Tom M. Ragonneau

Ph.D. The Hong Kong Polytechnic University

Actively developing software for derivative-free optimization.

Self introduction

I am a fresh Ph.D. graduate from the Department of Applied Mathematics at The Hong Kong Polytechnic University. I was advised by Dr. Zaikun Zhang and Prof. Xiaojun Chen, and supported by the University Grants Committee (UGC) of Hong Kong, under the Hong Kong Ph.D. Fellowship Scheme (HKPFS, ref. PF18-24698).

Research overview

My research interests include mathematical optimization and its applications, especially methods based on inaccurate information and methods dedicated to derivative-free optimization.

Selected publications

[1] T. M. Ragonneau and Z. Zhang. PDFO: A Cross-Platform Package for Powell’s Derivative-Free Optimization Solver. 2023. arXiv:2302.13246 [math.OC].

[2] T. M. Ragonneau and Z. Zhang. An Optimal Interpolation Set for Model-Based Derivative-Free Optimization Methods. 2023. arXiv:2302.09992 [math.OC].

[3] T. M. Ragonneau. “Model-Based Derivative-Free Optimization Methods and Software.” Ph.D. thesis. Hong Kong: Department of Applied Mathematics, The Hong Kong Polytechnic University, 2022.

[4] R. Benshila, G. Thoumyre, M. Al Najar, G. Abessolo Ondoa, R. Almar, E. Bergsma, G. Hugonnard, L. Labracherie, B. Lavie, T. M. Ragonneau, S. Ehouarn, B. Vieublé, and D. Wilson. “A deep learning approach for estimation of the nearshore bathymetry.” J. Coast. Res. 95.sp1. (2020), pp. 1011–1015.