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Ute SchmidView profile

Professor

Freiburg University of EducationGermany

Professor Ute Schmid is a Full Professor of Cognitive Systems at the University of Bamberg, where she has been a faculty member since September 2004. She leads the Cognitive Systems Group within the Bamberg Center of AI (BaCAI), focusing on creating AI systems that generate human-like explanations and reasoning processes. Her research bridges cognitive science and artificial intelligence to develop methods for explanation generation, inductive programming, and interactive machine learning. Professor Schmid's work emphasizes practical applications of explainable AI across diverse domains including image classification, medical diagnosis, and educational technologies. Her research on contrastive explanations, near misses, and human-AI alignment has significantly advanced the field of XAI. She has also pioneered research on AI literacy, recognizing the growing importance of basic AI understanding for responsible tool usage by non-experts. Her publication record demonstrates exceptional productivity and impact, with numerous articles in top-tier venues including Nature Machine Intelligence, IEEE Transactions on Visualization and Computer Graphics, and the Journal of Web Semantics. Her 2025 paper 'Aligning generalization between humans and machines' represents a significant theoretical contribution to understanding human-machine cognitive alignment. Professor Schmid actively contributes to gender diversity research in computer science through studies examining why women pursue PhDs in the field. She has also made important contributions to computing education, investigating how students acquire programming skills and how AI tools like code generators are integrated into learning processes. As an educator and researcher, Professor Schmid maintains strong international collaborations, with co-authors spanning multiple countries and institutions. Her interdisciplinary approach is evident in her diverse publication venues and collaborative work that bridges computer science, cognitive science, education, and application domains.

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Florian JohannsenView profile

Professor

Schmalkalden University of Applied SciencesGermany

Professor Florian Johannsen is a faculty member at Schmalkalden University of Applied Sciences in the Faculty of Business and Economics, where he leads research and teaching in Business Application Systems. His office is located in Building B, Room 0213, and he holds regular office hours on Thursdays from 2:00-3:00 PM, with appointments available during semester breaks. Professor Johannsen's research spans business application systems, method engineering, chatbots for internal business use, quality management for Smart Services & Industry 4.0, and social media analysis. His work often bridges theoretical frameworks with practical applications, particularly in developing modeling tools for business process improvement. He has led the WiWiNow Campus App project in collaboration with the University of Bremen, which received the Comenius EduMedia Seal in 2021 for its innovative approach to integrating technology into university teaching contexts. His recent publications (2021-2024) demonstrate consistent productivity with a focus on digital transformation in business processes, mobile learning applications, and the integration of sustainability principles into quality management systems. These works appear in top-tier information systems journals and conferences, showing his strong standing in the academic community. Best Associate Editor Award at WI 2022 Best Paper Award at DESRIST 2021 Comenius EduMedia Seal 2021 Best Associate Editor at ECIS 2019 Teaching Award from University of Regensburg (2017) Hilti Best Paper Award BDVB Award 2007 Professor Johannsen teaches advanced courses in business application systems, including specialized topics on ERP systems, service management, and social media analysis. His teaching reflects his research expertise, with courses designed to prepare students for the digital transformation challenges in modern business environments. His recent work on mobile learning applications demonstrates his commitment to innovative educational approaches that support student success, particularly in the transition to higher education.

