Mathieu ACHER

Mathieu ACHER is a Researcher active in software engineering, specializing in configuration sampling, software variability, and machine learning applications. His work spans empirical studies on configurable systems and adversarial learning techniques, particularly in web development and 3D printing domains.

• Key Research Areas: Configuration knowledge modeling, variability management, and constraint-based systems.
• Recent Projects: Investigated adversarial configurations for quality assurance (2019), applied machine learning to 3D printing defect prediction (2019).

Research Trends: Focuses on optimizing configuration testing via sampling strategies, integrating adversarial learning for robust software product lines, and cross-domain applications in 3D printing.

Activities: Co-organized the MaLTeSQuE@ESEC/SIGSOFT FSE 2019 and Machine Learning and Software Engineering in Symbiosis workshops (2018-2019).