Reuse of low-code programming Professors and Supervisors in Germany

Nadia PolikarpovaView profile

Associate Professor

Max Planck Institute for Software SystemsGermany

Nadia Polikarpova is an Associate Professor in the Department of Computer Science and Engineering at the University of California, San Diego . She earned her PhD from ETH Zurich in 2014 under Bertrand Meyer , followed by postdoctoral research at MIT CSAIL with Armando Solar-Lezama . Her academic contributions have been recognized with prestigious awards including the 2020 Sloan Fellowship , 2020 Intel Rising Stars Award , and 2020 NSF CAREER Award . Polikarpova's research focuses on program synthesis , program verification , and type systems . She leads the Programming Systems group at UCSD and contributes to the IFIP Working Group 2.8 on Functional Programming since 2022. Her work spans foundational research and practical tools, including projects like Synquid , SuSLik , and Laurel that combine formal methods with machine learning for code generation. Her recent publications in venues like OOPSLA , NeurIPS , and ICFP reveal trends in AI-assisted programming , live programming environments , and formal verification . She has advised numerous PhD and Master’s students including Shraddha Barke , Zheng Guo , and Tristan Knoth , many of whom have moved to prominent academic and industry positions. Notable artifacts from her lab include tools like ColDeco for spreadsheet inspection and Superfusion for eliminating intermediate data structures. 2020 : Sloan Fellow 2020 : Intel Rising Stars Award 2020 : NSF CAREER Award 2021 : Distinguished Paper at POPL 2023 : Distinguished Artifact at PLDI 2023 : Distinguished Paper at OOPSLA Polikarpova actively contributes to academic service, serving on program committees for PLDI , POPL , and OOPSLA , and co-chairing the OOPSLA Review Committee in 2023. She has delivered keynotes at APLAS'20 and PLDI'24 , emphasizing the integration of large language models with formal methods.

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Thomas BergerView profile

Professor

University of HohenheimGermany

Thomas Berger is a Professor at the University of Hohenheim , affiliated with the Faculty of Agricultural Sciences and leading the Department of Economics of Land Use . He also contributes to the Computational Science Hub and Hohenheim Tropics initiatives. Focus Areas: Climate change adaptation, land-use modeling, biodiversity-productivity trade-offs, agent-based simulation, and machine learning in agricultural systems. Key Projects: Simulation frameworks for smallholder resilience in Ethiopia, bioeconomic modeling in the Amazon, and hybrid intelligence applications in European agricultural policy. Recent Publications: 2025 study on climate change effects on insecticide reduction in Germany, 2024 work on reconciling biodiversity with productivity via hybrid models, and 2023 methodological contributions to surrogate modeling and seasonal forecast integration. Research Trends: Interdisciplinary integration of climate science, agricultural economics, and computational modeling, with increasing emphasis on AI-assisted decision support systems and sustainability policy validation. Teaching & Outreach: Offers Agricultural Economics seminars and Hohenheim Tropics discussions, requiring advance email registration for office hours.

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Mario BaldiView profile

Researcher

University of TrierGermany

Mario Baldi is a researcher affiliated with the Polytechnic University of Turin, Italy , with significant contributions to computer networking , distributed systems , and software-defined networking . Key research themes: network function virtualization , programmable dataplanes , time-driven scheduling , and traffic analysis . Recent work focuses on RDMA-enabled compute offloading (2023) and DNN inference in network data planes (2023). Longstanding expertise in multicast routing , voice/data packet efficiency , and XML-based protocol parsing (2000–2006). Collaboration network includes Yoram Ofek , Fulvio Risso , and Han Hee Song , with 99+ publications spanning 1994–2023.

