Find Academic Supervisors

Andrea ArcuriView profile

Professor

• Software Testing
• Software Engineering
• Cloud Computing
• +6 more

Andrea Arcuri is a Professor at the School of Economics, Innovation and Technology within Kristiania University of Applied Sciences . His research focuses on Software Testing , Software Engineering , and Cloud Computing , with a particular emphasis on automated testing techniques for web APIs. Specialized in RESTful, GraphQL, and RPC API fuzzing Developer of the open-source EvoMaster testing tool Pioneer in integrating evolutionary algorithms and symbolic execution for test generation Active in bridging academic research with industrial software testing practices His recent publications show a strong focus on Search-Based Software Testing (SBST) , Automated Test Generation , and Industrial Adoption of Testing Technologies . He has contributed extensively to improving testability through mock generation and database handling in API testing. While no formal scientific awards are listed in the public records analyzed, his work has been consistently published in top-tier software engineering venues since 2013. The articles demonstrate increasing sophistication in fuzzing techniques, with recent extensions to handle complex dependencies like MongoDB and SQL databases.

• Automating Software Engineering Tasks
• Mining Software Repositories
• Program Analysis
• +9 more

Univ.-Prof. Martin Pinzger is a Professor at the Department of Informatics Systems, Alpen-Adria-Universität Klagenfurt. He serves as Head of Department and Member of the Senate, actively contributing to academic governance. Research Focus: Automating Software Engineering Tasks, Mining Software Repositories, Program Analysis, Software Evolution and Visualization Recent Work: Developing tools for API evolution analysis, cybersecurity AI (CAI), robotics benchmarking (RobotPerf), and dependency validation His research combines empirical studies with tool development for software maintenance and security. Current projects address challenges in REST API breaking changes, cloud security certifications, and robotic system performance evaluation. Publications since 2023 demonstrate continued engagement with topics spanning AI-driven code segmentation, microservice API evolution, and cybersecurity tool development. Key trends include cross-disciplinary applications of NLP to software engineering and security-focused tool creation. Contact: martin.pinzger@aau.at

• Cyber-physical system security
• Threat modelling
• Critical infrastructure resilience
• +3 more

Dr. Carmen Cheh is a Research Scientist in the Department of Computer Science at the University of Illinois at Urbana-Champaign. She holds a Ph.D. in Computer Science from UIUC and a Bachelor of Computing (Hons) from the National University of Singapore. Her research focuses on cyber-physical system security, threat modeling, and critical infrastructure resilience. She has served as Co-Principal Investigator on two major grants: the 2023-2024 project on threat modeling for government systems and the 2022-2025 initiative on real-time fraud detection in e-commerce platforms. Her work bridges theoretical computer security with practical applications in critical infrastructure protection. Dr. Cheh has contributed to tools like CyberSAGE, which aids in automated security argument evaluation, and frameworks for detecting business logic flaws in software systems. She collaborates extensively with industry and government entities to advance cybersecurity practices in both digital and physical domains. Education: Ph.D., Computer Science, University of Illinois at Urbana-Champaign Bachelor of Computing (Hons), National University of Singapore Her research interests emphasize real-world security challenges in interconnected systems, including automated threat modeling, vulnerability discovery in business logic, and compliance frameworks for financial services. She has pioneered constraint-based methodologies for identifying security flaws in complex systems and developed novel approaches to insider threat detection using physical access data. Recent work explores the intersection of machine learning and cybersecurity in fraud detection systems. Her publications span top venues like ACM Transactions on Modeling and Computer Simulation, IEEE Secure Development Conference, and the IEEE International Conference on Computer Communications. Collaborations include projects with institutions like Argonne National Laboratory and the National Science Foundation.

