Christian Haubelt is a Professor at the Institute of Computer and Network Engineering, School of Engineering, University of Rostock, Germany. He is actively engaged in research and teaching in the areas of embedded and cyber-physical systems, smart implants, and IoT. His work is supported by multiple national and international projects including ELAINE (SFB 1270), SmILE (EU), 6G-Health (BMBF), and GenerIoT (BMBF). His research interests include: Embedded and Cyber-Physical Systems Smart Sensors and Smart Implants System-Level Design Methodologies SystemC-based Modeling and Verification Design Space Exploration and Multi-Objective Optimization Industrial Internet of Things and 6G for Healthcare His recent publications focus on real-time communication protocols, 5G/6G localization, smart implants, and secure IoT systems. Trends show a strong emphasis on integrating embedded systems with medical and industrial applications, particularly leveraging TSN, MQTT-SN, and OPC UA for reliable and secure communication. His work bridges theoretical modeling with practical implementation in safety-critical domains. Christian Haubelt has supervised multiple researchers including Michael Nast, Benjamin Rother, Nico Kalis, and Nico Graumüller. He leads several funded research projects such as ELAINE, SmILE, 6G-Health, and SUSTAIN, which focus on smart implants, secure IoT, and next-generation medical systems. These projects involve collaboration with DFG, EU, and BMBF. He is involved in the following research labs and teams: Embedded Systems and Cyber-Physical Systems Group Smart Implants Research Team (SmILE, ELAINE) 6G-Health Localization Team Industrial IoT Security (SUSTAIN, CargoAssist)
Simone Ferlin is an Adjunct Senior Lecturer at Karlstad University working with 5G and Internet evolution. She completed her PhD in computer science in 2017 at the Simula Research Lab and Universitetet i Oslo under the supervision of Dr. Ozgu Alay and Prof. Michael Welzl. Her PhD dissertation focused on increasing robustness in multipath transport with MPTCP. Dr. Ferlin's educational background includes a PhD in Computer Science from the Simula Research Lab and Universitetet i Oslo (2017). Her doctoral research centered on enhancing robustness in multipath transport protocols, specifically focusing on MPTCP (Multipath TCP). She also completed undergraduate work that contributed to a book project with Prof. Friedrich Oehme on electronics and circuit technology. Dr. Ferlin's research spans multiple domains at the intersection of networking, systems, and performance engineering. Her primary interests include network and system measurements, performance analysis, security, and congestion control. She investigates how networks like the Internet evolve, examining technology development, adoption patterns, and their impacts on various entities. Additionally, she explores ways to harmonize security and privacy while making them more usable and assessable. Her work particularly focuses on transport layer and multipath transport protocols, examining their performance and security aspects. She also investigates application and transport layer performance, automation, and monitoring. Her research extends to network programming in both Linux kernel and user space, mobile broadband networks from 2G to 5G, and their intersection with the Internet. She is deeply engaged in observability, distributed and system performance monitoring, and automation. Analysis of Dr. Ferlin's recent publications reveals a strong focus on next-generation networking technologies. Her work spans multiple domains including 5G/6G networks, transport protocols (particularly QUIC and MPTCP), network virtualization, container orchestration, and the application of machine learning to networking problems. She has increasingly incorporated large language models into network configuration and automation research. Her publications demonstrate a consistent emphasis on performance measurement, optimization, and security across diverse networking environments from the edge to the cloud. Dr. Ferlin has received notable recognition for her research contributions: Best paper award at IEEE ICIN'21 for 'Learning-based Incast Performance Inference in Software-Defined Data Centers' Applied Networking Research Prize (ANRP)'25 winner for 'NetConfEval: Can LLMs Facilitate Network Configuration?' Dr. Ferlin is actively involved in mentoring the next generation of networking researchers. She has co-supervised numerous Master's and PhD students across multiple institutions including Karlstad University, KTH, TU Berlin, University of Oslo, and universities in Brazil. Her students have worked on diverse topics including NAT64 performance comparison, system tracing visualization, network observability, ML applications to multipath transport, FEC integration with QUIC, high-performance networking for 5G, congestion control, shared bottleneck detection, multipath IoT applications, and container runtime performance. She is also involved in several significant research projects including Vinnova's SEMLA (Securing Enterprises via Machine-Learning-based Automation), Horizon Europe's CODECO (Cognitive Decentralised Edge Cloud Orchestration), and the Knowledge Foundation of Sweden's DRIVE (Data-driven Latency-Sensitive Mobile Services for a Digitized Society). Dr. Ferlin serves as Workshop Chair for ACM SIGCOMM '25, is a member of the ACM/IRTF Applied Networking Research Workshop (ANRW) steering committee, and co-chairs the Internet Congestion Control Research Group (ICCRG) at the IRTF. She previously served as Associate Technical Editor for IEEE Communications Magazine and has been active on numerous program committees for major networking conferences including SIGCOMM, CoNEXT, IMC, and PAM.
