DevOps Automation Professors and Supervisors | ApplySharif

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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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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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Mohammad HamdaqaView profile

Associate Professor

Max Planck Institute for Security and PrivacyGermany

Mohammad Hamdaqa is an Associate Professor at the Department of Computer Engineering and Software Engineering at Polytechnique Montréal (Canada), where he leads the Software and Emerging Technologies Lab. He received his PhD in Software Engineering from the University of Waterloo in Canada in 2016 and holds multiple advanced degrees including a Master of Applied Science in Software Engineering and an MBA with a minor in Management Information Systems. His educational background includes: Ph.D. in Electrical and Computer Engineering, University of Waterloo, Canada Master in Electrical and Computer Engineering, Concordia University, Canada Master in Business Administration, New York Institute of Technology, USA Bachelor in Computer Engineering, Jordan University of Science and Technology, Jordan Dr. Hamdaqa's research focuses on the intersection of software engineering and emerging technologies. His work explores how software engineering approaches can be tailored to address the complexities of architecting, building, and deploying applications for new platforms like Cloud Computing and Blockchain. He is particularly interested in how emerging technologies can advance software creation, evolution, and management practices. His research spans model-driven software engineering, cloud computing, blockchain, and the application of AI in software development processes. His recent publications demonstrate a strong focus on smart contract security, infrastructure as code, model-driven engineering, and the application of large language models in software engineering tasks. His work bridges theoretical software engineering concepts with practical applications in cutting-edge technology domains, with particular emphasis on addressing security, sustainability, and maintainability challenges in next-generation software systems. Dr. Hamdaqa has received recognition through service on program committees for major software engineering conferences including ASE, ICSE, MODELS, and SANER. He serves on the editorial board of Service Transactions on Internet of Things and is a Member of the IEEE Computer Society and the Association for Computing Machinery. He has supervised multiple Master's students to completion, with recent theses focusing on OCL generation, smart contract auditing, epidemiological modeling, and infrastructure as code security. His current research group continues to explore innovative approaches at the intersection of software engineering and emerging technologies. Dr. Hamdaqa leads the Software and Emerging Technologies Lab at Polytechnique Montréal, which brings together researchers and students to investigate cutting-edge challenges in software engineering for new technology platforms. The lab focuses on practical solutions that balance theoretical rigor with real-world applicability.

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Jingyue LiView profile

Professor

Max Planck Institute for Security and PrivacyGermany

Jingyue Li is a Professor in the Department of Computer Science at the Norwegian University of Science and Technology (NTNU), within the Faculty of Information Technology and Electrical Engineering. She earned her Ph.D. in Software Engineering from NTNU in 2006 and has extensive industrial experience including positions at IBM and DNV Research and Innovation. Her educational background includes: Ph.D. in Software Engineering from NTNU (2006) Professor Li's research spans several key areas in software engineering with a focus on both theoretical and practical applications. Her work bridges traditional software engineering practices with emerging technologies, particularly in the domain of security and blockchain systems. She has conducted extensive empirical research and applied design science methodologies to develop innovative tools and approaches. Her recent publications demonstrate a strong trend toward blockchain technologies, software security, and the intersection of AI with software engineering. The research shows increasing focus on practical applications of blockchain in decentralized autonomous organizations, consensus protocols, and security vulnerabilities in smart contracts. There's also significant work on integrating security practices into DevOps (DevSecOps) and applying machine learning techniques to software engineering problems. Professor Li has received recognition through her leadership roles in major conferences: General Chair for FSE 2025 (The ACM International Conference on Foundations of Software Engineering) Member of the EASE (International Conference on Evaluation and Assessment in Software Engineering) steering committee In terms of research leadership, Professor Li has served as Principal Investigator (PI) or Key Scientist on numerous research projects including TRACE4EU (2023-2025), PaaSforChain (2020-2023), CyberSmart (2017-2020), and several others focused on blockchain, security, and software engineering. She has also conducted research visits to institutions including University College London, University of Washington, Hiroshima University, and Peking University. Her research group appears to be actively engaged in both theoretical and applied research, with strong industry connections through projects like CyberSmart and SecureCyber that address real-world challenges in cybersecurity and smart city infrastructure.