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Petra GretschView profile

Professor

Freiburg University of EducationGermany

Petra Gretsch is a Professor of Linguistics and Language Didactics at the Institute for German Language and Literature at Pädagogische Hochschule Freiburg, where she has held a professorship since 2010. Her academic career spans over 25 years, including positions as Junior Professor (2009-2010), Academic Staff Member (2008-2009), and research roles at the Max Planck Institute for Psycholinguistics in Nijmegen (1998-2005). She completed her PhD with distinction in 2000 at the University of Tübingen. Her educational background includes a Master's degree from the University of Tübingen (1994) with top grades in all subjects, where she studied General Linguistics (major), Psychology and Computer Science (minors), with additional studies at the University of Edinburgh. Her academic journey began with research assistant work within the DFG project on complex syntax acquisition at the University of Tübingen (1990-1993). Professor Gretsch's research focuses on linguistics and language didactics, particularly continuous language education across educational transitions. Her work examines three dimensions: vertical (educational biography transitions), horizontal (institutional cooperation), and diagonal (multilingualism as a resource). She investigates language acquisition from early childhood through school transitions, with special attention to visual literacy in language learning and language-sensitive teaching across subject areas. Her recent publications (2023-2025) show consistent output in language education, with a focus on language assessment, inclusive education, and digital learning tools. These works demonstrate her commitment to practical applications of linguistic research in educational settings, particularly regarding language support for diverse learners and subject-specific language development. PhD with distinction (s.c.l.) in 2000 Scientific Advisory Board Member of Goethe Institute (since 2024, elected deputy chairperson 2024-2027) Scientific Advisory Board Member of Central Office for Foreign Schools (since 2020) Scientific Advisory Board Member of Daimler and Benz Foundation (2015-2021) Professor Gretsch leads the 'Durchgängige Sprachbildung Freiburg' project (since 2012), which has developed a comprehensive framework for continuous language education across institutional transitions. She also co-leads the Erasmus+ IDE project (2024-2027) on interpreter-mediated deaf education and participates in the STELT project strengthening German language teacher education in Norway. Her international collaborations include work with institutions across Europe, Asia, and South America through the Goethe Institute and ZfA. She directs research on practical applications of language education theory, with particular focus on developing accessible language learning materials like the 'Boto' framework for children aged 3-11, and creating tools for language assessment and support in inclusive educational settings.

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Kristina KelberView profile

Professor

Dresden University of Applied SciencesGermany

Professor Kristina Kelber is a faculty member at HTW Dresden (Hochschule für Technik und Wirtschaft Dresden), holding the Chair of Communications Engineering within the Faculty of Electrical Engineering. She is also a member of the Faculty Council, contributing to academic governance at the institution. Her research focuses on signal processing , digital image processing , and the analysis and design of nonlinear dynamic systems . Her work spans theoretical aspects of communications engineering and practical applications in diverse fields including music technology for accessibility applications, bird song identification, film restoration, and visitor center information systems. Her publication record demonstrates consistent expertise from the 1990s to present, with evolving applications from foundational work in chaos-based encryption systems to more recent applied research with social impact. Professor Kelber has secured research funding for projects such as "sprechAktiv," a child-friendly interactive language learning media initiative developed in cooperation with Linguwerk GmbH, Dresden, and funded by the BMBF's SME innovative program from 2013-2015. Her research methodology combines theoretical analysis with practical implementation, as evidenced by publications ranging from mathematical analysis of chaotic systems to applied projects in music technology and image processing. Member of the Faculty Council at HTW Dresden Associated with the Communication Technology laboratory Active researcher with publications spanning over two decades Professor Kelber teaches courses in systems theory, signals and systems, audio and video technology, signal coding, and digital image processing across multiple degree programs. She offers both traditional classroom instruction and distance learning options through the Bildungsportal Sachsen (OPAL) platform, demonstrating adaptability to different educational delivery methods and commitment to accessible education.

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Tanyasha YearwoodView profile

Professor

University of GöttingenGermany

Tanyasha Yearwood is a Professor in the Department of English Philology at the University of Göttingen's Faculty of Humanities. She holds an active teaching position with responsibilities spanning both the Department of English Philology and the Department of Romance Philology, teaching courses related to language teaching methodology, intercultural learning, and critical cultural awareness. Her primary research interests focus on Computer-Assisted Language Learning (CALL), Blended Learning approaches, and practical implementation of production-oriented learning and teaching methodologies. Yearwood's work particularly emphasizes the integration of technology in language classrooms, with special attention to creating learner-centered environments rather than technology-focused ones. She has extensively explored Activity Theory as a framework for understanding classroom dynamics in technology-enhanced language learning. Her publication record reveals a consistent trajectory in CALL research, with particular focus on how technology can be normalized in classroom settings to serve as complementary rather than central elements in language learning. Her work spans theoretical frameworks like Activity Theory to practical classroom implementations, especially in resource-constrained environments like single-computer classrooms. The evolution of her research shows increasing attention to cultural dimensions of language learning, particularly intercultural competence and critical cultural awareness. Yearwood maintains an active presence in international academic conferences, regularly presenting at major venues including EUROCALL, IATEFL, and specialized CALL conferences. Her teaching portfolio demonstrates comprehensive coverage of language teacher education across multiple semesters, with consistent offerings in research methods for language teaching and practical application of theoretical concepts.

