About
Paul Temple is an active researcher at the Faculty of Computer Science, University of Namur, specializing in machine learning applications for software systems. His work bridges artificial intelligence, deep learning optimization, and configurable software engineering.
Research focuses on energy-aware neural architecture search, variability-intensive systems, and constraint-integrated machine learning. Key contributions include developing genetic algorithms for balancing AI performance/consumption (SmartTune project) and RNN-based log analysis for software variants (VaryMinions). Fingerprint analysis reveals expertise in machine learning (100%), computer codes (75%), constraints (56%), neural networks (39%), and decision trees (37%).
Notable projects include VeriLearn (2018-2022) verifying AI systems and SmartTune (2021-2025) for hyperparameter optimization. Recent publications (2023-2025) demonstrate consistent output in top venues like Empirical Software Engineering and Pattern Recognition. His h-index of 165 indicates significant scholarly impact.
Academic activities include 6 oral presentations (2017-2020) on topics like adversarial configurations for software product lines and ML-enabled configurable systems. Supervised Work (2) suggests mentorship of junior researchers.