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Janaka SenanayakeView profile

Lecturer

Robert Gordon UniversityUnited Kingdom

Dr. Janaka Senanayake is a Lecturer in Cybersecurity at Robert Gordon University (RGU), attached to the School of Computing, Engineering and Technology. He is affiliated with the Cybersecurity Research Group and contributes to the university's 'Living in a Digital World' research theme. Dr. Senanayake completed his PhD in Cybersecurity at RGU, specializing in software security. He earned a Bachelor of Science (Special) in MIT with First Class Honors from the University of Kelaniya, Sri Lanka in 2017. Prior to joining RGU, he worked as a Software Engineer at DirectFN Pvt. Ltd. and NDB Bank Information Technology and R&D Department for approximately three years, and also served as a lecturer and researcher at several international universities. His research focuses on cybersecurity, software security, mobile computing, artificial intelligence, and software engineering. Dr. Senanayake has published extensively on Android security, AI-powered vulnerability detection, and network security solutions. His recent work demonstrates a strong emphasis on practical security applications using advanced AI techniques while addressing privacy concerns through approaches like federated learning. Dr. Senanayake has produced 23 publications from 2021-2025, with a significant concentration of high-impact work in 2024-2025. His research output shows a clear trajectory toward integrating cutting-edge AI technologies with practical cybersecurity applications, particularly in mobile and network security domains. His notable contributions include: MADONNA: A browser-based malicious domain detection system using optimized neural networks FedREVAN: Real-time detection of vulnerable Android source code through federated neural networks with XAI DroidKey: A framework for API key security in Android applications Research on integrating large language models for automated vulnerability scanning Dr. Senanayake is actively involved in PhD supervision with research topics including Software Security, Cybersecurity, Security and Artificial Intelligence, Mobile Security, and Law and AI. His industry background combined with academic expertise provides a valuable practical perspective to his research and teaching. He maintains active research collaborations, as evidenced by his numerous co-authored publications with researchers from different institutions, particularly focusing on cybersecurity challenges in both Western and Sri Lankan contexts.

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John LindströmView profile

Professor

Luleå University of TechnologySweden

John Lindström is a Professor at Luleå University of Technology's Department of Computer Science, Electrical and Space Engineering. His research centers on cyber security with specialized focus areas in IT/OT security management, IoT lifecycle solutions, and Zero Defect Manufacturing frameworks. He currently contributes to projects including Cybersäkerhetsnod Norr and industrial manufacturing optimization initiatives. Dr. Lindström's research bridges industrial engineering and cybersecurity, addressing critical challenges in operational technology security and sustainable manufacturing. His work emphasizes practical frameworks for Zero Defect Manufacturing maturity, OT security standardization, and IoT system lifecycle management, with applications in Industry 4.0 environments. Publication analysis reveals consistent focus on industrial cybersecurity and manufacturing optimization from 2019-2025. Recent works demonstrate strong emphasis on capability maturity models for quality management, OT security standardization, and interoperability requirements for smart manufacturing systems, frequently employing case study methodologies.

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Jay DeslauriersView profile

Research Fellow

University of WestminsterUnited Kingdom

Jay Deslauriers serves as a Research Fellow at the University of Westminster's Centre for Parallel Computing and holds a Teaching Fellow position at Imperial College London spanning both the Graduate School and Business School. With five years at Westminster following prior service as a full-time Lecturer in the School of Computer Science & Engineering, his career bridges advanced cloud research and technical education. His research focuses on cloud and container orchestration with emphasis on vendor-agnostic solutions across the cloud-edge continuum. Key projects include leading MiCADO framework development for the EU Horizon 2020 DIGITbrain (Digital Twins in Manufacturing) and ASCLEPIOS (secure healthcare cloud platform) initiatives. His technical expertise spans Kubernetes, Docker, TOSCA standards, and infrastructure-as-code implementation. Research outputs show consistent publication trends in Decentralized orchestration frameworks (2023-2025) Digital twin deployment systems (2021-2022) Cloud-agnostic application management (2018-2020) with recent work emphasizing microservices in edge computing environments. His professional engagement includes Society of Research Software Engineering membership (since 2019) AdvanceHE fellowship (since 2020) supporting his dual focus on technical infrastructure and research education. Current supervision interests center on cloud/container orchestration, Docker/Kubernetes implementation, and statistical methods for resource optimization. His MiCADO framework remains central to multiple EU-funded projects with ongoing development for cloud-edge continuum applications.