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Fang ZhaoView profile

Associate Professor

FernUniversität in HagenGermany

Fang Zhao serves as Junior Research Group Leader of the Multimedia group at FernUniversität Hagen's Center of Advanced Technology Assisted Learning and Predictive Analytics (CATALPA) since April 2021. As a cognitive and educational psychologist, she conducts interdisciplinary research on multimedia learning and multitasking within this university-funded research center, collaborating with partners across psychological and educational domains. Her academic credentials include a 2024 Habilitation from FernUniversität Hagen, a Ph.D. in Psychology from University of Koblenz Landau (2012-2015), an M.A. in Linguistics and Translation Studies from Durham University, U.K. (2010-2012), and a B.A. in Linguistics and English Language from Henan University, China (2006-2010). Dr. Zhao's research examines how individuals process multimedia information through text-picture integration, interactive simulations, and video-based instruction, with particular focus on exploration-exploitation dynamics in learning environments. Her sequence learning investigations extend to multitasking scenarios involving basic sequences, timing patterns, and complex hierarchical structures like Origami folding. This work bridges cognitive theory with practical educational technology applications through rigorous experimental methodologies. Recent publication analysis reveals consistent emphasis on optimizing visual representations for data comparison, measuring cognitive load in online learning, and evaluating guidance structures in asynchronous courses. Her research demonstrates that while interactive elements are generally preferred by learners, their educational benefits remain context-dependent with significant individual differences in effectiveness. Leading the Multimedia junior research group at CATALPA, Dr. Zhao directs investigations into how interactive and multimedia components influence learning processes across diverse student populations. The team operates within an interdisciplinary framework that integrates psychological theory with technological innovation to develop predictive analytics for learning enhancement.

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Jakub KuzilekView profile

Researcher

Humboldt UniversityGermany

Dr. Jakub Kuzilek is a researcher at the Institute of Computer Science, Faculty of Mathematics and Natural Sciences, Humboldt University of Berlin. He is a member of the "Didaktik der Informatik / Informatik und Gesellschaft" (Computer Science Education | Computer Science and Society) research group, also affiliated with the Educational Technology Lab at the German Research Center for Artificial Intelligence. He joined the CSES research group in January 2020 after previously working at the Faculty of Mechanical Engineering, CTU in Prague, and completing a 4-year research stay at the Open University. Dr. Kuzilek completed his Ph.D. in Biomedical Signal Processing using Blind Source Separation methods. His academic journey transitioned from biomedical signal processing to educational data mining when Professor Zdenek Zdrahal from the Knowledge Media Institute (Open University) invited him to work on data mining of student data in the OU Analyze project. Dr. Kuzilek's primary research interests focus on the intersection of machine learning and education. His work centers on Educational Data Mining (EDM) and Learning Analytics (LA), with particular emphasis on explainable AI applications in educational settings. He investigates student behavior in online learning systems, develops predictive models for student success, and explores methods for providing actionable feedback to learners. His research bridges the gap between signal processing techniques from his earlier work and modern educational technology applications, with a strong focus on practical implementations that can directly benefit students and educators. Analysis of Dr. Kuzilek's recent publications (2021-2024) reveals a clear focus on advancing Learning Analytics and Educational Data Mining. His work consistently explores how machine learning can be applied to understand and improve educational outcomes, with particular attention to explainability of predictive models. Key research threads include student success prediction using behavioral data, algorithmic approaches to student grouping, automated feedback generation, and the use of self-assessments in higher education. His methodological approach combines rigorous statistical analysis with practical educational applications, often using real-world educational datasets to validate his findings. Best paper award for "An Automatic Method for Holter ECG Denoising Using ICA" (2011) Second place in CINC Challenge 2011 for "Simple Scoring System for ECG Signal Quality Assessment on Android Platform" (2011) Dr. Kuzilek actively mentors students at various levels, supervising numerous bachelor's and master's theses on topics related to Learning Analytics, Educational Data Mining, and machine learning applications in education. His grant portfolio demonstrates sustained research activity, including leadership roles on projects funded by the Czech Science Foundation, University Development Foundation, and BMBF. His current research focuses on AI-supported personalization in vocational training and implementing AI-based feedback systems in higher education institutions. As a core member of the Computer Science Education | Computer Science and Society research group at Humboldt University, Dr. Kuzilek collaborates with colleagues including Prof. Dr. Niels Pinkwart and other researchers to advance the field of educational technology. His work bridges theoretical research in machine learning with practical applications in real educational settings, contributing to both academic knowledge and tangible educational improvements.

