Mr Lucas Brunel | Applied Mathematics | Best Paper Award
PhD Student, ONERA, France
Lucas Brunel is a dedicated PhD student at ONERA, Université Paris-Saclay, and CNRS LIMOS, where he focuses on advancing multi-fidelity surrogate models and uncertainty quantification for aerospace applications. With a strong background in mechanical and systems engineering, Lucas collaborates with leading researchers to push the boundaries of computational mechanics and aerospace design optimization. His work is published in prestigious journals and conferences, emphasizing his expertise in surrogate modeling and active learning.
PROFILE
STRENGTHS FOR THE AWARD
- Innovative Research Contributions: Lucas Brunel’s work on multi-fidelity surrogate models and uncertainty quantification is at the forefront of applied mathematics and aerospace design optimization. His research addresses complex challenges in computational mechanics, showcasing originality and practical relevance.
- Published Works: His publication in the prestigious journal Computer Methods in Applied Mechanics and Engineering and presentations at international conferences like ECCOMAS highlight his ability to produce high-impact research.
- Collaborative Excellence: Working with renowned institutions such as CNRS LIMOS, ONERA, and ETH Zürich, Lucas demonstrates interdisciplinary collaboration and a strong network in the scientific community.
- Practical Applications: The focus on aerospace vehicle design makes his research highly applicable and impactful in both academia and industry.
AREAS FOR IMPROVEMENTS
- Broader Application Scope: Expanding his research to other industries beyond aerospace could further enhance the versatility and applicability of his work.
- Increased Visibility: Engaging in outreach activities like workshops, webinars, or community-driven platforms could amplify his visibility in the scientific community.
- Impact Metrics: Continuing to build a higher citation count and co-authoring papers with industry professionals could solidify his standing as a leading researcher.
EDUCATION
- PhD in Applied Mathematics (2022 — Ongoing): ONERA, Université Paris-Saclay & CNRS LIMOS (EMSE, UCA), France.
- Thesis: Multi-fidelity based mesh uncertainty propagation applied to aerospace vehicle design.
- Supervisors: Rodolphe Le Riche, Bruno Sudret, Mathieu Balesdent, Loïc Brevault.
- Diplôme d’Ingénieur in Mechanical Engineering (2017 — 2022): Université de Technologie de Compiègne, France.
- Master of Science in Systems Engineering (2021 — 2022): Université de Technologie de Compiègne, France.
EXPERIENCE
- PhD Researcher (2022 — Ongoing): Conducting innovative research on multi-fidelity surrogate modeling and uncertainty quantification for aerospace design at ONERA and CNRS LIMOS.
- Engineering Projects (2017 — 2022): Worked on mechanical and systems engineering projects during undergraduate and graduate studies, emphasizing computational simulations and design optimizations.
- Collaborative Research: Engaged with top institutions like ETH Zürich for advancing methodologies in applied mechanics.
AWARDS AND HONORS
- Recipient of the Best Poster Award at the 9th European Congress on Computational Methods in Applied Sciences and Engineering (2024).
- Recognized for contributions to the Computer Methods in Applied Mechanics and Engineering Journal.
- Recipient of a PhD Fellowship for interdisciplinary research in aerospace systems design.
RESEARCH FOCUS
Lucas Brunel specializes in multi-fidelity surrogate modeling, uncertainty quantification, and active learning techniques. His primary aim is to optimize computational methods for aerospace vehicle design. His research integrates functional output simulators, mesh uncertainty propagation, and high-dimensional data modeling to improve predictive accuracy and efficiency in engineering applications.
PUBLICATION TOP NOTES
- A Survey on Multi-Fidelity Surrogates for Simulators with Functional Outputs: Unified Framework and Benchmark 📖
- Uncertainty Quantification Oriented Active Learning for Surrogates of Simulators with Functional Outputs 📊
- A Review of Multi-Fidelity Surrogate Models for High Dimensional Field Outputs 📜
CONCLUSION
Lucas Brunel is a strong contender for the Best Researcher Award due to his innovative and impactful contributions to surrogate modeling and uncertainty quantification. His academic rigor, collaborative efforts, and practical focus on aerospace design optimization establish him as an emerging leader in his field. While broadening the application scope and increasing his visibility could further strengthen his case, his current achievements make him a deserving candidate for this recognition.