Find Academic Supervisors

Mitchell OlsthoornView profile

Assistant Professor

• Network Security
• Search-based Software Engineering
• Pen-testing
• +5 more

Mitchell Olsthoorn is an Assistant Professor in the Software Engineering Research Group (SERG) at Delft University of Technology. He is also a member of the Computational Intelligence for Software Engineering lab (CISELab) and the Delft Blockchain Lab (DBL). His academic career is built on a strong foundation from Delft University of Technology, where he earned all his degrees. Mitchell's research interests span a diverse range of topics including Network Security, Search-based Software Engineering, Pen-testing, Computational Intelligence, Software Testing, Security Testing, Fuzzing, and Blockchain. His work demonstrates a strong focus on applying computational intelligence techniques to solve complex software engineering problems, particularly in the areas of test case generation and security testing. His publication record shows a consistent research trajectory with a focus on developing innovative testing frameworks for various programming languages and blockchain technologies. His work bridges the gap between theoretical research and practical applications, with tools developed for JavaScript, Kotlin, and blockchain platforms. Cum laude distinction (top 5% in Netherlands) Mitchell actively contributes to the academic community through conference organization and program committee roles. His current position as Hot-off-the-Press Track Co-Chair for SSBSE 2025 demonstrates his growing recognition in the software engineering research community. He also serves on program committees for major conferences including ISSTA, ICST, and ASE. Mitchell maintains active research laboratories including the Computational Intelligence for Software Engineering lab (CISELab) and the Delft Blockchain Lab, where he continues to advance research in software testing and security.

• Software and systems engineering
• Empirical studies
• Software quality
• +3 more

Stefan Wagner is a Professor at the Institute of Software Engineering (ISTE) and leads the Empirical Software Engineering Group at University of Stuttgart , Germany. His research focuses on software and systems engineering with emphasis on empirical studies , software quality , human aspects in software engineering , automotive software , and software engineering for AI-based systems . Research Trends : Recent publications highlight his work in automotive software architecture centralization (2023) mutation testing in industrial contexts (2022) GitHub communication channel analysis (2022) microservices/DevOps adoption in cyber-physical systems (2022) code security feedback systems (2022) empirical studies of agile team leadership (2021) automated security requirements in CPS (2021) Methodological Contributions : He has developed scenario-based evolvability analysis methods, empirical frameworks for citation drivers in SE, and systematic mapping approaches for AI-based system engineering challenges and automotive security countermeasures.

• Typography
• Type Design
• Font Production
• +5 more

Lucas de Groot is a Professor for Type Design at the Design Department, University of Applied Sciences Potsdam. He founded FontFabrik and LucasFonts, and is renowned for contributions to type design, interpolation theory, and Python-scripted OpenType development. Active in type design since the 1980s Specializes in subpixel rendering and cleartype hinting Collaborated with institutions like Sun Microsystems and Der Spiegel Developed typefaces for multilingual environments and media-specific applications Research interests include: Typography and type design Interpolation theory in font development Python scripting for OpenType Subpixel rendering and cleartype hinting Language-specific typography Anisotropic interpolation for scalable fonts Publications focus on typeface systems, multilingual fonts, and screen-optimized typography. His work spans from the 1990s to the early 2000s, emphasizing technological integration and design innovation.

Stefan GuglerView profile

Researcher

• Computational Quantum Chemistry
• Materials Science
• Machine Learning
• +3 more

Dr. Stefan Gugler is a Postdoctoral Researcher at the Technical University of Berlin (TU Berlin), affiliated with the Berlin Institute for the Foundations of Learning and Data (BIFOLD) and the Machine Learning Group led by Prof. Dr. Klaus-Robert Müller. His research focuses on integrating machine learning methods, such as diffusion models and Gaussian processes, into theoretical chemistry to address challenges like molecular similarity, reaction networks, and catalyst design. He holds a PhD in quantum chemistry from ETH Zurich (2023), where he developed machine learning approaches for dispersion interactions, and a Master’s degree in computational inorganic chemistry from MIT (2018). His work has been recognized with an MSDE Award for his thesis on transition metal complexes. Gugler’s contributions include open-source software tools like qcscine/readuct and qcscine/puffin , advancing computational chemistry and machine learning workflows. Education: PhD in Quantum Chemistry, ETH Zurich (2023) Master’s in Computational Inorganic Chemistry, MIT (2018) Interdisciplinary Sciences (BSc/MSc), ETH Zurich (2016–2018) Research Interests: Molecular similarity and chemical reaction networks Diffusion models and generative AI for chemistry Machine learning in quantum chemistry and materials science Explainable AI (XAI) for scientific applications Awards: MSDE Award (2018), MIT Labs/Teams: Active contributor to BIFOLD and the qcscine open-source project, focusing on machine learning-driven computational chemistry tools.