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Amiangshu BosuView profile

Associate Professor

Max Planck Institute for Security and PrivacyGermany

Amiangshu Bosu is a tenured Associate Professor in the Department of Computer Science at Wayne State University's College of Engineering. Previously, he served as a tenure-track Assistant Professor at Southern Illinois University Carbondale from 2016-2018. His academic journey includes completing his Ph.D. at the University of Alabama in 2015 under Professor Jeffrey Carver, followed by postdoctoral research with Dr. Danfeng Yao at Virginia Tech. His educational background reflects a strong foundation in software engineering research, with his doctoral work focusing on empirical approaches to software development practices. This foundation has enabled his current research trajectory examining human aspects of software engineering. Bosu's research program centers on empirical software engineering with particular emphasis on code review dynamics, toxicity detection in developer communications, and diversity issues in open source communities. His work bridges technical analysis with social science perspectives, investigating how communication patterns affect participation, especially regarding gender dynamics in OSS projects. Recent work increasingly incorporates natural language processing and machine learning techniques to build tools like ToxiCR for automated toxicity detection in code reviews. Analysis of his publication record reveals a clear evolution toward examining social dynamics in software development, with growing emphasis on gender bias, toxicity, and diversity issues. His research consistently applies empirical methods to understand real-world developer experiences while developing practical tools to improve code review processes and community health. His scientific recognition includes the prestigious NSF CAREER award (2024), NSF CRII award (2019), and Wayne State University's College of Engineering Research Excellence award (2025). He maintains senior membership status in both ACM and IEEE, reflecting his standing in the computing community. NSF CRII award (2019) NSF CAREER award (2024) College of Engineering Research Excellence award (2025) Senior Member of ACM Senior Member of IEEE Bosu actively contributes to the software engineering research community through service on program committees for major conferences including ICSE, ASE, ESEC/FSE, and ESEM. His GitHub presence (amiangshu.me) demonstrates active engagement with research tools and datasets, particularly those related to code review analysis and toxicity detection. While specific lab structure isn't detailed in the provided materials, his research group appears focused on empirical studies of software development practices with strong connections to industry through collaborations on projects like Chromium OS security analysis.

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Matteo CamilliView profile

Associate Professor

Max Planck Institute for Security and PrivacyGermany

Matteo Camilli is an Associate Professor in the Department of Electronics, Information and Bioengineering (DEIB) at Politecnico di Milano, Italy, where he leads research in software engineering and verification. His academic journey includes positions as Assistant Professor at Free University of Bozen-Bolzano and postdoctoral research at the University of Milan and University of Bergamo. His educational background includes a PhD in Computer Science (2015), MSc in Computer Science (2012), and BSc in Computer Science (2009), all from the University of Milan. His doctoral research focused on combining advanced abstraction techniques and big data approaches to address state explosion problems in formal verification. Camilli's research primarily centers on software verification, testing, and methods to improve dependability of autonomous, cyber-physical, service-based, and ML-enabled critical systems. His work spans formal methods, model-based testing, uncertainty quantification, and design-time/runtime verification with applications to complex distributed systems. His recent publications reflect a growing focus on explainable self-adaptation, quality assurance for LLM-based systems, and managing uncertainty in adaptive systems. His publication record includes papers in top journals (TOSEM, TAAS, JSS, EMSE) and conferences (ICSE, ISSRE, ICST, ICSA). He serves on program committees for prestigious conferences including ICSE, ICSA, ICST, and ECSA, and is on the steering committee for the International Workshop on Formal Approaches for Advanced Computing Systems (FAACS). Camilli actively contributes to the academic community through conference organization, including serving as Program Committee Member for numerous conferences and as Program Co-Chair for the Software Architecture track at ACM SAC. He also serves as guest editor for special issues on automated testing and dependable AI systems. His teaching portfolio at Politecnico di Milano includes Software Engineering 2, Software Engineering for Automation, and Distributed Software Development. Previously at Free University of Bozen-Bolzano, he taught Systems Engineering and Verification and Reliability for Dependable Systems.