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Björn LundellView profile

Researcher

Louisiana State University of AlexandriaUnited States

Björn Lundell is a Researcher at the School of Informatics, University of Skövde, Sweden. His work centers on Open Source Software (OSS), ICT standards, and digital governance in public sector contexts. He investigates sustainable software practices, interoperability, and policy compliance. Research Interests: Lundell explores: OSS adoption in government and industry Digital preservation (e.g., PDF/A conformance) Software ecosystems and standardization SaaS licensing risks and open alternatives His 158 publications reflect a focus on practical challenges in public IT, including accessibility, procurement, and cross-border data governance. Recent trends show emphasis on IoT standards and reproducible builds. Affiliations: Lundell is exclusively affiliated with the University of Skövde. No lab, awards, or supervised students are mentioned in the source material.

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Yang LiuView profile

Professor

Max Planck Institute for Security and PrivacyGermany

Yang Liu is a Full Professor and University Leadership Forum Chair at the School of Computer Science and Engineering, Nanyang Technological University (NTU) in Singapore. He serves as Programme Director for HP-NTU Digital Manufacturing Corp Lab, Deputy Director of the National Satellite of Excellence of Singapore, and Cluster Director in Cybersecurity at Energy Research Institute @NTU. His research spans Cybersecurity , Software Engineering , and Artificial Intelligence . He leads research in malware modeling and detection, vulnerability analysis using machine learning and program analysis, formal verification of security systems, program specification learning, performance analysis, Android system security, and AI security, robustness, fairness, and explainability. His notable work includes the Process Analysis Toolkit (PAT) for model checking and the Deep-Series tools for deep learning testing. Professor Liu has published extensively in top-tier conferences including ASE, ICSE, FSE, ISSTA, and S&P. His research demonstrates strong trends toward integrating AI/ML techniques with traditional software engineering and security approaches, particularly focusing on large language models for code analysis, vulnerability detection, and program repair. Recent publications show a growing emphasis on blockchain security, smart contract analysis, and addressing security challenges in AI systems. NRF Investigatorship (Class 2020) ACM's Distinguished Speaker Nanyang Research Award (Young Investigator) Microsoft Asia Research Fellowship 20 Year ICFEM Most Influential System Award for PAT Multiple ACM SIGSOFT Distinguished Paper Awards Professor Liu actively advises students and has seen notable student achievements, including Singapore Data Science Consortium research award winners and AISG PhD Fellowship recipients. His research is supported by numerous grants including a $900,000 NTU-NAP grant for Formal Verification on Cloud and a $471,000 grant for Vulnerability Detection in Binary Code. He leads the HP-NTU Digital Manufacturing Corp Lab and contributes to RollsRoyce@NTU Corporate Lab research on complex business systems simulation.

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Ali MesbahView profile

Professor

Max Planck Institute for Security and PrivacyGermany

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.

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Yintong HuoView profile

Assistant Professor

Max Planck Institute for Security and PrivacyGermany

Yintong Huo is an Assistant Professor at the School of Computing & Information Systems, Singapore Management University (SMU), where he leads research in intelligent software engineering. He received his PhD from The Chinese University of Hong Kong (CUHK) in 2024 under Prof. Michael R. Lyu and holds a Bachelor's degree from the University of Electronic Science and Technology of China. His research focuses on empowering AI models (particularly LLMs) for software development, testing, and operations, with two flagship projects: LogPAI (open-source AI platform for automated log analysis) and WebPAI (multimodal intelligence for automatic webpage development). His work spans log analysis, code intelligence, UI generation from prototypes, and configuration diagnostics. Huo's publication record shows strong trends in leveraging multimodal LLMs for practical software engineering challenges, with recent work on interactive webpage generation (Interaction2Code), configuration logging (ConfLogger), and log parsing (LILAC). His research bridges theoretical AI advancements with real-world system reliability needs. ICSE Distinguished Reviewer Award (2025) ISSRE Distinguished Reviewer Award (2024) IEEE Open Software Services Award (2022) ACM SIGSOFT CAPS Travel Grants National Scholarship (2019) Huo actively supervises PhD students (including Shi Ying Chang and Dan Huang) and research engineers. His lab has secured funding for multiple projects including WebPAI and LogPAI. He serves on program committees for major conferences (ASE, ICSE, FSE) and reviews for top journals. Current projects include dynamic webpage generation and configuration diagnostics, with ongoing work on small language models for logging systems. Huo leads the LogPAI and WebPAI research groups, developing open-source tools for automated log analysis and multimodal UI code generation. The LogPAI project has garnered over 3,000 GitHub stars and 70,000 downloads. His team collaborates with industry partners on AIOps challenges and is expanding into configuration diagnostics through the ConfLogger project.

