Paolo Arcaini

Paolo Arcaini is a Project Associate Professor at the National Institute of Informatics in Japan, where he has been employed since April 2019. Previously, he served as a Project Assistant Professor at the same institution from March 2018 to March 2019. Prior to that, he was an Assistant Professor at the Department of Distributed and Dependable Systems of Charles University from March 2015 to February 2018. His academic journey includes postdoctoral fellowships at the University of Bergamo and CNR-IDPA, followed by completing his PhD in Computer Science at the University of Milan.

• PhD in Computer Science at the University of Milan (January 2010 - December 2012)
• Postdoctoral fellow at University of Bergamo (October 2013 - February 2015)
• Postdoctoral fellow at CNR-IDPA (January 2013 - September 2013)

Professor Arcaini's research focuses on the intersection of quantum computing and software engineering, particularly in quantum software testing and verification. He has pioneered approaches to applying search-based techniques to quantum software development, including mutation testing and error mitigation for quantum programs. His work also extends to autonomous systems testing, where he develops methods for scenario generation, safety assessment, and falsification of autonomous driving systems. His research in formal methods for cyber-physical systems combines signal temporal logic with search-based techniques to verify complex system behaviors. A significant portion of his work addresses the challenges of testing AI-enabled systems, particularly deep neural networks in safety-critical contexts.

Analysis of Professor Arcaini's recent publications reveals a strong trend toward quantum software engineering, with numerous papers on testing methodologies for quantum programs, error mitigation techniques, and quantum-inspired optimization for software testing. His work demonstrates a consistent focus on applying search-based techniques to challenging domains, with increasing attention to safety-critical applications of AI and quantum computing. The interdisciplinary nature of his research connects formal methods, machine learning, and software engineering to address verification challenges in emerging technologies.

• Best paper award on testing AI system at IEEE International Conference on Artificial Intelligence Testing (AITest 2020)
• Distinguished paper award at Symposium on Search-Based Software Engineering (SSBSE 2021)
• Best paper award at Symposium on Search-Based Software Engineering (SSBSE 2020)

Professor Arcaini is highly active in the software engineering research community, serving on program committees for numerous top conferences including ASE, ICSE, ISSTA, and ESEC/FSE. His work on quantum software engineering has positioned him as a leader in this emerging field, with multiple tool demonstrations and journal-first papers that bridge theoretical advances with practical applications. His research on autonomous systems testing has resulted in several tools for scenario generation and safety assessment that are being adopted by the automotive industry. While specific grant information isn't detailed in the provided materials, his extensive publication record across multiple high-impact venues suggests substantial research funding support.

Professor Arcaini leads the MMM research group (as indicated by his personal website at http://group-mmm.org/~arcaini/), which focuses on model-based methods for software engineering. His team appears to specialize in applying formal methods and search-based techniques to emerging domains like quantum computing and autonomous systems. The group maintains active collaborations with researchers worldwide, as evidenced by the international co-authorship of his publications across European and Asian institutions.