Prof. Tegawendé F. Bissyandé is a Chief Scientist in the Professor category at the Interdisciplinary Centre for Security, Reliability and Trust (SnT) at the University of Luxembourg. He holds the prestigious position of ERC Fellow and serves as Principal Investigator of the NATURAL project focused on Artificial Intelligence for Program Repair. His research spans software engineering, cybersecurity, and artificial intelligence, with particular emphasis on applying machine learning techniques to software development and security challenges. Dr. Bissyandé's research interests include: Software Debugging (especially bug localization and program repair) Software Security (especially malware detection and analysis) Code Search (both free-form and semantic code-to-code) Machine Learning and Natural Language Processing for software engineering Cyber-security applications in mobile and cloud environments His recent work demonstrates a strong focus on leveraging Large Language Models (LLMs) for various software engineering tasks. Analysis of his 15 most recent publications reveals several key trends: extensive application of LLMs to program repair and code generation; innovative approaches to Android security and malware detection; development of novel techniques for code search and understanding; and exploration of the intersection between natural language processing and software engineering. His research increasingly bridges theoretical software engineering with practical applications in mobile security and developer productivity tools, with a significant portion of his work focusing on Android ecosystem security and program repair technologies. Dr. Bissyandé has received numerous prestigious awards throughout his career: APSEC Best ERA Paper Award (2018) for 'LSRepair: Live Search of Fix Ingredients for Automated Program Repair' IPSJ SIG SE Excellent Research Award (2018) for 'FaCOY: a Code-to-Code Search Engine' FOSS Impact Paper Award (2018) for 'Characterizing Deprecated Android APIs' SANER Best ERA Paper Award (2016) for 'Parameter Values of Android APIs: A Preliminary Study on 100,000 Apps' ASE Best Paper Award (2012) for 'Diagnosys: automatic generation of a debugging interface to the Linux kernel' As an active member of the software engineering research community, Dr. Bissyandé serves on program committees for major conferences including ICSE, ASE, and ISSTA, and has been an Area Chair for ICSE 2024. His industry partnerships include significant collaborations with BGL BNP Paribas (since January 2019), Luxembourg Stock Exchange (since January 2018), and Paul Wurth (January 2015 to 2018), demonstrating the practical impact of his research. He leads the SerVAL lab at SnT, which focuses on software validation and analysis, with particular expertise in mobile security and program repair technologies, and actively mentors PhD candidates through FNR research grants.
Bernhard Heinloth, M.Sc., is affiliated with the Department of Computer Science (INF) at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), specifically within Chair of Computer Science 4 (System Software). His research focuses on system software optimization, kernel tailoring for embedded systems, and dynamic software updates. He has contributed to projects like Luci (dynamic shared object updates), Cocoon (on-demand kernel compilation), and Honey (binary library reduction). Teaching activities include leading exercise sessions for courses such as Betriebsysteme (Operating Systems), Systemnahe Programmierung in C (Low-Level Programming), and Praktikum angewandte Systemsoftwaretechnik (Systems Software Lab). He has advised numerous master's theses on topics ranging from interrupt latency analysis to compiler-based OS optimization. His publications span academic venues like USENIX ATC, PLOS, and SBESC, with a strong emphasis on practical system software engineering. Current work continues exploring compiler-driven system optimizations and real-time kernel performance.
Christian Dietrich is a Professor at Technische Universität Braunschweig, specializing in operating systems, real-time systems, and software dependability. Previously affiliated with Friedrich-Alexander-Universität Erlangen-Nürnberg and Leibniz Universität Hannover, he leads the Systems Research and Architecture (SRA) group. His research focuses on dependable embedded operating systems, fault tolerance, static analysis, and compiler optimization. He has contributed to projects like dOSEK, cHash, and MELF, addressing challenges in real-time scheduling, redundancy reduction, and variability management in system software. Education: PhD in Computer Science from Leibniz Universität Hannover (2019). Research Interests: Embedded systems dependability, real-time OS design, static/dynamic analysis, fault injection, and compiler-driven optimization. His work bridges theory and practice, with applications in automotive and safety-critical systems. Recent Work: Recent articles explore compiler caching efficiency (IRHash), memory management (HyperAlloc), and fault-space pruning for hardware fault injection. His work on cHash reduced redundant compilations by 80%, earning a USENIX ATC Best Paper Award. Awards: ECRTS 2018 Outstanding Paper, RTAS 2015 Best Paper, and multiple teaching accolades. Supervised over 30 theses, including topics like live patching, fault injection frameworks, and stack-sharing mechanisms. Lab/Team: Heads the SRA group, collaborating on projects like AHA (Hardware Abstraction), CLASSY-FI (fault injection), and CADOS (RTOS variability management). Active in conferences like OSDI, EuroSys, and RTSS.
