My CV
Publications
Talks
Teaching
Numerics
Main page

Contact

Email : croyer2(at)wisc.edu
Clément Royer
Wisconsin Institute for Discovery
330 N Orchard St
Madison, WI 53715
USA

Clément W. Royer

La version française de cette page se trouve ici.


Welcome to my web page. Here you can learn a little about me and my research interests. You can also have a look at my publications, my teaching activities, the codes that I have written and the talks that I have given.
Enjoy your visit !

Latest news

The paper A decoupled first/second-order steps technique for nonconvex nonlinear unconstrained optimization with improved complexity bounds, co-authored with Serge Gratton and Luís Nunes Vicente, has been accepted for publication in Mathematical Programming!
See here for the online version or follow this link for a freely available report. You can also download and try out the associated code: it handles both derivative-based and derivative-free problems.

Short bio

  • I am a postdoctoral research associate within the Wisconsin Institute for Discovery, in Madison, Wisconsin (USA). I am fortunate to be supervised by Stephen J. Wright.

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

  • From 2013 to 2016, I was a teaching assistant (moniteur, in charge of lab and tutorial sessions) at the French Engineering School ENSEEIHT.

  • I obtained my Engineer degree (equivalent to Master's Degree) in Computer Science and Applied Mathematics, as well as my Master in Computer Science from Toulouse INP (National Polytechnic Institute).

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


    Research interests

    My research essentially revolves around the field of numerical optimization and its applications, particularly in complex systems and data science.
    My current work aims at developing efficient nonconvex optimization algorithms, with a focus on incorporating randomness (typically within linear algebra techniques), and establishing complexity guarantees for those frameworks.
    Following the lines of my Ph.D., I also maintain a high interest in derivative-free optimization and its applications to solving simulation-based problems.


    This page was designed by Clothilde Royer, many thanks to her.
    Materials on this page are available under Creative Commons CC BY-NC 4.0 license.