Andrea Stocco

Andrea Stocco is an Assistant Professor at the Technical University of Munich (TUM) within the Chair of Software Engineering for Data-Intensive Applications and the School of Computation, Information and Technology, while also serving as Head of the Automated Software Testing Field of Competence at fortiss GmbH in Munich. His research bridges software engineering and deep learning, focusing on enhancing the robustness, reliability, and dependability of data-intensive systems, particularly in autonomous driving and web applications.

• Key research areas: Testing AI-based systems, autonomous driving validation, computer vision for software engineering, web test automation, and reliability of DL systems
• Notable awards: IEEE Computer Society TCSE Distinguished Paper Award (2025), ACM SIGSOFT Distinguished Artifact Award (2020), Best Presentation Award at NEXTA 2021
• Leadership roles: Program Chair for ASE 2024 (Research Track), ICSE 2024 (Demonstration Track), and SCAM 2024 (Research Track)
• Editorial involvement: Empirical Software Engineering journal (2025), Journal of Software: Evolution and Process (2024), ACM TOSEM Replicated Computational Results Distinguished Reviewers Board

His work explores techniques like anomaly detection, uncertainty quantification, and attention maps to improve safety-critical systems' testing. Recent publications examine digital twins for autonomous driving, generative AI in test input generation, and the reality gap between virtual and physical testing environments. Andrea actively contributes to conference program committees in software engineering and testing, including ASE, ICSE, FSE, and ICST.