Benedict Herzog is a Researcher at the Bochum Operating Systems and System Software (BOSS) group at Ruhr-Universität Bochum (RUB). Previously, he was part of the Department of Computer Science 4 (Distributed Systems and Operating Systems) at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU). His work focuses on energy-efficient systems, operating systems optimization, and embedded computing. Herzog holds a Master's degree in Computer Science from FAU, where his thesis explored energy demand estimation using artificial neural networks, and a Bachelor's degree in Energy-aware error correction in wireless sensor networks. His research interests span energy-aware computing, system software design, and machine learning applications for optimizing edge and embedded systems. He actively participates in academic activities, serving as a reviewer for conferences like TECS, SBESC, and EMSOFT. Herzog has taught courses such as 'Systemnahe Programmierung in C' and 'Energy-Aware Computing Systems' at FAU, and advised multiple students on topics ranging from interrupt handling overhead to Meltdown/Spectre mitigation impacts. Key technical contributions include frameworks for energy measurement integration (EnergyBudgets), system-call aggregation (AnyCall), and automated OS configuration optimization. His work bridges hardware-software co-design challenges in energy efficiency, with applications in edge computing and real-time systems.
Juliana Alves Pereira is a Professor at the Computer Science Department of the Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Brazil, where she leads the Artificial Intelligence for Software Engineering lab (AISE) as part of the Software Engineering lab (LES). Her academic journey includes a Ph.D. in Software Engineering with distinction (summa cum laude) from Otto-von-Guericke-Universität Magdeburg (OvGU) in Germany (2018), a Master's degree in Computer Science from the Federal University of Minas Gerais (Brazil), and postdoctoral research at the University of Rennes, Inria/IRISA (France). Her research focuses at the intersection of software engineering and artificial intelligence, particularly in automating software engineering through software analysis, machine learning, recommender systems, and meta-heuristic optimization. Dr. Pereira's work explores applications of Machine Learning, Explainability, Transfer Learning, Generative AI, Deep Learning, Natural Language Processing, and Recommender Systems in software quality and human aspects contexts. Her publications demonstrate a consistent focus on empirical software engineering, with significant contributions in code quality analysis, pull request characteristics, exception handling, and performance prediction in configurable systems. Her research shows increasing integration of advanced AI techniques with traditional software engineering practices. Best Dissertation Prize from the School of Computer Science in 2018 (Germany) Dissertationspreis award from OvGU (2018) ACM Best Paper Award from SPLC 2021 ACM Best Paper Award from ICPE 2020 CBSoft Most Influential Paper Award from Brazilian Computer Society (SBC) Dr. Pereira actively supervises master's and doctoral research in the Software Engineering concentration area at PUC-Rio. She has served on Program and Organizing Committees for major international conferences including ICSE, ASE, SANER, MSR, and ICSME. Her laboratory collaborations span national and international research groups, reflecting her significant impact in the software engineering community.