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Pinjia HeView profile

Assistant Professor

Max Planck Institute for Security and PrivacyGermany

Pinjia He is an Assistant Professor and Presidential Young Fellow at The Chinese University of Hong Kong, Shenzhen's School of Data Science. He is also recognized as a national-level young talent in China. His academic journey includes a postdoctoral position at ETH Zurich's Department of Computer Science under Prof. Zhendong Su, a Ph.D. in Computer Science and Engineering from The Chinese University of Hong Kong supervised by Prof. Michael R. Lyu, and a B.E. in Computer Science and Technology from South China University of Technology. Ph.D. in Computer Science and Engineering, The Chinese University of Hong Kong Postdoctoral Scholar, ETH Zurich B.E. in Computer Science and Technology, South China University of Technology Dr. He's research spans software engineering, natural language processing, and systems, with particular focus on (1) AI for SE (e.g., LLM for code, AIOps), (2) SE for AI (e.g., LLM safety), and (3) software testing. He is renowned for his work on robust NLP systems and software log analysis. His research has been published at top venues including ICSE, FSE, ASE, ISSTA, ICLR, and OSDI. His publication trends show a consistent focus on log analysis systems, with recent work shifting toward LLM applications in software engineering and safety evaluation of conversational AI systems. His research demonstrates strong industry impact with tools downloaded over 60,000 times by more than 450 organizations. Most Influential Paper Award (ISSRE) IEEE Open Software Services Award Dr. He actively contributes to the academic community as Social Media Co-Chair for FSE 2025, Associate Editor of TOSEM, and serves on program committees for major conferences including FSE 2025, ICSE 2025, ISSTA 2025, and ASE 2024. His GitHub repositories (logparser, loglizer, loghub) have garnered over 5,000 stars and significant industry recognition including from IBM. While specific grant information isn't detailed in the provided text, his extensive publication record and tool development suggest substantial research funding. His work has been cited over 5,000 times according to Google Scholar, and his open-source tools have been widely adopted in both academia and industry. His current research focuses on advancing the intersection of software engineering and artificial intelligence, particularly in leveraging LLMs for software development tasks while ensuring their safety and reliability.

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Maxime LamotheView profile

Assistant Professor

Max Planck Institute for Security and PrivacyGermany

Maxime Lamothe is an assistant professor at Polytechnique Montreal specializing in empirical software engineering and mining software repositories. His research focuses on software APIs, build systems, and the intersection of AI and software engineering. Previously, he was a postdoctoral researcher at the University of Waterloo's Software REBELs Lab under Prof. Shane McIntosh. Dr. Lamothe's educational background includes: Ph.D. in Software Engineering from Concordia University (2020) M.Eng from Concordia University (2017) B.Eng from McGill University (2013) His research interests center around empirical studies of software engineering practices, with particular focus on API design and evolution, software build systems, and performance analysis. Dr. Lamothe investigates how developers interact with APIs, how build systems operate in practice, and how AI techniques can enhance software engineering processes while maintaining human oversight of critical decisions. Dr. Lamothe's publication record shows a consistent focus on empirical approaches to understanding software engineering practices. His work frequently examines API usage patterns, code review processes, and continuous integration systems. A notable trend is his growing interest in applying AI techniques to software engineering challenges while maintaining empirical validation of proposed solutions through rigorous case studies and longitudinal analyses. Dr. Lamothe actively serves the academic community as a reviewer for top journals including Transactions on Software Engineering (TSE), Empirical Software Engineering (EMSE), and Journal of Systems and Software (JSS). He has served on program committees for major conferences including ASE, ICSE, ESEC/FSE, MSR, and SANER across multiple years, with particular involvement in the NIER Track, Research Papers track, and Tool Demonstration tracks. Currently seeking Masters and Ph.D. students, Dr. Lamothe leads research at the intersection of traditional software engineering practices and emerging AI techniques. His work combines rigorous empirical methods with practical applications to solve real challenges in software development, with implications for improving API design, enhancing code review processes, optimizing build systems, and developing trustworthy AI-assisted software engineering tools.