• Computer Science
• Software Engineering
• Biometrics
• +2 more

Asma Shakil is a researcher in computer science with a focus on software engineering, biometrics, and education technology. Her work spans empirical studies on code readability, pedagogical strategies for capstone courses, and biometric signature verification systems. She collaborates with scholars across institutions, contributing to conferences like ITiCSE, ACE, and CHI. 2025: Co-authored a paper on team-based capstone projects. 2024: Authored multiple studies on student engagement and capstone course design. 2019: Explored gaze-based code navigation in CHI proceedings. 2008-2010: Pioneered offline signature verification research with Hidden Markov Models. Research Interests: Asma's work bridges software engineering practices, biometric authentication, and educational innovation. Her recent papers emphasize scalable teaching methods and team-based learning in computing education, while her earlier contributions focus on statistical modeling for signature verification. Publication Trends: Her research has evolved from biometrics to education technology, with a recurring emphasis on empirical validation. Key subfields include functional decomposition, code navigation, and pedagogical interventions for student engagement. Collaborations: Regular co-authors include Paul Denny, Sara Hooshangi, and Ewan D. Tempero, indicating sustained partnerships in education technology research.

Tina SeufertView profile

Professor

• Educational Psychology
• Instructional Science
• Self-Regulated Learning
• +7 more

Prof. Dr. Tina Seufert is a full Professor for Research on Learning and Instruction at the University of Ulm, affiliated with the Faculty of Engineering, Computer Science and Psychology. Since 2022, she has served as Scientific Director of the School of Advanced Professional Studies (SAPS). She previously held leadership roles including Dean of the Faculty (2013–2016) and Director of the Institute for Psychology and Education (2009–2013). Research Interests: Self-regulated learning and cognitive load Promoting knowledge acquisition with multiple representations (multimedia research) Instructional Design for Online-based Continuing Education Influence of learner characteristics Learning with VR Promotion of learning strategies Measurement of cognitive load Her recent publications show a strong focus on integrating cognitive load theory with self-regulated learning, refining measurement tools, and enhancing multimedia instruction through disfluency, coherence training, and individual differences. Her work bridges theoretical psychology and practical instructional design, particularly in digital and continuing education contexts. Scientific Service and International Engagement: Assistant Editor, Instructional Science (since 2018) Member, European Association for Learning and Instruction (EARLI) since 1998 Coordinator, EARLI SIG 6 'Instructional Design' (2007–2011) Active participant in program and organizing committees for EARLI SIG conferences on Text and Picture Comprehension and Instructional Design She advises graduate students and leads research in instructional psychology, though specific advisees are not listed. Her work is supported by academic grants implied through publication output and leadership roles. She leads a research group focused on learning and instruction, contributing significantly to the development of evidence-based teaching practices.

Andrea Di SorboView profile

Assistant Professor

• Software Maintenance and Evolution
• Empirical Software Engineering
• Mining Software Repositories
• +3 more

Andrea Di Sorbo is an Assistant Professor at the University of Sannio, Italy, specializing in software engineering with a focus on software maintenance, evolution, security, and blockchain applications. His academic career demonstrates strong engagement with the international software engineering community through publications and service roles. Dr. Di Sorbo received his Ph.D. in Information Technology from the University of Sannio in 2018, followed by a postdoctoral fellowship at the same institution. His educational background established the foundation for his research in empirical software engineering approaches. His research interests span multiple critical areas in modern software development, with particular emphasis on Software Maintenance and Evolution , Empirical Software Engineering , and Software Security and Privacy . Additional specializations include Mining Software Repositories , Blockchain-oriented Software Engineering , and Text analysis and summarization of Software artifacts . These interests reflect both traditional software engineering concerns and emerging challenges in blockchain and security domains. Analysis of his publication record from 2020-2025 reveals a clear evolution toward blockchain applications and security concerns, while maintaining empirical methods as his research foundation. His work bridges theoretical software engineering principles with practical applications in UAV systems, smart contracts, and fairness in complex software systems, demonstrating both breadth and increasing specialization in critical emerging areas. Dr. Di Sorbo has served as a guest editor for Frontiers in Big Data and Information and Software Technology journals, and as a reviewer for major software engineering journals including TSE, EMSE, JSS, IST, SCP, and JSEP. His service to the academic community is substantial, with program committee membership for prestigious conferences including ICSE, ASE, ARES, MOBILESoft, and SEAA. He has also served as Workshop Co-Chair for NLBSE 2023 and Session Chair for multiple NLBSE events, demonstrating leadership in specialized software engineering communities.