Christian Dietrich is a Professor for Reliable Distributed Systems at Technical University of Braunschweig since 2024, where he heads the Reliable System Software research group within the Institute of Operating Systems and Computer Networks, part of the Faculty of Electrical Engineering, Information Technology, and Physics. He previously held positions at Leibniz Universität Hannover where he completed his distinguished doctoral research. Professor Dietrich's research focuses on operating systems, distributed systems, and reliable systems with particular expertise in memory management, real-time systems, and embedded systems. His work spans both theoretical foundations and practical implementations, with significant contributions to system software reliability and efficiency. His research interests include operating system design, memory management techniques, real-time computing, embedded systems, fault tolerance, and compiler optimizations for system software. Dietrich's recent publications demonstrate a strong focus on memory management innovations (particularly for persistent memory), virtualization techniques, and reliability mechanisms for distributed systems. His work frequently bridges the gap between theoretical computer science and practical system implementation, with many contributions finding their way into production systems. The research shows increasing emphasis on hardware-software co-design and adapting operating systems to modern hardware capabilities. His scientific achievements have been recognized with numerous prestigious awards: USENIX ATC Distinguished Artifact Award (2023) for LLFree USENIX ATC Best Paper Award (2017) for cHash RTAS Best Paper Award (2015) for dOSEK Multiple Outstanding Paper Awards at ECRTS, OSPERT, and ISORC Wissenschaftspreis Hannover (2020, awarded in 2024) Professor Dietrich has secured significant research funding including multiple DFG projects (DI 2840/1-1, DI 2840/2-1) and has been involved in collaborative projects with industry partners. His teaching portfolio includes advanced courses on operating systems, programming languages, and compilers, for which he received teaching excellence awards. He leads an active research group focused on reliable system software with ongoing projects including ParPerOS (Parallel Persistency OS) and ATLAS (Adaptable Thread-Level Address Spaces). The Reliable System Software group maintains strong connections with both academic and industrial partners, contributing to open-source projects and collaborating on cutting-edge research in system software reliability. The group's work has practical impact, with some findings leading to more than 100 accepted patches in the Linux mainline kernel.
Professor Daniel Lohmann leads the Systems Research and Architecture (SRA) group at Leibniz Universität Hannover since 2017, following his role as Associate Professor (Privatdozent) at Friedrich-Alexander-Universität Erlangen-Nürnberg (2009–2016). His work focuses on configurable system software, emphasizing embedded systems, real-time systems, and dependable architectures. Key projects include danceOS (dependability in embedded OS), Sloth (minimal-effort kernels), and AspectC++ (aspect-oriented C++ extension). His research is funded by DFG and addresses challenges in variability management, fault tolerance, and real-time scheduling. Research interests span operating systems design, software product lines, generative programming, and aspect-oriented development. Notable contributions include the CiAO OS family and the Sloth RTOS, leveraging aspect-oriented techniques for flexibility and efficiency. His work on configuration analysis (e.g., static variability in Linux) and fault mitigation (e.g., AN-Codes for soft errors) highlights his expertise in system reliability and optimization. Publications emphasize real-time systems, embedded software, and software engineering, with awards including the Best Paper Award at SPLC 2010 and an Outstanding Paper at RTAS 2017. He supervises theses on system software tailoring, fault tolerance, and industrial software ecosystems. His groups collaborate on invasive computing (SFB/TRR 89) and hardware-aware OS design.
Andreas Ziegler is a Professor at the Department of Computer Science (INF) of Friedrich-Alexander University Erlangen-Nürnberg. His research focuses on system software optimization , particularly in Linux kernel configurability and binary tailoring . He leads the Chair of Computer Science 4 (System Software) and develops open-source tools for minimizing software stacks while preserving functionality. University: Friedrich-Alexander University Erlangen-Nürnberg School: College of Engineering Department: Department of Computer Science Rank: Professor Research Interests: Ziegler investigates methods to automate software stack tailoring. His work spans: Configuration Interface Utilization (e.g., Linux kernel modules) Binary-Level Code Removal (ELF file manipulation without source access) Maintenance Impact Quantification (AST hashing for change detection) Publication Trends: Recent works emphasize attack surface reduction and scalable configuration testing , while earlier studies focus on feature modeling and compilation redundancy . Tools developed include GitHub-hosted open-source solutions . Advising: Supervised multiple Master’s theses on topics like header analysis for dead code detection and dynamic variability management in Linux systems.
Valentin Rothberg is a Researcher at the Department of Computer Science 4 (Distributed Systems and Operating Systems) at Friedrich-Alexander-Universität Erlangen-Nürnberg. His work focuses on operating systems, software configuration management, and compiler optimization. He is a core contributor to projects like CADOS (Configurability Aware Development of Operating Systems) and VAMOS (Variability Management in Operating Systems). Research interests include Linux kernel customization, dynamic variability in software systems, and compiler-based redundancy detection. He has authored notable publications on AST hashing for build optimization and impact analysis of Linux feature changes. Rothberg has advised multiple theses on topics like kernel configuration analysis and static analysis tools. His open-source contributions include the vgrep tool for enhanced text search and collaboration on container technologies like Podman . He maintains active involvement in FAU's distributed systems research and has presented at conferences such as USENIX and VaMoS.