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Domenico BianculliView profile

Associate Professor

Max Planck Institute for Security and PrivacyGermany

Domenico Bianculli is an Associate Professor and Chief Scientist 2 at the Interdisciplinary Centre for Security, Reliability and Trust (SnT) at the University of Luxembourg. He leads the Software Verification and Validation (SVV) research group and is affiliated with the Department of Computer Science in the Faculty of Science, Technology and Medicine (FSTM). Additionally, he serves as the deputy study program director for the Master in Space Technologies and Business. Dr. Bianculli earned his PhD from the University of Lugano (Switzerland) under Carlo Ghezzi, with a dissertation titled "Open-world software: Specification, Verification, and Beyond." He also holds a MSc in Computing Systems Engineering and a BSc in Computer Engineering from Politecnico di Milano (Italy). His research focuses on the specification, verification and validation of software systems, particularly evolvable software systems. His work spans trace checking and run-time verification of temporal properties, modeling access control policies, program analysis for security, incremental verification techniques, and verification of service-oriented systems. Dr. Bianculli bridges theoretical foundations with practical applications in cyber-physical systems, financial technology, and regulatory compliance. His recent publications reveal a strong trend toward applying machine learning to software engineering challenges, particularly in log analysis, anomaly detection, and automated compliance checking. He has made significant contributions to verifying cyber-physical systems through techniques for stress testing control loops and trace diagnostics for signal-based temporal properties. His work increasingly addresses financial technology challenges, with papers focusing on automated regulatory compliance related to GDPR and financial regulations. ACM SIGSOFT Distinguished Paper Award for "Efficient large-scale trace checking using MapReduce" (ICSE 2016) Nomination for the best paper award for "SMT-based checking of SOLOIST over sparse traces" (FASE 2014) Dr. Bianculli leads multiple significant research projects including KITS24/19067232 "SnT-R2S" funded by FNR Luxembourg, LOGODOR "Automated Log Smell Detection and Removal" funded by FNR's CORE scheme, and several financial regulation projects including AFRICA, ICCOFIDO, and RUMOFA. His research has been supported by national funding agencies and industry partnerships with CSSF Luxembourg, HITEC Luxembourg, BGL BNP Paribas, and LuxSpace. As head of the SVV research group at SnT, Dr. Bianculli oversees a team developing advanced techniques for software specification, verification, and validation. His group works on theoretical foundations and practical applications, with current projects addressing challenges in cyber-physical systems, financial technology, and regulatory compliance. The group maintains strong collaborations with industry partners in the financial sector and space technology domains.

