ERC Starting Grant recipient (MemCAD project) Author of foundational work on Astrée static analyzer Co-author of textbook on Introduction to Static Analysis published by MIT Press Active program committee member for major conferences including POPL, PLDI, and SAS Rival has supervised numerous PhD students throughout his career, including Tie Cheng (now CEO of MatrixLead), Arlen Cox, Huisong Li, and Jiangchao Liu. His laboratory has received research funding from multiple sources including ANR projects (VeriAMOS, VerAsCo, AnaStaSec) and the ERC Starting Grant for MemCAD. The MemCAD project has led to the development of analysis tools applicable to spreadsheet applications through the startup MatrixLead, where Rival serves as Scientific Adviser.
Dr. Mahsa Varshosaz is an Associate Professor in the Software Quality Research group at the IT University of Copenhagen , Denmark. Her work bridges theoretical and practical aspects of software quality assurance, with a focus on model-based testing , formal verification , and automatic program repair for complex systems. Her research spans software product lines , autonomous systems , and cyber-physical systems , including projects like REMARO (testing of underwater robotic systems) and Linux kernel program repair. She employs formal methods to address challenges in system safety, reliability, and variability. Selected publications reveal a trajectory in hybrid testing techniques combining symbolic execution and reinforcement learning, safety analysis of autonomous underwater vehicles, and formal verification of probabilistic systems. Her work intersects software testing formal methods AI-based verification robotics safety product line engineering concurrent system analysis . She actively contributes to academia as Co-Chair of Doctoral Symposium in SPLC conferences Editorial Board member of Science of Computer Programming Program Committee member across testing/verification workshops like A-MOST, ITEQS, and ECOOP . Her 2023 invited talk series at Trustworthy Autonomous Systems Verifiability Node and participation in Dagstuhl/Shonan seminars highlight her influence in unifying formal methods with AI-based autonomous systems . Projects include REMARO (co-coordinator) and INSIGHT.
Krishna Narasimhan is a Researcher at the Software Technology Group within Technical University of Darmstadt, Germany, focusing on developer struggles with cryptographic APIs and secure programming practices. He plays a key role in the CogniCrypt framework development, an Eclipse Foundation project designed to help developers use crypto APIs securely. His research spans secure programming, programming languages, static analysis, source code transformation, and domain-specific languages. His work demonstrates a clear progression from foundational research in program transformation during his PhD to practical applications in API security and developer tooling. Recent work shows growing interest in AI-assisted development and machine learning bug detection. His publication record reveals consistent contributions to major software engineering venues (ECOOP, SPLASH, ICSE), with recent papers examining trustworthy AI software development, misuse-resilient APIs, and code generation from test specifications. The research shows strong emphasis on practical tools that address real-world developer challenges rather than purely theoretical contributions. Narasimhan maintains active service in the research community as a committee member for artifact evaluation at numerous conferences including ECOOP, PLDI, ISSTA, and SPLASH, demonstrating recognition of his expertise in experimental methodology and reproducibility. His career path includes industry experience as a Language Engineer at Itemis developing Mbeddr (an embedded DSL platform), followed by return to academia where he now bridges practical tool development with academic research. His PhD work focused on semi-automatic tools for source code evolution tasks like copy-paste abstraction and data representation migration.
Jonas Norlinder is a researcher affiliated with Uppsala University in Sweden, specializing in memory management and virtual machine design . He actively contributes to academic conferences such as ECOOP, SPLASH, and PLDI, serving on committees for artifact evaluation and extended review processes.
Martina Maggio is a Professor at the Department of Computer Science , Saarland University (since March 2020) and holds a 20% position at the Department of Automatic Control , Lund University (since 2023). Her research bridges control theory with software engineering to address predictability in computing systems. PhD : Politecnico di Milano (completed with work on control-theoretical tools for computing systems) Visiting Graduate Student : MIT CSAIL (collaborated on Self-Aware Computing project) Her research focuses on: Control theory for resource allocation in cloud infrastructures and embedded systems Formal verification of event-triggered systems and deadline misses Robustness of cyber-physical systems under computational faults Automated methodologies for runtime adaptation in software Timing requirements in big data applications Security vulnerabilities in control systems Key article trends include: control-theoretic approaches to computing systems, stochastic modeling of deadline misses, formal verification of timing constraints, and security-aware control algorithms . Scientific recognition: Co-authored paper selected as Most Influential Paper at SEAMS 2025 Best Paper Award at ECRTS 2021 ACM SIGSOFT Distinguished Paper Award (FSE 2020) Outstanding Reviewer (ICPE 2020) Mentorship includes supervising PhD candidates (e.g., Clara Rubeck, Robert Pietsch) and serving as an academic advisor for industry collaborations (e.g., with Bosch Corporate Research). She also contributes to open-source tool development (WeaklyHard.jl) and has held leadership roles like Program Co-Chair for ICCPS 2020.