Jacques KleinView profile

Professor

• Software Engineering
• Software Security
• Program Analysis
• +6 more

Prof. Dr. Jacques Klein is a Chief Scientist (Full Professor) and Co-head of the TruX Research Group at the SnT Centre (Security and Trust Centre) of the University of Luxembourg. With a career spanning over 15 years at the university, he has progressed from Research Scientist (2010-2015) to Senior Research Scientist (2015-2019), Associate Professor (2019-2022), and finally to Full Professor in 2023. His research focuses on three main areas: program analysis applied to mobile security, software debugging (particularly bug localization and program repair), and NLP/AI for software engineering. He has supervised numerous PhD students and has acquired over 5 million euros in research funding through projects from the Luxembourg Research Agency, European Commission, and industrial partnerships. Prof. Klein is an active member of the software engineering research community, serving as General Co-Chair of ASE 2023 and MobileSoft 2025, and as a steering committee member for ISSTA, ASE, and MobileSoft. He is also an Editorial Board Member of the Springer Empirical Software Engineering Journal since 2021. His recent publications demonstrate a strong focus on applying AI and machine learning techniques to software security challenges, particularly in the Android ecosystem, with significant contributions to malware detection, code analysis, and privacy compliance. His work has been recognized with multiple prestigious awards including the ICSE 10-year most influential paper award and the PLDI Most Influential Paper Award. Member of the Institut Grand-Ducal - Section des Sciences (since June 2024) Principal Investigator on numerous research projects Extensive service on program committees for major software engineering conferences He teaches courses on static program analysis, software vulnerabilities, and security analysis at the Master's level, and has made significant contributions to the Android research community through the AndroZoo dataset containing over 24 million Android applications.

Mohamed Wiem MkaouerView profile

Associate Professor

• Software Engineering
• Refactoring
• Artificial Intelligence
• +7 more

Mohamed Wiem Mkaouer is an Associate Professor of Software Engineering in the Golisano College of Computing and Information Sciences at Rochester Institute of Technology (RIT). He serves as the principal investigator of the SMILE (Software Maintenance and Intelligent Evolution) Research Lab, which focuses on designing intelligent algorithms to tackle software engineering problems. Dr. Mkaouer has published over 130 peer-reviewed papers in top venues including TSE, TOSEM, EMSE, ICSE, FSE, CHI, and ASE, and has secured $1.5 million in externally funded projects as PI/Co-PI. PhD in Computer and Information Science, 2016, University of Michigan MS in Computer Science, 2010, University of Geneva (Switzerland) BS in Computer Science, 2007, University of Tunis (Tunisia) Dr. Mkaouer's research spans the intersection of Software Engineering and Artificial Intelligence, with particular focus on software quality assurance, systems refactoring, and the application of search-based techniques. His work increasingly explores the integration of large language models in software development processes, examining how AI tools like ChatGPT impact developer workflows, code quality, and refactoring practices. His research often employs empirical methods, mining software repositories, and conducting large-scale studies of developer behavior. Analysis of Dr. Mkaouer's recent publications reveals a strong trend toward investigating AI-assisted software development, particularly focusing on how developers interact with large language models for code refactoring and quality improvement. His work bridges traditional software engineering concerns with emerging AI capabilities, examining both infrastructure-as-code quality and mobile application development challenges. His research methodology typically combines empirical studies of developer practices with the development of intelligent tools to support software maintenance. Recipient of 5 best-paper/presentation awards RIT GCCIS Best Emerging Researcher Award (2020) Dr. Mkaouer actively mentors a diverse group of students at multiple levels, from undergraduate to PhD candidates, through the SMILE Research Lab. His externally funded projects demonstrate the practical relevance of his research to industry needs. He also contributes significantly to the software engineering community through service on program committees for major conferences including ASE, ICSE, and ICSME, where he frequently serves in leadership roles for tracks related to software maintenance, refactoring, and AI in software engineering. The SMILE Research Lab, under Dr. Mkaouer's leadership, maintains strong industry connections and collaborates with researchers worldwide. The lab's work has practical implications for improving software quality, reducing technical debt, and enhancing developer productivity through intelligent tooling and evidence-based practices.