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Mohammad Adnan HamdaqaView profile

Associate Professor

Max Planck Institute for Security and PrivacyGermany

Mohammad Adnan Hamdaqa is an Associate Professor at the Department of Computer Engineering and Software Engineering at Polytechnique Montréal (Canada), where he leads the Software and Emerging Technologies Lab. He holds a Ph.D. in Software Engineering from the University of Waterloo (2016), along with a Master's in Electrical and Computer Engineering from Concordia University, an MBA from New York Institute of Technology, and a Bachelor's in Computer Engineering from Jordan University of Science and Technology. His research focuses on the intersection of emerging technologies and software engineering, particularly how software engineering approaches can be adapted for new platforms like Cloud Computing and Blockchain. His work spans model-driven software engineering, cloud applications, and blockchain technologies. Analysis of his recent publications reveals a strong emphasis on blockchain technology, especially smart contracts and Ethereum, with significant work on security, evolution, and visualization of these systems. His research also demonstrates growing integration of large language models in software engineering tasks, particularly for model specification and code generation. There's also a notable thread of work on sustainability in infrastructure as code and security practices across cloud platforms. Hamdaqa actively contributes to the academic community as a member of IEEE Computer Society and ACM, and has served on program committees for numerous conferences in software engineering and services communities. He has successfully supervised multiple Master's students, with recent theses focusing on smart contract auditing, epidemiological modeling using model-driven approaches, and security practices in infrastructure as code. His lab maintains active research in both theoretical and applied aspects of software engineering for emerging technologies.

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Simone ScalabrinoView profile

Assistant Professor

Max Planck Institute for Security and PrivacyGermany

Simone Scalabrino is an Assistant Professor at the University of Molise, Italy, where he is part of the STAKE lab. He also serves as CSO at Datasound. His academic career includes teaching courses such as Automated Software Delivery and Object-Oriented Programming at the University of Molise. Dr. Scalabrino received his Ph.D. from the University of Molise in 2019 with a thesis entitled "Automatically Assessing and Improving Code Readability and Understandability," supervised by Prof. Rocco Oliveto. He earned his Master's Degree in Computer Science from the University of Salerno in 2015 and his Bachelor's Degree in Computer Science from the University of Molise in 2013. His research interests focus on Software Quality, Software Testing, Software Security, and Empirical Software Engineering . Dr. Scalabrino's work spans multiple areas including code readability assessment, software testing methodologies, Docker container analysis, game quality assessment, and voice user interface testing. His research often combines empirical methods with machine learning techniques to address practical software engineering challenges. Analysis of his recent publications reveals a strong focus on improving software quality through various approaches. His work spans code readability assessment, Docker container analysis, game quality testing, and voice user interface evaluation. There's a clear trend toward applying machine learning techniques to traditional software engineering problems, particularly in the areas of code understanding, defect prediction, and quality assessment. His research often involves large-scale empirical studies with real-world data from open source projects and commercial applications. Scientific Awards Distinguished Reviewer Award @ FSE 2025 Distinguished Reviewer for TSE (2023) Best Reviewer Award for JSS (2022) ACM Distinguished Paper Award @ MSR 2019 ACM Distinguished Paper Award @ ASE 2017 ACM Distinguished Paper Award @ ICPC 2016 Dr. Scalabrino has been actively involved in mentoring students through research projects, though specific student names are not listed in the provided information. He has served on program committees for numerous prestigious conferences including ASE, ICSE, ICPC, and FSE. His service extends to reviewing for top-tier journals such as Transactions on Software Engineering and Empirical Software Engineering. He leads or contributes to several research projects including DevProDev, which focuses on developer-centered recommendation systems, and ATTICUS, a tele-monitoring system for ambient-assisted living. Dr. Scalabrino has also developed multiple research tools such as Code Readability Predictor, TIRESIAS, OCELOT, CLAP, and ACRyL to address various software engineering challenges.

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