Marc Seidel, M.Sc., is a Research Assistant at the Institute for Systems Theory and Automatic Control , University of Stuttgart. His work bridges theoretical and applied control systems research, focusing on autonomous mobility and networked control. Research Interests include: Controller design for real-time systems under weakly-hard constraints Switched systems with graph-constrained switching Networked Control Systems Event-triggered consensus schemes Orientation estimation using inertial sensors Publications reflect expertise in autonomous e-scooter control, multi-agent coordination, and sensor-based safety filters. Key themes: control theory, robotics, and sustainable transportation. Teaching Roles at the University of Stuttgart include: SS 2024: Formal Methods in Control SS 2022-SS 2023: Concepts of Automatic Control SS 2022: Nonlinear Dynamics WS 2021/22-WS 2025/26: Lab and project courses Academic Background : M.Sc. in Engineering Cybernetics (University of Stuttgart, 2021), thesis on periodic event-triggered consensus with cooperation from Prof. Dimos V. Dimarogonas (KTH Stockholm) B.Sc. in Engineering Cybernetics (University of Stuttgart, 2015-2019), thesis on trajectory tracking control Professional Engagements : 01/2025-03/2025: Research stay at Department of Automatic Control, Lund University 03/2021-08/2021: Internship at Robert Bosch GmbH (Renningen, Germany) 08/2020-11/2020: Study abroad at KTH Stockholm for master's thesis Projects : Lead responsibility in the Autonomous E-Scooter initiative, integrating control theory into sustainable urban mobility solutions.
Shigehiko Schamoni is a Lecturer and Compute Lab Manager at Heidelberg University's Institute of Computer Engineering (ZITI), where he oversees scientific computing infrastructure and teaches computer science courses. He is completing his PhD under Prof. Stefan Riezler in the Statistical NLP group. His dual roles bridge technical management and academic instruction, with teaching responsibilities spanning undergraduate and graduate courses since 2011. Research Focus: Schamoni's work intersects clinical AI and natural language processing, with emphasis on: Machine learning for medical applications (sepsis prediction, clinical validity) Speech translation and automatic speech recognition Cross-lingual information retrieval Data augmentation techniques Multimodal machine learning His 15 most recent publications (2016-2024) demonstrate strong thematic clustering: 47% focus on medical AI (primarily sepsis prediction and clinical data validation), while 53% address NLP challenges (speech translation, ASR, and multimodal systems). This bifurcation reflects consistent collaboration with medical researchers alongside core NLP innovation. Teaching Experience includes instruction across 10+ courses since 2011, such as: Graduate courses: "Tools – Werkzeuge für effizientes wissenschaftliches Arbeiten" (2023-2024) Undergraduate courses: "Einführung in die Nutzung computerlinguistischer Ressourcen" (2021-2022) Programming courses: "Advanced Programming" and "Parallel Programming Paradigms" (2012-2015) He maintains affiliations with both the ZITI infrastructure team and Statistical NLP research group.
Dr. rer. nat. Maximilian Gelbrecht is a postdoctoral researcher at the Earth System Modelling Group under Prof. Niklas Boers at the Technical University of Munich (TUM School of Engineering and Design). He is also a guest researcher at the Potsdam Institute for Climate Impact Research. His work bridges process-based and data-driven approaches in climate modeling. Research Focus: Scientific machine learning, GPU programming, and automatic differentiation applied to atmospheric dynamics and chaotic systems Technical Expertise: Climate model optimization, high-performance computing, data assimilation
Martin Eberlein is a Doctoral Researcher and Ph.D. candidate in the Software Engineering group at Humboldt University of Berlin, Germany, working under Prof. Lars Grunske. Previously, he collaborated with Prof. Andreas Zeller's research group at CISPA Helmholtz Center for Information Security. His research focuses on automated software engineering, particularly software testing, vulnerability detection, and fuzzing. He is currently part of the EMPEROR project, which aims to automatically generate explanations for program behaviors, especially failures. Dr. Eberlein has developed notable tools including Avicenna (for explaining why programs fail) and EvoGFuzz (an evolutionary, grammar-based fuzzer). Education: 2022-Present: Dr. rer. nat. (PhD), Computer Science, Humboldt-Universität zu Berlin 2020-2022: Master of Science (M.Sc.), Computer Science, Humboldt-Universität zu Berlin (Final Grade: 1.0) 2015-2020: Bachelor of Science (B.Sc.), Computer Science, Humboldt-Universität zu Berlin (Final Grade: 1.3) His publications demonstrate innovative approaches to software testing and debugging, with emphasis on explaining program failures through machine learning. Recent work includes 'Which Inputs Trigger My Patch?' (APR'2025) and 'jAST' (FSE'2025), showing trends toward automated explanation of software behavior and program analysis tools. Scientific Awards: Black Shirt from HU-Berlin research group (2025) €900k initial funding for InputLab startup Dr. Eberlein serves on program committees for FSE 2025 (Artifact Evaluation Track) and ISSTA 2025 (Tools Demonstrations Track). He organizes and assists with teaching courses at HU Berlin, particularly in Software Engineering II and Compiler Construction. As co-founder of InputLab, he bridges academic research with practical applications in software testing for government and business formats. He maintains active research collaborations through GitHub, his blog, and participation in major software engineering conferences worldwide.