Gabriele BavotaView profile

Associate Professor

• Software Quality
• Empirical Software Engineering
• Mining Software Repositories
• +3 more

Gabriele Bavota is an Associate Professor at the Software Institute of Università della Svizzera Italiana (USI) in Lugano, Switzerland. He leads the SEART (Software Engineering Advanced Research Team) group and serves as Principal Investigator for the DEVINTA ERC starting grant focused on developer intelligence through mining software artifacts. Dr. Bavota's research spans Software Quality, Empirical Software Engineering, and Mining Software Repositories. His work has evolved from foundational studies on code smells and technical debt to cutting-edge research at the intersection of artificial intelligence and software development. He has made significant contributions to understanding API usage patterns, software quality metrics, and developer behavior through empirical studies of large software repositories. His recent publications reveal a strong focus on AI-assisted software development, with extensive research examining code generation, code summarization, and code review automation using large language models. He has also expanded his research to include quality assurance in game development (detecting game stuttering and low engagement events) and voice user interface testing. His work consistently bridges theoretical insights with practical applications for software developers. ACM SIGSOFT Distinguished Paper Award for API compatibility research (MSR 2019) ACM SIGSOFT Distinguished Paper Award for Hugging Face model documentation study (ICPC 2024) ACM SIGSOFT Distinguished Artifact Award for deep learning fault taxonomy (ICSE 2020) As an active member of the software engineering research community, Dr. Bavota serves on program committees for major conferences including ICSE, ASE, FSE, and MSR. He has held leadership roles such as Program Co-Chair for ICSME 2023 and Vision/Reflection Track Co-Chair for ICSE. His SEART research group develops practical tools like the SEART Data Hub that streamline large-scale source code mining and preprocessing for empirical software engineering research.

Andrea MorichettaView profile

Associate Professor

• Blockchain Technology
• Smart Contracts
• Business Process Management
• +4 more

Andrea Morichetta is an Associate Professor at the University of Camerino (UNICAM). His research focuses on blockchain technology, smart contracts, and business process management. He explores the integration of blockchain with choreography-based systems, model-driven engineering, and process mining. His work addresses challenges in smart contract testing, distributed systems coordination, and auditability in decentralized applications. Key research areas include: Blockchain-based execution frameworks for BPMN choreographies Mutation testing strategies for Solidity smart contracts Decentralized identity systems using blockchain Event log analysis for Ethereum applications His publications highlight advancements in: Smart contract security and testing methodologies Choreography-driven architectures for IoT and MLOps Formal analysis of business process collaborations He contributes to international conferences and workshops on blockchain, enterprise modeling, and business informatics research. His work bridges theoretical foundations with practical implementations in distributed systems and process automation.

Yann-Gaël GuéhéneucView profile

Professor

• Software Engineering
• IoT Systems
• Static and Dynamic Analyses
• +4 more

Yann-Gaël Guéhéneuc is a Professor at Concordia University's Department of Computer Science and Software Engineering. He leads the Ptidej Team, focusing on software engineering methodologies, IoT systems, and game engine architecture analysis. His research emphasizes static/dynamic analyses, service-oriented architectures, and machine learning design patterns. Current Affiliations: Concordia University (Full-time Professor) Ptidiej Team Lead Research Interests: Specializes in IoT system testing, microservices architecture, game engine design patterns, and anti-pattern detection in multi-language systems. His work bridges theoretical software engineering principles with practical industrial applications, particularly in legacy system modernization and machine learning system design. Recent Trends in Publications: Focuses on IoT testing methodologies, machine learning architecture patterns, and service-oriented system transformations. His 2025 works advance IoT system taxonomy and game engine analysis techniques. Advising: Supervises MASc and PhD programs in Software Engineering and Computer Science Labs/Teams: Ptidej Team develops software tools for system analysis (e.g., Magnet, SyDRA)