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Robert ClarisóView profile

Lecturer

Max Planck Institute for Security and PrivacyGermany

Robert Clarisó is a Lecturer at Universitat Oberta de Catalunya (UOC) in the IT, Multimedia and Telecommunication Department. He has a strong background in Computer Science with a BSc (2000) and PhD (2005) from UPC-Barcelona Tech. His academic career includes positions as a part-time associate professor at UPC-Barcelona Tech and at Universitat Autònoma de Barcelona. Dr. Clarisó's educational background includes: BSc in Computer Science from UPC-Barcelona Tech (2000), graduated as the top of his class with a Special mention in the Spanish National University Degree Awards PhD in Computer Science from UPC-Barcelona Tech (2005), thesis titled "Abstract Interpretation Techniques for the Verification of Timed Systems" under Dr. Jordi Cortadella Fortuny His research primarily focuses on Formal Methods and Software Engineering, with recent expansion into AI-related topics. Dr. Clarisó has made significant contributions to Model-Driven Engineering, particularly in the area of Object Constraint Language (OCL). His recent work has shifted toward examining bias and fairness in Large Language Models and exploring the application of Generative AI in software engineering education, reflecting a strategic pivot to address contemporary challenges in AI ethics and deployment. Dr. Clarisó has held several leadership positions including Coordinator of the Research Group on Software Engineering at UOC (2008-2015), Academic Director of the Official Master in Computing Engineering (2011-2019), and Academic Director of the Bachelor's Degree in Techniques for Software Development (2020-2023). He currently leads the university's working group on "AI in education" and is a principal investigator of the SOM Research Lab. His notable recognition includes a Special mention in the Spanish National University Degree Awards. Dr. Clarisó has served on program committees for major conferences including MODELS and ASE across multiple years, demonstrating his standing in the academic community. As an educator, Dr. Clarisó has taught courses on automata theory, compilers, algorithms and data structures, graph theory, and software development. He has coordinated undergraduate theses and led postgraduate programs, showing his commitment to academic mentorship and program development. Dr. Clarisó is actively involved in research teams, currently leading the SOM Research Lab which focuses on software engineering research. His recent work has centered on the intersection of formal methods, model-driven engineering, and AI technologies, particularly examining ethical implications and educational applications.

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Istvan DavidView profile

Assistant Professor

Max Planck Institute for Security and PrivacyGermany

Istvan David is an Assistant Professor of Software Engineering at McMaster University's Faculty of Engineering, Department of Computing and Software, where he leads the Sustainable Systems and Methods Lab (SSM) and works as a researcher in the McMaster Centre for Software Certification (McSCert). His work bridges the gap between model-driven engineering, digital twins, and sustainability in systems engineering. Dr. David's research interests focus on digital twins , model-driven engineering , sustainability in computing, cyber-physical systems , and collaborative modeling . His lab develops novel reinforcement learning techniques , digital twin architectures , and modeling and simulation methods with a strong emphasis on sustainability as both a system characteristic and an engineering principle. His recent publications reveal a strong trend toward integrating digital twin technology with sustainability concerns, particularly in automotive systems, smart farming, and resource-efficient software engineering. The research spans from foundational modeling techniques to applied solutions addressing the four essential sustainability dimensions of technical systems: technical (long-term usage), economic (financial viability), environmental (reduced impact), and social (elevated utility). Scientific Awards: Best Practice Paper Award at MODELS Best Paper 2024 Runner-up in the Journal of Computer Languages Dr. David actively mentors students including PhD candidate Xiaoran (Sharon) Liu, and has supervised undergraduate researchers like Adwita Kashyap and Kyanna Dagenais. He has secured multiple research grants supporting work on sustainable systems and digital twin technologies, with applications in automotive engineering, smart farming, and resource-efficient computing. His lab collaborates with industry partners and academic institutions worldwide, including VU Amsterdam and University of Montréal. The Sustainable Systems and Methods Lab focuses on the vision of 'sustainable systems by sustainable methods,' addressing the growing problem of unsustainable systems engineering practices. The lab's work on bipartite sustainability aims to both build sustainable systems and develop systems using sustainable methods.

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Achiya ElyasafView profile

Assistant Professor

Max Planck Institute for Security and PrivacyGermany

Achiya Elyasaf is an Assistant Professor at the Software and Information Systems Engineering Department of Ben-Gurion University of the Negev, Israel. He received all his academic degrees in computer science from Ben-Gurion University and completed postdoctoral research in David Harel's group at the Weizmann Institute. In 2021, he co-founded Provengo Technologies, which develops software-testing solutions leveraging his expertise in software engineering and artificial intelligence. Dr. Elyasaf's research focuses on creating synergies between software engineering and artificial intelligence. He pioneered Context-Oriented Behavioral Programming, a paradigm for developing context-aware systems through natural and incremental behavior specification. His work on utilizing expert knowledge for evolving solvers to combinatorial games has been recognized as one of the most important achievements in AI gaming, mentioned alongside Deep Blue's victory over Kasparov and Watson's Jeopardy! win in Nick Bostrom's 2014 book 'Superintelligence: Paths, Dangers, Strategies'. His recent publications demonstrate strong activity in model-based testing, combinatorial sequence testing, and behavior composition. The articles reveal consistent focus on applying AI techniques to software engineering challenges, particularly in testing and verification domains, with practical implementations like the Provengo tool suite and EC-KitY framework. Dr. Elyasaf has received significant recognition for his work, including three HUMIE Awards from the Genetic and Evolutionary Computation community (Gold in 2013 and 2011, Bronze in 2009). He is actively recruiting MSc students, PhD students, and post-docs with funded positions, indicating an expanding research program at Ben-Gurion University. His GitHub profile shows active development of EC-KitY, a scikit-learn-compatible Python toolkit for evolutionary computation.