Dr. Julio Sincero is a former researcher at the Department of Computer Science 4 (Distributed Systems and Operating Systems Group) at the University of Erlangen-Nuremberg. His academic work focuses on variability management in system software, configuration analysis, and software product lines, particularly in the context of operating systems like Linux. He holds a PhD from Friedrich-Alexander-Universität Erlangen-Nürnberg (2013). His research explores challenges such as variability bugs, configuration inconsistencies, and non-functional property management in large-scale systems. He contributed to projects like VAMOS (Variability Management in Operating Systems) and the CiAO framework for embedded systems. Teaching activities include courses on operating systems and related technical seminars. Notable publications span static analysis of system software variability, configuration coverage techniques, and Linux kernel feature management. He has collaborated with institutions worldwide, addressing topics like many-core system reengineering and software product line adaptability. Dr. Sincero's work emphasizes practical solutions for scalability and maintainability in complex system software, with a focus on bridging theoretical research and real-world implementation challenges.
Lars Nolte is a Researcher at the Chair of Integrated Systems (Lehrstuhl für Integrierte Systeme) at the Technical University of Munich, where he conducts cutting-edge research in computer architecture and operating systems with a focus on hardware acceleration for Linux kernel mechanisms using FPGA platforms. His primary research areas include Computer Architecture, Operating Systems, Hardware/Software Co-Design, Embedded Systems, FPGA Acceleration, and Linux Kernel Development. He investigates hardware-assisted solutions for inter-process communication, event notification, and thread synchronization to reduce latency in real-time systems, primarily through the PASSTA project which develops FPGA-based accelerators for Linux syscall optimization. Nolte's recent publications demonstrate a clear trend toward hardware-software co-design for Linux performance enhancement, with 10 publications since 2019 focusing on FPGA-accelerated kernel features like futex, epoll, and IPC. His work bridges computer architecture and systems software, targeting embedded and high-performance computing applications. He actively supervises student research, having guided numerous Bachelor's, Master's, and research internships on topics including hardware-accelerated Linux mechanisms, network processing, and tracing systems. Notable advisees include Maximilian Grözinger (Hardware Assisted Futex) and Jonas Kirf (Inter-Process Communication survey). The Chair of Integrated Systems, led by Prof. Andreas Herkersdorf, provides Nolte's collaborative research environment focused on integrated systems for cellular communications and embedded applications, with facilities including FPGA labs and Gem5 simulation infrastructure.
Adam Krafczyk is a researcher in the Software Systems Engineering (SSE) group at the University of Hildesheim's Institute of Computer Science. As part of the Faculty of Mathematics, Natural Sciences, Economics and Computer Science, he focuses on software product lines, static analysis, and variability modeling. His work bridges theoretical computer science with practical industrial applications, particularly in improving software configuration and variability management. Research Interests: - Variability-aware metrics for software product lines - Static analysis techniques for large-scale systems - Conversion of integer-based variability to propositional logic - Industrial IoT platforms and energy optimization (e.g., ReGaP project) - Generative AI applications in software development (GENIUS project) - Configuration mismatch detection in systems like Linux Notable Projects: GENIUS: Generative AI for the Software Development Lifecycle ReGaP: Energy optimization in manufacturing via AI/IIoT IIP-Ecosphere: Industrial IoT platform for AI integration MetricHaven: Tool for variability-aware quality metrics Awards: • Best Paper Award at SEAMS 2023 for 'Control Action Types - Patterns of Applied Control for Self-adaptive Systems' Professional Contributions: - Developed novel approaches for analyzing software product line variability - Collaborated with industry partners like Siemens and Bosch - Active in conferences like SPLC, SEAMS, and ETFA
James R. Cordy is a Professor in the School of Computing at Queen's University, Faculty of Engineering and Applied Science, Kingston, Canada. He is a leading researcher in software engineering, with a focus on source code analysis, software clone detection, model-driven engineering, and program transformation. He has been actively publishing since 1977, with a sustained record of contributions in top-tier venues such as ICSE, MoDELS, and WCRE. His research interests include software clone detection, model transformation, Simulink models, source transformation, software maintenance, and grammatical inference. He has developed and contributed to influential tools such as TXL and NiCad, and his work often involves empirical studies and tool evaluation in real-world software systems. The most recent articles highlight trends in model transformation, clone detection, verification of state machines, and migration of legacy systems. His work increasingly integrates formal methods and empirical validation, particularly in automotive and safety-critical domains. He has also explored applications in healthcare software, such as artificial pancreas systems. Most Influential Paper Award, SCAM 2001 (awarded in 2019) He has advised numerous students, including Manar H. Alalfi, Matthew Stephan, and Chanchal K. Roy, who have co-authored multiple publications with him. His research is often collaborative, involving teams from Queen's University and other institutions. He has also contributed to workshops and special issues, demonstrating leadership in the software engineering community.
