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
Tushar Sharma is an Assistant Professor in the Faculty of Computer Science at Dalhousie University, Canada. His research focuses on software engineering, particularly software quality, refactoring, technical debt, and the application of machine learning in software engineering (ML4SE). He leads the SMART Lab and is actively involved in projects related to Green AI and sustainable software development. PhD : Software Engineering, Athens University of Economics and Business, Greece (2019) MS : Computer Science, Indian Institute of Technology-Madras, India His research interests span software design and architecture, code and design quality, refactoring, technical debt, mining software repositories, and applied machine learning for software engineering. He is particularly interested in sustainable AI, green software engineering, and the use of large language models for code. His work bridges empirical studies with practical tool development to improve software maintainability and quality. His recent publications highlight a strong trend in code smell detection, refactoring automation, energy-aware AI, and the reliability of large language models in software engineering. He has developed tools like Designite and DPy and contributed datasets such as MaRV and DACOS, emphasizing empirical validation and reproducibility in software engineering research. Dean's Research Excellence Award Best Artifact Award, SCAM 2023 IEEE Senior Member Tushar Sharma has secured significant research funding, including an NSERC Discovery Grant for DevQOps, Mitacs Accelerate grants with industry partners, and contributions to the $154M Canada First Research Excellence Fund project. He actively mentors students and collaborates with industry. He leads the SMART Lab at Dalhousie and has organized workshops such as SATToSE 2018. He is also a founding developer of Designite, a widely used software design quality assessment tool.
Alexandru G. Bardas is an Associate Professor at the University of Kansas in the Department of Electrical Engineering & Computer Science (EECS) and the Institute for Information Sciences (I2S) . He received his PhD from Kansas State University under advisors Xinming (Simon) Ou and Scott A. DeLoach. His research focuses on cybersecurity from a systems perspective , including moving target defenses, security operations center (SOC) metrics, DevOps security, power grid cybersecurity, and defensive technologies for political activists. He explores UDP-based DDoS detection, DNS traffic analysis, and the intersection of AI with cybersecurity, emphasizing foundational knowledge over tool-specific training. Key research areas: Cybersecurity, Systems Security, Moving Target Defenses, SOC Metrics, DevOps Security Recent publications in ACSAC 2024 , USENIX Security 2024/2023 , and IEEE Security & Privacy 2022 Dr. Bardas has received significant recognition including: NSF CAREER Award (2022) for SOC automation Bellows Scholar (2021) at KU NSA SoS Honorable Mention (2023) He actively advises students across disciplines, with graduates now at Sandia National Laboratories , Blue Cross Blue Shield , and Pacific Northwest National Laboratory . Dr. Bardas participates in NSF grant reviews , serves on program committees for SOUPS and MILCOM , and leads outreach initiatives like the GenCyber Summer Camp .
Prof. Dr. Harald Ritz serves as Professor of Practical Computer Science, especially Business Informatics, at the Technical University of Central Hesse (THM) within the Department of Mathematics, Natural Sciences and Computer Science since 2003. He holds leadership roles as Chair of Examination Committees for B.Sc. and M.Sc. Business Information Systems and Spokesperson for the MNI department in the Business Informatics Working Group (AKWI). His educational background includes a Diplom in Business Informatics (Dipl.-Wirtsch.-Inform.) and doctorate (Dr. rer. pol.) from the Technical University of Darmstadt, following professional experience at SAP SI AG and a professorship at Heilbronn University of Applied Sciences. Ritz's research centers on AI-driven digital transformation for data-driven enterprises, with focus on the “Data to Decision” value chain encompassing Framing, Allocation, Analytics, and Preparation phases. His work integrates business intelligence, data warehousing, machine learning, and SAP ecosystems to address challenges in SME digitalization, operational IT management, and educational technology. Current projects emphasize AI applications in higher education, including intelligent tutoring systems and automated feedback mechanisms. Analysis of his 15 most recent publications reveals a consistent trajectory toward applied AI solutions in business contexts, particularly in intelligent chatbots for educational support, financial trading algorithms, and cloud-based data infrastructure. The research demonstrates increasing integration of no-code platforms, real-time analytics, and domain-specific AI applications across logistics, banking, and procurement sectors. No scientific awards were documented in the source materials. Professor Ritz actively supervises academic development through bachelor’s and master’s theses, doctoral research, and collaborative projects. Current initiatives include the “Winfy” AI chatbot (v4.0, 2025), AI-based feedback systems for educational content (Freiraum 2025 grant), the frits intelligent tutoring project with Prof. Kammer, and doctoral research on AI adoption in SMEs. His work bridges theoretical research with practical implementation in SAP environments and cloud platforms. He operates within THM’s MNI department infrastructure, collaborating through the Business Informatics Working Group (AKWI) and contributing to the Digital Classroom communication platform for online education.