Fiorella ZampettiView profile

Researcher

• Experimental Software Engineering
• Continuous Integration and Delivery
• Static Analysis Tools
• +4 more

Fiorella Zampetti is a researcher at the University of Sannio, Italy, specializing in empirical software engineering with a focus on continuous integration and delivery, static analysis tools, mining software repositories, and software maintenance and evolution. Her work bridges theoretical research with practical applications in real-world software development environments. Her research interests span multiple critical areas of modern software engineering, with particular emphasis on Experimental methodologies for evaluating software engineering practices Technical debt identification and management, especially in emerging domains like deep learning systems Continuous integration and delivery pipelines, including common anti-patterns and solutions Mining software repositories to extract valuable insights about development processes Software quality assessment through static analysis and empirical studies Analysis of her recent publications reveals an evolving research trajectory that has increasingly incorporated artificial intelligence and large language models into traditional software engineering concerns. Her 2023-2025 work shows a significant focus on how AI-generated code impacts software development practices, licensing concerns, and educational contexts. She has also maintained a strong thread of research on technical debt, particularly examining self-admitted technical debt across different software domains. Dr. Zampetti has been actively involved in the software engineering research community as a program committee member for major conferences including ASE, ICSE, ESEC/FSE, and ICSME. Her service on these committees demonstrates recognition by her peers as a subject matter expert in her research domains. Her research has practical implications for software development teams looking to improve their CI/CD practices, manage technical debt effectively, and understand the emerging challenges posed by AI-assisted development tools. She has conducted numerous empirical studies that provide evidence-based insights into software engineering practices across both open-source and industrial contexts.

• Software Engineering
• Human Aspects of Software Development
• Developer Well-being
• +3 more

Daniel Graziotin is Professor of Business Informatics and Digital Technologies at the University of Hohenheim. His research examines human aspects of software engineering, including developer well-being, emotional intelligence, and research methodologies. Research Focus: Graziotin investigates psychological factors in software development, including stress and emotional intelligence in developers, collaborative coding practices, and open science methodologies. His work bridges behavioral science and technical software engineering practices. Publications: Recent articles (2022-2025) focus on developer psychology, qualitative research methods in software engineering, GitHub collaboration patterns, and blockchain developer ecosystems. His research often employs longitudinal analyses and phenomenological approaches to understand developer experiences.

• Empirical Software Engineering
• Code Quality Analysis
• Software Maintenance
• +7 more

Rocco Oliveto is a Professor in the Department of Computer Science at the University of Salerno, Italy, with a distinguished research career spanning over two decades in empirical software engineering. His work bridges theoretical software engineering principles with practical applications, with recent expansion into healthcare informatics and machine learning applications. His research interests focus on code quality assessment, software maintenance practices, developer behavior analysis, and empirical studies of software engineering phenomena. He has made significant contributions to understanding code smells, bug prediction, API compatibility issues, and more recently, container technologies and smart contract analysis. His recent work demonstrates a strategic expansion into healthcare applications, leveraging software engineering techniques for medical diagnostics and rehabilitation systems. Oliveto's publication pattern shows consistent productivity with multiple high-impact publications each year across top venues including IEEE Transactions on Software Engineering, ACM Transactions on Software Engineering and Methodology, and Empirical Software Engineering journal. His recent articles (2023-2025) reveal a growing interest in applying software engineering techniques to healthcare domains while maintaining strong contributions to core software engineering topics. The research demonstrates sophisticated methodological approaches combining empirical studies with machine learning techniques. His collaborative network includes prominent researchers such as Simone Scalabrino, Gabriele Bavota, and Andrea De Lucia, with whom he has co-authored numerous high-impact publications. This collaboration spans both traditional software engineering topics and emerging interdisciplinary applications in healthcare.

Naser Al MadiView profile

Assistant Professor

• Eye Tracking
• Program Comprehension
• Human-Computer Interaction
• +3 more

Naser Al Madi is an Assistant Professor of Computer Science at Colby College, where he teaches core courses including Data Structures and Algorithms (CS231) and Software Engineering (CS321). His research integrates eye tracking with software engineering to enhance source code comprehension through analysis of developer behavior and eye movement patterns during software development. His educational background includes a PhD from Kent State University (2020), followed by a visiting research scholar position at Harvard University's School of Engineering and Applied Science and Schepens Eye Research Institute in 2023. Prior to joining Colby, he began his teaching career at Hamilton College where he taught Operating Systems and Wearable Technology courses. PhD, Kent State University, 2020 Visiting Research Scholar, Harvard University, 2023 Began teaching career at Hamilton College Dr. Al Madi's research focuses on the intersection of eye tracking technology and software engineering, particularly examining how developers comprehend source code through eye movement analysis. His work extends to Human-Computer Interaction applications in clinical rehabilitation settings and the impact of AI tools like GitHub Copilot on code readability and developer workflows. He maintains an active research blog discussing cognitive aspects of programming and regularly collaborates with undergraduate students on research projects. His recent publications analyze lexical similarity in identifier names, the readability of AI-generated code, and longitudinal eye tracking studies of developers progressing from novice to expert levels. These works collectively explore how cognitive processes affect software development practices and how tools can be designed to better support developer cognition. Dr. Al Madi is deeply committed to inclusive computer science education, advocating that 'anyone can become a computer scientist if they work hard' regardless of background. He actively mentors undergraduate researchers, emphasizing the importance of diversity in technology development to prevent exclusionary design patterns. His teaching philosophy integrates modern software engineering practices with critical analysis of AI tools, requiring students to understand and verify all AI-generated code rather than using it uncritically. Based in the Davis Science Center at Colby College, he maintains an active presence in the software engineering research community, serving on program committees for major conferences including ASE and FSE. His blog features practical career advice for students, including guidance on resume building, internship applications, and navigating the tech industry.