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Marieke HuismanView profile

Professor

Max Planck Institute for Software SystemsGermany

Marieke Huisman is a Professor in Software Reliability at the University of Twente, where she leads the Formal Methods and Tools (FMT) Group within the Electrical Engineering, Mathematics and Computer Science faculty. She serves as the Chair of the Computer Science department and holds several significant leadership positions including President and Steering Committee chair of the ETAPS association, which runs the ETAPS conferences. As a Fellow of the Netherlands Academy of Engineering (NAE), she contributes to national and international research initiatives including serving on the board of the ICT-Research Platform Netherlands (IPN) and the NWO advisory table for Computer Science. Her research focuses on program verification, reliability of concurrent and distributed applications, software specification, and formal methods. She has pioneered work in the verification of concurrent data structures and parallel programming models, with a particular emphasis on developing practical verification techniques that can be applied to real-world software systems. Her research has led to the development of the VerCors verification toolset, which is designed to verify concurrent and distributed software. Analysis of her recent publications reveals a strong focus on practical applications of formal verification techniques, with significant work on GPU programming verification, embedded systems verification, and the development of tools that bridge the gap between theoretical verification methods and industrial practice. Her work spans multiple subdomains including memory safety for concurrent programs, verification of heterogeneous systems, and automated invariant generation. Netherlands Prize for ICT Research 2013 - A prestigious award worth 50,000 euros for innovative research in ICT 2023 Athena Award - Recognizing female researchers who stand out as role models for others Professor Huisman has secured substantial research funding through multiple NWO projects including the ERC Starting Grant for the VerCors project, the NWO VICI project Mercedes (Maximal reliability of concurrent and distributed software), and the NWO OC M project Pallas. She actively supervises PhD students and master's projects, with a focus on practical verification techniques. Her leadership extends to major collaborative efforts such as the VerifyThis verification competition series and the development of the VerCors verification infrastructure. She also co-initiated the Alice & Eve project, which celebrates women in computing and promotes diversity in computer science.

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Stefan KrötschView profile

Professor

University of Applied Sciences KonstanzGermany

Professor Stefan Krötsch serves as Professor of Building Construction and Design at the School of Architecture, Constance University of Applied Sciences (HTWG Konstanz) since 2018. His academic leadership includes chairing the examination board for architecture programs (2019-2024) and serving on Baden-Württemberg's timber construction guidelines committee. Previously, he held positions as Junior Professor of Timber Construction at TU Kaiserslautern (2015-2018) and Academic Council member at TU Munich's Architecture Faculty (2008-2014). His research focuses on sustainable timber construction systems, circular building practices, and innovative material applications. Key research areas include: Multi-story timber construction systems Material reuse and circular economy in construction Bamboo-concrete composite structures Design-build pedagogy integrating theory and practice Climate-responsive building techniques Historic building renovation with sustainable materials Professor Krötsch's recent publications and research projects demonstrate strong trends toward circular construction systems and material innovation. His Stuttgart 210 project explores reuse of curved cross-laminated timber elements from Stuttgart 21 station construction, while his 'Holzbau im Bestand' research investigates prefabricated timber renovation systems. His work consistently bridges academic research with practical implementation through student design-build projects across Germany and Africa. His scientific recognition includes the Hugo-Häring-Preis 2020, European Union Prize for Contemporary Architecture nomination (2019), and multiple awards for sustainable construction innovation. His Fibra Award finalist status and Ralph Erskine Award (2017) highlight international recognition of his sustainable design work. Professor Krötsch's research funding demonstrates substantial grant acquisition capability, including 1.8 million EUR for Stuttgart 210 real laboratories, 124,960 EUR from Bundesinstitut für Bau- for parametric structures research, and 305,000 EUR for cross-laminated timber waste recycling research. His student projects have received numerous awards including the German University Prize for Timber Construction (1st prize 2019). His design-build approach connects theoretical education with practical implementation through student-led construction projects in Germany and Africa, creating laboratories for sustainable building practices. The Stuttgart 210 project established four real laboratories in Ingersheim, Stuttgart, Marbach, and Mannheim to test circular construction systems using reclaimed materials.

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Andreas WortmannView profile

Professor

University of StuttgartGermany

Andreas Wortmann is a Professor at the Institute for Control Engineering of Machine Tools and Manufacturing Systems (part of the University of Stuttgart) and an Associate Member of the Cluster of Excellence IntCDC . His research focuses on Digital Twin Technology , Model-Driven Engineering , and Cyber-Physical Production Systems , with applications in Industrial Automation and Domain-Specific Languages . Recent publications highlight his work on systematic mapping studies of digital twin platforms, low-code development for manufacturing systems, and language engineering for heterogeneous environments. He has contributed to standards like the Asset Administration Shell and explored AI integration in timber construction process planning . Key collaborations include projects with researchers in robotics , software architecture , and industrial IoT . His work bridges academic research with practical implementations in the German automotive industry and smart manufacturing domains.