Dr. Joonsang Baek is an Associate Professor at the School of Computing and Information Technology, University of Wollongong (since 2021). His research focuses on Cybersecurity , Cryptography , and Network Security , with notable contributions to digital signature revocation, attribute-based encryption, and privacy-preserving protocols. Member, Institute of Cybersecurity and Cryptology (since 2017) Supervision interests: Cybersecurity, Applied Cryptography, Network Security Research Highlights: Innovations in withdrawable signatures, secure cloud data sharing, and 5G authentication protocols. His work combines theoretical cryptography with practical applications in edge computing and AI-driven security systems. Grants: Led projects on ransomware datasets, dynamic access control, and TLS optimization. Collaborated with Data61, Discovery Projects, and industry partners on cybersecurity resilience initiatives. Collaborations: Frequent co-author with researchers like Willy Susilo, Cao Cao, and Xinyu Liu. Active in ACM Asia CCS, IEEE Transactions, and LNCS publications.
Jasmin Jahic is a Researcher at the Computer Architecture Group of the University of Cambridge, working under Timothy M. Jones. She holds a PhD in 'Supervised Testing of Embedded Concurrent Software' from the University of Kaiserslautern (2020) and has extensive experience as a researcher and project manager at the Fraunhofer Institute for Experimental Software Engineering. Her research focuses on concurrency in embedded systems, software engineering, AI integration, and low-power systems. Education: PhD in Computer Science from the University of Kaiserslautern (2020). Prior roles include Project Manager at Fraunhofer IESE and Coordinator of the European Master Program in Software Engineering. Research Interests: Concurrent computing, embedded systems architecture, AI applications in software engineering, and low-power system design. She explores concurrency bugs, synchronization mechanisms, and software architecture evolution in the context of Industry 4.0 and autonomous systems. Professional Activities: Co-Organizer of SAMOS workshops (2018–2021), Reviewer for IEEE/ACM conferences, and contributor to European Strategic Research Agendas for embedded systems. Teaches courses on software architectures for embedded systems and supervises numerous graduate students. Key Contributions: Frameworks like BOSMI for multithreaded software testing, FERA for concurrency bug detection, and research on AI adoption in traditional embedded systems. Active in HiPEAC conferences and industry partnerships.
Prof. Rocco OLIVETO is a Full Professor at the University of Molise, affiliated with the School of Biosciences and Territory. His research spans software engineering, artificial intelligence, cybersecurity, and healthcare technology. He focuses on empirical studies of developer practices, AI-driven code analysis, vulnerability detection in smart contracts, and human-centric computing. His work also addresses challenges in game development, mobile app optimization, and wearable health monitoring systems. Notable research areas include code readability assessment, machine learning applications in healthcare diagnostics, and the effectiveness of AI tools like GitHub Copilot. He has contributed to projects like QualAI (continuous quality improvement for AI systems) and 2Vita-B (cognitive and physical rehabilitation systems). His empirical studies often bridge academic research with real-world developer workflows, emphasizing practical applicability. Prof. Oliveto's recent work explores topics such as automated gameplay analysis for game debugging, detection of engagement issues in video games, and robust methods for identifying security vulnerabilities. He has also investigated Dockerfile quality, developer frustration metrics, and the ethical implications of AI in administrative document simplification.
Tero Päivärinta is a Professor at the University of Oulu, Faculty of Information Technology and Electrical Engineering. His work focuses on software engineering, digital ecosystems, and cybersecurity. He specializes in empirical studies of software systems, digital twins, and autonomous driving technologies. His research explores hybrid intelligence systems, data-centric decision-making, and governance of collective ambidexterity in digital initiatives. Education: PhD holder with extensive experience in academic and industry collaborations. Key research domains include cyber-physical systems, DevSecOps automation, and IT governance in public sectors. He co-leads projects such as the NUVE Lab’s vehicle testing frameworks and contributes to initiatives like the Software-Defined Vehicle project. Research highlights include advancing knowledge graphs for manufacturing, cybersecurity compliance in DevOps pipelines, and evaluating data-driven decisions. His articles emphasize interoperability challenges, adaptive systems design, and sustainable digital transformation in public utilities. Professional contributions include organizing the TKTP Annual Symposium and co-editing volumes celebrating academic peers like Markku Oivo. His work bridges theoretical software engineering with practical applications in mobility, governance, and industrial systems.