• Runtime Verification
• Formal Methods
• Concurrency Theory
• +7 more

Adrian Francalanza is a Professor in the Department of Computer Science at the Faculty of Information and Communication Technology, University of Malta. His research is centered on formal methods, runtime verification, and concurrency, with a focus on monitorability and distributed systems. His research interests include: Runtime Verification and Monitor Synthesis Session Types and Protocol Safety Concurrency and Actor-Based Systems Branching and Linear-Time Temporal Logics Probabilistic and Decentralized Monitoring Formal Tools for Cyber-Physical and Distributed Systems The recent publications highlight a strong trend in theoretical and practical advances in monitorability, especially for branching-time and probabilistic systems. His work bridges theory with implementation, often resulting in tools like STMonitor and DetectEr. There is a clear emphasis on session types, runtime enforcement, and the verification of communication protocols in real-world systems such as REST APIs and SMTP. Scientific awards include: Distinguished Paper Award at ECOOP 2025 Best Paper Award at DisCoTec 2022 He has been actively involved in advising and organizing major academic events. He served as Program Chair for GandALF 2024 and 2025, FORTE 2024, and VORTEX workshops. He led a three-year project funded by Rannis on Theoretical Foundations for Monitorability in collaboration with Reykjavik University. He has received grants and recognition for developing practical tools such as DetectEr and STMonitor, which support runtime monitoring of Erlang and session-typed systems. He is associated with several research teams and labs, including: Runtime Verification and Monitorability Research Group at University of Malta Collaborators on the DetectEr project Developers of STMonitor and polyLarva tools International collaborators at Reykjavik University and beyond

• Software Engineering
• Software Testing
• Program Analysis
• +4 more

Alessandro Orso is the Dean and Professor of the University of Georgia College of Engineering. Previously, he served as a professor at Georgia Institute of Technology, where he directed the Scientific Software Engineering Center and held leadership roles, including interim dean of the College of Computing (2023–2024). He earned his Ph.D. and master’s in computer science and electrical engineering from Politecnico di Milano, Italy. Orso’s research focuses on software testing, program analysis, and debugging, with applications in improving software reliability and security. His work includes developing automated testing tools (e.g., AutoRestTest), methodologies for scientific software engineering, and techniques for program debloating. His research has secured funding from agencies and industry partners like Google, IBM, and Microsoft, including a $11M grant from Schmidt Futures. His scientific awards include being a Distinguished Member of the ACM and IEEE Fellow. He advocates for innovative education, such as Georgia Tech’s Online Master of Science in Computer Science and his virtual software engineering course. His publications span automated testing, API analysis, and security, reflecting his commitment to advancing both academic research and practical software solutions. Orso’s leadership includes directing the Scientific Software Engineering Center, which pioneers methodologies for scientific software improvement and trains a new generation of engineers. His career blends academic excellence with impactful industry collaborations, driving advancements in software engineering practices.

• Software Engineering
• Software Testing
• Program Analysis
• +4 more

Alessandro (Alex) Orso is the Dean and Professor at the University of Georgia College of Engineering , starting in 2025. Previously, he spent 25 years at Georgia Institute of Technology , where he served as a Professor in the College of Computing , Director of the Scientific Software Engineering Center , and Associate Dean for Off-Campus and Special Initiatives . Education: Ph.D. in Computer Science – Politecnico di Milano, Italy M.S. in Electrical Engineering – Politecnico di Milano, Italy B.S. in Electrical Engineering – Politecnico di Milano, Italy Research Focus: Alex Orso is a leading expert in software engineering , with a focus on software testing , program analysis , and debugging . His work aims to improve software reliability, security, and trustworthiness , and has been validated on real-world systems. He has led initiatives to integrate AI and large language models into testing workflows, particularly for REST APIs and mobile applications . Scientific Recognition: Distinguished Member of the Association for Computing Machinery (ACM) Fellow of the Institute of Electrical and Electronics Engineers (IEEE) ISSTA Impact Paper Award (2021) Research Funding & Leadership: Orso has secured major funding from Google, IBM, Microsoft , and government agencies. In 2021, he led the acquisition of $11 million from Schmidt Futures to establish the Scientific Software Engineering Center at Georgia Tech, where he served as inaugural director. Teaching & Innovation: He was an early advocate of Georgia Tech’s Online Master of Science in Computer Science (OMSCS) and has taught a virtual software engineering course since its launch in 2014.