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Peter Alois FrancoisView profile

Research Fellow

University of Duisburg-EssenGermany

Peter Alois Francois is a Research Fellow at South Westphalia University of Applied Sciences, Faculty of Computer Science, where he contributes to the Transformation Management (TM) group. He leads research in the project "Construction and Evaluation of Reference Models and Components for AI-supported Process Automation" and teaches process management and automation to practitioners and management teams. His academic credentials include: M.Sc. in Business Informatics (2019-2021) from Fachhochschule Dortmund B.Eng. in Engineering Management with IT (2015-2016) from Staffordshire University B.Sc. in International Studies of Business Administration and Computer Science (2014-2019) from Fachhochschule Südwestfalen His research centers on business process management with specialized focus on low-code reuse ecosystems and citizen developer dynamics. He investigates cognitive biases in digital transformation and vendor lock-in effects in automation platforms, bridging theoretical frameworks with industrial applications from his prior roles at NDR and DB Regio AG. His work emphasizes practical implementation of process automation in organizational contexts. Analysis of his publications (2022-2025) reveals a cohesive research trajectory toward systematic reuse of automation artifacts. Key themes include organizational capability building for BPM, critical evaluation of RPA adoption goals, and architectural frameworks for enabling citizen developers. His work consistently addresses the intersection of human factors and technical systems in process automation. The TM-group he belongs to is actively expanding its research capacity in information systems and transformation management, with ongoing recruitment for new research positions to strengthen their innovation focus.

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Xiaoyang ZengView profile

Professor

Schloss Dagstuhl - Leibniz Center for InformaticsGermany

Xiaoyang Zeng is a Professor at Tsinghua University's School of Information Science and Technology, Institute of Microelectronics, with an extensive research portfolio in VLSI design, integrated circuits, and hardware acceleration systems. With over 429 publications spanning from 2005 to 2025, Professor Zeng maintains an exceptionally active research program, particularly evident in the high publication volume in recent years (45 papers in 2024 and 28 projected for 2025). His collaborative network includes prominent researchers such as Yibo Fan, Jun Han, Xu Cheng, and Xiaoyong Xue. Professor Zeng's research focuses on cutting-edge areas including Compute-in-Memory architectures, neuromorphic computing, low-power circuit design, and hardware acceleration for AI applications. His work bridges theoretical innovation with practical implementation, as evidenced by numerous publications in top-tier IEEE journals including the Journal of Solid-State Circuits, Transactions on Circuits and Systems, and Transactions on VLSI Systems. Recent work demonstrates particular strength in RRAM-based CIM accelerators, energy-efficient converters, and advanced signal processing techniques. The publication trends show a strategic evolution from traditional circuit design toward emerging computing paradigms, with increasing focus on AI hardware acceleration, neuromorphic systems, and energy-efficient computing solutions. His research group has developed innovative approaches to address challenges in memory-centric computing, analog circuit design, and hardware implementation of machine learning algorithms, with applications spanning consumer electronics, medical devices, and edge computing systems. Selected Scientific Awards: IEEE Journal of Solid-State Circuits Best Paper Award (2022) National Natural Science Award of China (Second Class, 2020) IEEE Asian Solid-State Circuits Conference Best Paper Award (2019) Professor Zeng has successfully advised numerous graduate students who have become active contributors in the field, with several now leading their own research projects. His research has been supported by multiple national-level grants from the National Natural Science Foundation of China and the Ministry of Science and Technology, focusing on next-generation computing architectures and advanced circuit design methodologies. The research group maintains strong industry connections with leading semiconductor companies for technology transfer and practical implementation of research outcomes.

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Maliheh IzadiView profile

Assistant Professor

Max Planck Institute for Security and PrivacyGermany

Maliheh Izadi is a tenure-track assistant professor in the Faculty of Electrical Engineering, Mathematics, and Computer Science at Delft University of Technology (TU Delft), Netherlands. She leads the AISE (AI-enabled Software Engineering) research lab and serves as the scientific manager for the TU Delft/JetBrains Collaboration (AI4SE). She is also a member of the Software Engineering Research Group (SERG) at TU Delft and actively supervises PhD, MSc, and BSc students. Dr. Izadi's research focuses on enhancing software development tools through building smarter software and tailoring machine learning and NLP techniques to source code. Her primary interests include building and tailoring large language models (LLMs) and autonomous agents to source code, with specific focus areas including evaluation, benchmarking, model memorization, IDE integration, in-IDE Human-AI interaction, and extending models' capabilities to low-resource programming languages. Her work bridges the gap between deep learning and source code analysis, with applications in code understanding, generation, documentation, and developer productivity enhancement. Her recent publications reveal a strong trend toward evaluating and improving LLMs for code, with emphasis on safety, usability, and efficiency. She has made significant contributions to benchmark development, harmfulness assessment of LLMs in programming contexts, and improving the integration of AI tools within development environments. Her research consistently addresses real-world industrial challenges while advancing theoretical understanding of model behavior. Google Research Scholar Award (2025) for proposal on Tackling LLM Hallucinations Amazon Research Award (2024) for proposal on Addressing Memorization in Code LLMs ACM SIGSOFT Distinguished Paper Award (2025) for How Much Do Code Language Models Remember? ACM SIGSOFT Distinguished Paper Award (2024) for A Transformer-Based Approach for Smart Invocation of Automatic Code Completion Best Tool Award at SaTML'22 competition for STACC Best Tool Award at NLBSE'22 competition for Catiss Dr. Izadi actively collaborates with industry partners, particularly JetBrains Research, where she leads the AI4SE ICAI lab. She has supervised multiple PhD and master's students and has served on program committees for major software engineering conferences including ASE, ICSE, FSE, and MSR. Her research has been published in top venues such as IEEE/ACM ICSE, FSE, ASE, TOSEM, EMSE, MSR, ICSME, SANER, and JSS. She is also organizing the First International workshop on Autonomous Agents in Software Engineering (AgenticSE) co-located with ASE'25.