Aravind Machiry is an Assistant Professor at Purdue University's Electrical and Computer Engineering Department and a founding member of the Purdue Systems and Software Security (PurS3) Lab . His research focuses on system security, particularly vulnerability detection, prevention, and secure system development using static/dynamic program analysis, fuzzing, type systems, and machine learning. Designing practical solutions for software and embedded system security Recipient of NSF CAREER and Amazon Research awards Active participant in SPLASH 2025 as OOPSLA Review Committee member His recent work includes automated vulnerability detection in embedded software, spatial memory safety enhancements, and security analysis of GitHub workflows. He has received recognition for his research through multiple distinguished paper awards and industry funding. Selected scientific awards include NSF CAREER Award (2024) Amazon Research Award (2022) Test of Time Award at FSE 2023 for DynoDroid Distinguished Paper Award at OOPSLA 2022 for 3c Qualcomm Innovation Fellowship (2025) His research team has developed frameworks like ARGUS for taint analysis of CI/CD workflows and FuzzUEr for UEFI interface fuzzing, discovering hundreds of critical vulnerabilities in open-source projects and thousands of command injection flaws in GitHub repositories.
Marina Milovanović is a Professor at the University of Singidunum, Faculty of Informatics and Computing, Department of Mathematics. She holds dual doctoral degrees from the Faculty of Science, University of Kragujevac (Department of Mathematics, 2014) and Faculty of Entrepreneurial Business, Union University (2008), along with Master's and Bachelor's degrees from the Faculty of Mathematics, University of Belgrade (2000-2005 and 1995-2000 respectively). Faculty of Science, University of Kragujevac, Department of Mathematics (PhD, 2014) Faculty of Entrepreneurial Business, Union University (PhD, 2008) Faculty of Mathematics, University of Belgrade (Master's, 2000-2005) Faculty of Mathematics, University of Belgrade (Bachelor's, 1995-2000) Svetozar Marković High School, science and mathematics major (1991-1995) Professor Milovanović specializes in Mathematics Education and Educational Technology, with particular expertise in interactive multimedia applications for teaching mathematics. Her research consistently bridges theoretical mathematics with practical educational technology solutions, evolving from traditional multimedia approaches to incorporating cutting-edge AI and machine learning techniques. She has authored multiple books including 'Interactive multimedia in mathematics teaching' (2015) and collections of solved mathematics problems for entrance exams. Her recent publication record through 2025 demonstrates active engagement in interdisciplinary research, particularly at the intersection of educational technology, artificial intelligence, and practical applications in fields ranging from software engineering to medical diagnostics. Her work shows a clear trajectory from foundational educational technology research toward more sophisticated AI-enhanced learning systems. Professor Milovanović has made significant contributions to semantic web applications in education, particularly through Moodle LMS enhancements, and has explored SCADA applications in industrial contexts. Her collaborative research spans multiple countries and institutions, reflecting an international scholarly network. She has extensive experience developing computer tools for engineering education and has published on diverse topics including petroleum industry processes, environmental management, and financial mathematics. Her work demonstrates consistent application of computational approaches to solve domain-specific problems across multiple disciplines.
