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clement.royer@lamsade.dauphine.fr
Clément Royer
Université Paris Dauphine-PSL
Place du Maréchal de Lattre de Tassigny
75016 Paris
FRANCE
I am also on Google Scholar and Github.

Clément W. Royer

Associate professor, Université Paris Dauphine-PSL


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Latest news

  • Research visit (2025/07) I visited Warren Hare at the University of British Columbia (Okanagan Campus) in Kelowna, BC, Canada. I gave a talk in the COCANA seminar series during my stay, the slides can be found here. Thanks to Warren for being such a great host!

  • Conference (2025/07) I attended the eighth International Conference on Continuous Optimization, held at the University of Southern California on July 21-24. I presented in the derivative-free optimization cluster, and co-chaired two sessions with Florentin Goyens on nonconvex optimization (with ties to semidefinite programs) and manifold optimization (from a geometric perspective). Thanks to the organizers and to all those I had the opportunity to discuss with!

  • Conference (2025/06) I was invited to the first Portuguese-American Optimization Workshop (PAOW), held in Horta (Portugal). Following this workshop, I also attended the 2025 edition of Modeling and Optimization: Theory and Applications (MOPTA), organized in Ponta Delgada (Portugal). Thanks a lot to the organizers for putting together this double event!

  • Accepted paper (2025/06) The paper Direct-search methods in the year 2025: Theoretical guarantees and algorithmic paradigms, co-authored with Kwassi Joseph Dzahini, Francesco Rinaldi and Damiano Zeffiro, has appeared online in EURO Journal on Computational Optimization.

  • New preprint (2025/06) A line search framework with restarting for noisy optimization problems, co-authored with Albert S. Berahas and Michael J. O'Neill.
    Using a restart condition, we equip popular frameworks like nonlinear conjugate gradient and L-BFGS quasi-Newton with complexity guarantees, even in a noisy setting!

  • Accepted paper (2025/05) The paper A characterization of positive spanning sets with ties to strongly connected digraphs, co-authored with Denis Cornaz and Sébastien Kerleau, has appeared in Discrete Applied Mathematics.

  • New preprint (2025/04) Direct-search methods for decentralized blackbox optimization, co-authored with El Houcine Bergou, Youssef Diouane and Vyacheslav Kungurstev. We adapt derivative-free algorithms to the decentralized setting. This is not trivial from a theoretical viewpoint but the resulting methods perform well in practice!

  • Conference/School (2025/02) I was an invited speaker at the Mathematics, Artificial Intelligence and Applications conference held in Sousse (Tunisia). This event is jointly held with the CIMPA school Control, Optimization, and Model Reduction in Machine Learning in Hammamet (Tunisia). I was one of the lecturers in that school, and the materials for my course on optimization for machine learning can be found on Github or here.

  • Award (2025/02) As in 2022, I am a recipient of a Meritorious Service Award from the journal Mathematical Programming acknowledging exceptional contributions as a reviewer during the year 2024.

  • Lectures (2025/02) I am giving a series of lectures on complexity in continuous optimization for Dauphine's PhD program in Computer Science. Slides and notes can be found here.

  • New preprint (2024/11) A characterization of positive spanning sets with ties to strongly connected digraphs, with Denis Cornaz and Sébastien Kerleau.
    Check it out for an unexpected link between positive spanning sets and strongly edge-connected digraphs!

  • Accepted paper (2024/10) The paper Complexity analysis of regularization methods for implicitly constrained least squares, co-authored with Akwum Onwunta, has appeared in Journal of Scientific Computing.

  • Teaching (2024/09) The Fall semester has started! I will be teaching several courses around linear algebra and applications to data science (bachelor level) and optimization for machine learning (master level). Details can be found here.

    Research interests

    My research essentially revolves around the field of numerical optimization and its applications, particularly in complex systems and data science. In addition to optimization, my work relies heavily on linear algebra techniques and randomized methods.
    Lately I have been interested in analyzing certain classes of nonconvex optimization problems and developing efficient algorithms with complexity guarantees for solving those problems. I am also highly interested in derivative-free optimization and its applications to solving simulation-based problems.

    Short bio

  • September 1st, 2019: Joined Université Paris Dauphine-PSL and LAMSADE as a maître de conférences (equivalent to associate professor, with tenure granted on September 1st, 2020).

  • November 2016-August 2019: Postdoctoral research associate within the Wisconsin Institute for Discovery, in Madison, Wisconsin (USA). I was fortunate to work in the group of Stephen J. Wright.

  • November 4, 2016: PhD in applied mathematics from the university of Toulouse, delivered by the Université Toulouse III Paul Sabatier. Prepared at the Institut de Recherche en Informatique de Toulouse, under the joint supervision of Serge Gratton and Luís Nunes Vicente.

  • For more information, you can have a look at my vitae in a short or extended format.

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