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Steffen HelkeView profile

Professor

South Westphalia University of Applied SciencesGermany

Prof. Dr.-Ing. Steffen Helke serves as a full Professor in the Department of Electrical Engineering & Information Technology at University of Applied Sciences Südwestfalen. His academic roles include Senate membership, evaluation officer for the department, program coordinator for Media Informatics, and spokesperson for the GI Specialist Group Automotive Software Engineering. Current affiliations span committee work in electrical engineering bachelor programs and leadership in safety-critical software research. His research focuses on functional software security , safety-critical system verification , and model-based quality assurance . Key areas include information flow control languages, automotive software security, hierarchical statechart validation, and requirements delta analysis for efficient development estimation. Methodologies emphasize formal verification, static analysis, and tool-supported refactoring to ensure robustness in embedded systems. Teaching encompasses advanced courses in Software Engineering, IT Security, Ethical Hacking, and Competitive Programming. Thesis supervision occurs in research areas like NLP-based requirements analysis, refactorings for security languages (Jif), and model checking for Statecharts. Industrial collaborations facilitate project/bachelor theses with real-world security applications. Research trends from publications show consistent focus on bridging formal methods with industrial software development. Dominant disciplines include Software Engineering (72% of works) and Formal Verification (58%), with emerging subfields like NLP-assisted requirements engineering (2019) and automotive security frameworks. Keyword analysis reveals sustained emphasis on verification (100% of works), security (80%), and automotive applications (40%). Administrative contributions include leadership in the combined Electrical Engineering bachelor program and active participation in university governance through department councils. Tools developed in his research (e.g., Delta Analyzer, R2BC) are integrated into curricula using ReqView, Matlab/Simulink, and Enterprise Architect for systematic requirement engineering and UML modeling.

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Qing HuangView profile

Associate Professor

Max Planck Institute for Security and PrivacyGermany

Qing Huang is an Associate Professor in the School of Computer and Information Engineering at Jiangxi Normal University in Nanchang, China. His academic career focuses on bridging software engineering with artificial intelligence, particularly through the application of large language models to enhance software development processes. His research interests span multiple interconnected domains: Software Engineering Knowledge Graphs Human-Computer Interaction Programming Languages Artificial Intelligence applications in software development Dr. Huang's recent work demonstrates a strong focus on leveraging large language models (LLMs) to address fundamental challenges in software engineering. His research explores how AI can enhance code generation, API understanding, software testing, and knowledge representation in programming contexts. A significant portion of his work investigates the intersection of knowledge graphs and LLMs to create more intelligent software development tools. His publications reveal a consistent pattern of innovation in applying cutting-edge AI techniques to practical software engineering problems, with particular emphasis on improving developer productivity through better tooling and knowledge management. Dr. Huang has made notable contributions to the field of prompt engineering for software development tasks, exploring how natural language interfaces can serve as "APIs" for human-AI interaction. His work on AI Chains represents a novel approach to connecting human developers with LLM capabilities through structured knowledge representations. Additionally, he has conducted significant research on smart contract analysis, code reuse, and type inference in partial code contexts. His scientific contributions have been recognized through publications at major software engineering conferences including ASE and ICSE, with multiple papers accepted across different tracks (Research Papers, Journal-First, Tool Demonstrations). Dr. Huang serves as a Program Committee member for ASE 2025 in the Research Papers track, demonstrating his standing in the software engineering research community. Dr. Huang collaborates extensively with researchers from various institutions, including Data61 (Australia), Nanyang Technological University, and other Chinese universities. His work demonstrates strong interdisciplinary connections between traditional software engineering and emerging AI technologies.

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