Alastair F. Donaldson is a Professor and Director of Research in the Department of Computing at Imperial College London, where he leads the FastPL research group. His academic career spans over a decade at Imperial, progressing from Lecturer (2011-2014) to Senior Lecturer (2014-2017), Reader (2017-2020), and Professor (2020-present). He has also held significant industry positions, including Founder and Director of GraphicsFuzz Ltd. (acquired by Google in 2018), Senior Software Engineer at Google (2018-2021), and Visiting Researcher at both Google and Microsoft Research Redmond. Donaldson earned his PhD from the University of Glasgow under Alice Miller, following a BSc (hons, First Class) in Computing Science and Mathematics. His postdoctoral work included an EPSRC Postdoctoral Research Fellowship at the University of Oxford and a Research Fellowship at Wolfson College Oxford. His research focuses on formal analysis, software testing and programming languages techniques for improving software reliability, with special emphasis on high-performance systems. Donaldson's work bridges theoretical foundations with practical applications, particularly in compiler testing, GPU programming verification, and metamorphic testing. His research has significantly influenced both academia and industry, as evidenced by the acquisition of his startup GraphicsFuzz by Google. Analysis of his recent publications reveals a strong focus on fuzz testing techniques applied across diverse domains including compilers, GPUs, cryptographic protocols, and large language models. His work consistently combines formal methods with practical testing approaches, addressing challenges in compiler correctness, memory models, and API verification across multiple platforms. 2017 BCS Roger Needham Award EPSRC Early Career Fellowship Best Paper Award, EuroSys 2024 Best Paper Award, MET 2021 Best Paper Award, IWOCL 2019 Best Paper Award, IISWC 2019 Best Paper Award, ICST 2016 ACM SIGSOFT Distinguished Paper Award, ISSTA 2023 ACM SIGSOFT Distinguished Paper Award, FSE 2017 ACM SIGPLAN Most Influential OOPSLA Paper Award, 2022 (for GPUVerify) As Director of Research in the Department of Computing, Donaldson oversees research strategy and development. His FastPL research group investigates novel techniques for programming, testing and reasoning about high performance systems. He has served on numerous program committees and held leadership roles including PLDI Steering Committee Chair (2022-2025) and PACM-PL Advisory Board member. His industry engagement includes testifying as an Expert Witness in the IBM UK Ltd v LzLabs GmbH & Ors case. The FastPL research group, which Donaldson leads, focuses on formal analysis, software testing and programming languages. The group has made significant contributions to compiler testing, GPU verification, and metamorphic testing techniques, with practical impact demonstrated by the acquisition of GraphicsFuzz. Current research directions include fuzzing for zero-knowledge proof circuits, randomized testing of decompilers, and systematic testing of large language models for code generation.
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.
Margaret-Anne Storey is a Professor of Computer Science at the University of Victoria and holds the Canada Research Chair Tier I in Human and Social Aspects of Software Engineering. She is affiliated with the Faculty of Engineering and Computer Science and leads the Computer Human Interaction and Software Engineering Lab. Her research focuses on software engineering, human-computer interaction, information visualization, and collaborative work practices. Storey earned her PhD from Simon Fraser University (SFU). Her work bridges socio-technical systems, developer experience (DevEx), and the ethical integration of AI in software engineering. She has pioneered studies on remote work productivity during the pandemic, developer satisfaction, and the human-centered design of tools. Key research interests include understanding developer productivity through frameworks like SPACE (2021), analyzing code review strategies, and exploring the impact of generative AI on software engineering research. Her work often employs mixed-methods approaches and emphasizes empirical validation. Storey has been recognized with the Canada Research Chair Tier I (2020–present). Her contributions span keynote addresses at major conferences (e.g., ICSE), framework development (e.g., DASP for security practices), and interdisciplinary collaborations with organizations like Microsoft. Her research also addresses societal challenges, such as drug-checking technology and participatory culture in education. She advocates for human-centric AI in software engineering and critical questioning of AI’s societal impacts.
Dr. Rafid Al-Khannak is an Associate Professor in Computing at Buckinghamshire New University. He holds a PhD in Engineering and IT from the University of Bolton, completed in collaboration with Siemens AG. His research focuses on engineering and IT operational development, particularly in cloud computing, distributed systems, cybersecurity, and infrastructure automation. Al-Khannak maintains industry collaborations with Amazon and Siemens on cloud implementation and security projects. Key research areas include: Secure cloud migration frameworks using AWS hybrid models Infrastructure automation through CI/CD pipelines Penetration testing methodologies for cloud applications AI-enhanced education system transformation Healthcare application development for specialized needs
Rei Sanchez-Arias is a Teaching Professor and Director of the Master of Applied Data Science (MADS) program at UNC Chapel Hill's School of Data Science and Society. His expertise includes data mining, machine learning algorithm development, and data science pedagogy. He previously held positions at Florida Polytechnic University and St. Thomas University. Research interests span educational tools, health informatics, and optimization methods. Recent work involves AI for endoscopic surgery evaluation, meta-analysis of MLOps tools, and curriculum design for data science programs. Awards include the Excellence in Teaching Award from Florida Polytechnic. Student mentorship focuses on data wrangling and analytics projects.