Carola Doerr is a CNRS Research Director at Sorbonne University's LIP6 Laboratory, specializing in black-box optimization algorithms. She leads the Operational Research team and serves as Scientific Delegate for Section 2 at CNRS (40% time commitment since September 2023). Her research bridges theoretical foundations and practical applications of optimization heuristics, with significant industrial collaborations including Thales, Honda, and Facebook. Her primary research interests include black-box optimization, algorithm configuration, benchmarking methodologies, and discrepancy theory. Doerr develops mathematical models predicting minimum evaluations required for optimization problems while creating practical tools like IOHprofiler for algorithm analysis. Her work enables dynamic algorithm selection that adapts to different problem instances and optimization phases. Her recent publications reveal strong trends in dynamic algorithm configuration, theory-guided benchmarking, and biomedical applications. She has pioneered approaches combining machine learning with optimization theory to create more efficient techniques for industrial and scientific problems, particularly in sensor configuration and medical prediction. CNRS Bronze Medal 2022 for black-box optimization research ERC Consolidator Grant 2024 for dynaBBO project (€2M) Feodor Lynen Research Fellowship from Alexander von Humboldt Foundation Otto Hahn Medal from Max-Planck-Society Multiple best paper awards at GECCO, FOGA, and CEC conferences Doerr actively supervises numerous PhD students across multiple institutions and leads the Benchmarking Network. Her research group develops open-source tools like IOHprofiler that facilitate empirical comparisons of optimization algorithms. Current projects focus on dynamic algorithm selection for biomedical applications and mechanical design optimization, with strong emphasis on explainability and real-world implementation.