Ali MesbahView profile

Professor

• Software Engineering
• AI-driven Software Analysis
• Software Testing
• +5 more

Ali Mesbah is a Professor in the Department of Electrical and Computer Engineering at the University of British Columbia (UBC), where he leads the SALT lab. His research focuses on software engineering with emphasis on AI-driven software analysis, software testing, and software evolution. Previously, he was a Visiting Research Scientist at Google during 2017-2018. Dr. Mesbah received his BSc/MSc (2003) and PhD (2009) degree cum laude in Computer Science from the Delft University of Technology (TUDelft). After completing a postdoctoral fellowship with the Software Engineering Research Group at TUDelft and a Visiting Researcher position at Fujitsu Laboratories of America, he joined UBC in 2011. His research interests span software engineering with particular focus on AI-driven software analysis, software testing, software evolution, program comprehension, fault localization and repair. His work has significant applications in web application testing, JavaScript analysis, and automated program repair. He has pioneered techniques for testing modern web applications, analyzing JavaScript code, and leveraging AI for software maintenance tasks. His recent publications demonstrate a clear evolution toward integrating large language models with traditional program analysis techniques, focusing on test generation, bug repair, and understanding multi-hunk patches. His work bridges theoretical software engineering concepts with practical applications, particularly in web technologies and AI-assisted development. Amazon Research Award (2023) Killam Accelerator Research Fellowship (KARF) (2020) Killam Faculty Research Prize (2019) NSERC Discovery Accelerator (DAS) award (2016) ACM Distinguished Paper Awards at ICSE (2009, 2014) IEEE Distinguished Paper Award at ICST (2018) Best Paper Award at ESEM (2015) Best Paper Award at ICWE (2013) Dr. Mesbah has advised numerous PhD and MASc students, many of whom have gone on to positions at leading technology companies including Google, Amazon, Apple, Microsoft, and SAP. His research has been supported by various grants including the Amazon Research Award and NSERC funding. He leads the SALT lab at UBC, which focuses on software analysis, testing, and learning, with current research directions including AI-driven software engineering, web application testing, and program repair. The lab maintains active collaborations with industry partners and academic institutions worldwide.

Shing-Chi CheungView profile

Professor

• Software Engineering
• Program Analysis
• Software Testing
• +7 more

Shing-Chi Cheung is a Professor of Computer Science and Engineering at the Hong Kong University of Science and Technology (HKUST), School of Engineering. He founded the CASTLE research group and co-founded the International Workshop on Automation of Software Testing (AST) in 2006. His leadership includes serving as General Chair of FSE 2014 and chairing multiple APSEC conferences. His research focuses on software quality enhancement through program analysis, testing, debugging, and AI techniques, targeting Android apps, open-source software, deep learning systems, smart contracts, and spreadsheets. Current projects include metamorphic testing frameworks, binary analysis tools, and vulnerability detection systems for emerging technologies. His publication portfolio demonstrates consistent contributions to software engineering since 2016, with recent work emphasizing AI-integrated testing methodologies, smart contract security, and deep learning system reliability. Key trends show increasing focus on cross-language analysis, data visualization quality, and compiler-level verification for modern software stacks. Distinguished Member of the ACM Fellow of the British Computer Society Editorial board member: Science of Computer Programming (SCP), Journal of Computer Science and Technology (JCST) Former editorial board member: IEEE Transactions on Software Engineering (2006-2009), Information and Software Technology (2012-2015) Four patents in China and the United States Cheung actively mentors through the CASTLE research group and serves on program committees for major conferences including ICSE, ESEC/FSE, and ISSTA. His work bridges academic research with practical applications through industry collaborations and tool development. He has contributed to numerous workshops and symposia as steering committee member and program chair.