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Antonio FilieriView profile

Visiting Associate Professor

Max Planck Institute for Security and PrivacyGermany

Antonio Filieri is a Senior Applied Scientist at Amazon Web Services (AWS) and holds a Visiting Associate Professor position at the Department of Computing, Imperial College London. Previously, he was a tenured Associate Professor at Imperial College London (2022-2024) and Assistant Professor (2016-2022), and served as Assistant Professor at the University of Stuttgart between 2013 and 2015. His academic career spans over a decade with significant contributions to software engineering research. Dr. Filieri's research focuses on formal mathematical methods for software design, verification, self-adaptation, and security. His primary research areas include static analysis, privacy, and automated test generation for security; exact and approximate methods for probabilistic program analysis; control theory for adaptive software; quantitative verification and model checking; and runtime-efficient and incremental verification. His work bridges theoretical foundations with practical applications in industry settings, particularly in cloud computing and security domains. His recent publications demonstrate a strong focus on probabilistic methods for software analysis, security testing, and performance modeling. The research trends show increasing integration of formal methods with machine learning techniques, particularly in test oracle generation and neural network analysis. There's also a clear emphasis on scalability and practical applicability of verification techniques to real-world systems like serverless computing and microservices architectures. Dr. Filieri has received numerous prestigious awards for his contributions: Best Student Paper Award (2025) for 'Robust Probabilistic Model Checking with Continuous Reward Domains' ACM Distinguished Paper Award (2023) for 'Sibyl: Improving Software Engineering Tools with SMT Selection' Best Paper Award (2022) for 'Enhancing Performance Modeling of Serverless Functions via Static Analysis' Best Artifact Award (2017) for 'Self-adaptive video encoder: comparison of multiple adaptation strategies made simple' Most Influential Paper Award (awarded at SEAMS 2025) for 'Software Engineering Meets Control Theory' ACM SigSoft Distinguished Paper Award (2011) for 'Run-time Efficient Probabilistic Model Checking' Dr. Filieri has advised several PhD students including Donato Clun (2024), Runan Wang (2024), and Xiaotong Ji (expected 2025). His advising focuses on probabilistic program analysis, automated testing, and security verification. His research has been supported by significant grants from both academic and industry sources, enabling collaborations across multiple institutions and contributing to advancements in software engineering practices. While specific lab information isn't prominently featured in the provided materials, Dr. Filieri's work suggests strong connections with research groups focused on formal methods, software verification, and adaptive systems at both Imperial College London and AWS. His research often involves interdisciplinary collaboration between theoretical computer science and practical software engineering challenges.

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Ding LiView profile

Assistant Professor

Max Planck Institute for Security and PrivacyGermany

Ding Li is an Assistant Professor in the School of Computer Science at Peking University. He holds a Ph.D. in Computer Science from the University of Southern California (USC) and a B.S. from Peking University. His research focuses on program analysis, energy optimization for mobile applications, and security, with publications in top conferences including ICSE, FSE, and ASE. His research interests span: Program Analysis : Techniques to optimize mobile application energy consumption. System Security : Identifying vulnerabilities in Android apps and WebAssembly binaries. Cloud/Edge Computing : Enhancing serverless computing efficiency and federated learning security. Dr. Li's recent work explores the integration of large language models into pointer analysis and automated optimization of resource inefficiencies. His publications demonstrate a consistent focus on practical system optimizations and security enhancements across mobile, cloud, and machine learning domains. Awards: Viterbi Undergraduate Research Mentoring Award (2014)

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