Sergio MaffeisView profile

Associate Professor

• Computer Security
• Machine Learning
• Programming Languages
• +3 more

Dr. Sergio Maffeis is an Associate Professor and Senior Lecturer in Computer Security at the Department of Computing, Imperial College London, within the Faculty of Engineering. He leads the Security & Machine Learning Lab and holds affiliations with the Engineering Secure Software Systems and Programming Languages research groups. His research focuses on cyber security, machine learning, formal methods, and programming languages. Maffeis earned his Ph.D. from Imperial College London and an MSc from the University of Pisa, Italy. Research interests include adversarial machine learning, intrusion detection systems, and secure software development. His work bridges theoretical foundations with practical applications, such as detecting Advanced Persistent Threats (APTs) and improving ML model robustness against adversarial attacks. Recent publications highlight advancements in combining machine learning with security, including KnowML for knowledge graph-enhanced ML-NIDS and APIRL for REST API fuzzing. He has supervised numerous PhD students, including Abdullah Aldaihan (Large Language Models for Cyber Threat Detection) and Fahad Alotaibi (Concept Drift in ML-based Security). Grants include EPSRC/GCHQ funding for certified verification of client-side web programs and GCHQ grants for web security and lab infrastructure. His lab collaborates on projects like the Security & Machine Learning Lab, exploring cutting-edge topics in secure AI and network defense.

Justus BognerView profile

Assistant Professor

• Microservices
• Artificial Intelligence
• Software Engineering
• +3 more

Justus Bogner is an Assistant Professor at the Faculty of Science, Vrije Universiteit Amsterdam, affiliated with the Software and Sustainability (S2) department and the Network Institute. His research focuses on microservices architecture, AI/ML system sustainability, and software engineering practices. He teaches courses like Service Oriented Design and Software Design. Research Interests: Bogner’s work explores the intersection of AI and sustainable software engineering, including energy-efficient microservices, explainable AI (XAI), and MLOps architectures. He emphasizes empirical studies, systematic mappings, and controlled experiments to address challenges in software quality, design patterns, and trade-offs between performance and environmental impact. Awards: Best Presentation Award (2021) Distinguished Artifact Award (2024) Distinguished Artifact Award (2024) Distinguished Paper Award (2024) Grants/Advising: His work has been supported by grants focusing on empirical software engineering and sustainable AI. He collaborates on datasets analyzing technical debt in AI systems and green AI practices.

• Empirical software engineering
• Software architecture
• Design patterns
• +8 more

Justus Bogner is a researcher at the Institute of Software Engineering (ISTE) and leads the division for Software Engineering for AI- & Microservice-Based Systems (SE4AI&MS) at the University of Stuttgart. His work focuses on empirical software engineering , microservices , AI-based systems , and software evolvability . He has contributed extensively to understanding architectural migration, technical debt in AI systems, and quality assurance methodologies. His research spans various subfields including service-oriented architecture , RESTful API design , design patterns , and software maintainability metrics . Recent publications highlight empirical comparisons between JavaScript and TypeScript, frameworks for microservice migration, and systematic studies on AI engineering challenges. Bogner's work often bridges academic research with industry practices through collaborations with IEEE and Springer, though no specific awards or student advisories are mentioned in the provided text.

Alessandro OrsoView profile

Professor

• Software Engineering
• Software Testing
• Program Analysis
• +3 more

Alessandro (Alex) Orso is a Professor in the School of Computer Science and Interim Dean of the College of Computing at Georgia Institute of Technology. He holds an M.S. in Electrical Engineering (1995) and a Ph.D. in Computer Science (1999) from Politecnico di Milano, Italy. Since 2000, he has been a faculty member at Georgia Tech. Affiliations: School of Computer Science, Scientific Software Engineering Center, Center for Experimental Research in Computer Systems (CERCS), and Online Master of Science Computer Science (OMSCS). Research Focus: Software engineering with emphasis on testing, program analysis, and improving software reliability/security through formal methods and tools. His research has been funded by DARPA, NSF, IBM, and Microsoft, among others. He co-founded the Scientific Software Engineering Center to advance methodologies for high-performance scientific software. Orso is a Distinguished Member of the ACM and an IEEE Fellow. Key contributions include developing techniques for automated REST API testing, program debloating, and cross-browser web application testing. His work bridges theory and practice, emphasizing real-world system validation. Awards: Four impact awards: ISSTA (2017, 2021), ASE (2020), IBM Haifa (2013) Editorial roles: ACM TOSEM, IEEE TSE Program chairs: ISSTA 2010, FSE 2014, ICSE 2017 Advising & Grants: Supervised over 40 students (PhD, Master's, undergrad). Secured funding from government/industry partners. Tools developed include AutoRestTest, Barista, and X-PERT. Labs/Teams: Leads the Arktos Research Group, focusing on software testing, analysis, and tool development. Collaborates with industry and government on applied research projects.

Manish MotwaniView profile

Assistant Professor

• Software Engineering
• Automated Program Repair
• Automated Testing
• +4 more

Manish Motwani is an Assistant Professor at the School of Electrical Engineering and Computer Science, Oregon State University. His research focuses on automating software engineering practices to improve software quality, particularly in high-performance computing (HPC), REST APIs, and natural language-driven program repair. He leads the Advanced Software Engineering Research (ANSWER) lab, which is part of the Software Engineering and Human-Computer Interaction group. Education: Ph.D. in Computer Science (University of Massachusetts Amherst), Postdoctoral Fellow (Georgia Institute of Technology) Motwani's research bridges empirical analysis of software repositories with automated techniques for testing, debugging, and program repair. Key projects include: Automated Testing for HPC Applications OpenAPI Specification Generation via Static Analysis High-Quality Patch Validation Using Bug Reports JaRFLy Framework for Patch Evaluation Swami Tool for Natural Language Test Oracles RAFL and Blues Fault Localization Techniques His work addresses critical challenges such as patch overfitting, HPC bug detection, and semantic search for real-world defects. He has published in top venues like ICSE, TSE, and EMSE, and holds two U.S. patents for automated requirements and regulatory compliance tools. At Oregon State, Motwani actively mentors and seeks motivated PhD students interested in software testing, debugging, and program repair for HPC and AI/ML applications. He previously contributed to requirements engineering at Tata Research Development and Design Centre in India.

Gregor HenzeView profile

Professor

• Building Energy Systems
• Model Predictive Control
• Reinforcement Learning
• +5 more

Gregor Henze is an endowed professor at the University of Colorado Boulder and a Contingent Worker at the National Renewable Energy Laboratory (NREL) , with a joint appointment since 2013. His expertise spans building energy systems , model predictive control , and reinforcement learning applications in architectural engineering. Education: Master of Mechanical Engineering, Oregon State University Master of Energy and Process Engineering, Technical University of Berlin PhD in Civil Engineering, University of Colorado Boulder Henze’s research focuses on advanced controls for building energy systems , including sensor fusion algorithms , district energy systems , and building-to-grid integration . He has authored over 200 publications and holds three patents , with recent work emphasizing machine learning and real-time optimization . Recent publications highlight reinforcement learning in building control (2023) and optimization frameworks for district thermal energy systems (2022). His work intersects energy analytics , occupancy detection , and smart building technologies . Scientific Awards: 4 Best Paper Awards Research and Commercialization Award from Colorado Cleantech Industry Association (2011) Fellow of the Renewable and Sustainable Energy Institute Henze is a co-founder and Chief Scientist of QCoefficient, Inc. , developing real-time control solutions for grid-interactive buildings. He served as the Fulbright Distinguished Chair at CSIRO, Australia (2022).