After dual PhDs from Ecole Polytechnique and Stanford University in optimisation and finance, followed by a postdoc at U.C. Berkeley, Alexandre d'Aspremont joined the faculty at Princeton University as an assistant then associate professor with joint appointments at the ORFE department and the Bendheim Center for Finance. He returned to Europe in 2011 thanks to a grant from the European Research Council and is now directeur de recherche at CNRS, and professor at Ecole Normale Supérieure in Paris. He received the SIAM Optimization prize for 2004-2007, a NSF CAREER award, and an ERC starting grant. In 2016, he co-founded Kayrros, an earth observation startup. His research focuses on convex optimization and applications to machine learning, statistics, climate and finance.

After finishing her undergraduate math studies in Argentina, Claudia moved to Paris where she obtained her PhD and habilitation degrees. Personal reasons caused Claudia to reverse direction over the Atlantic Ocean; she now lives in Rio de Janeiro.

Claudia has participated in industrial collaborations since the time of her PhD studies. Her first experience in this area, with Electricité de France, was so beneficial that it greatly influenced her career: Claudia’s theoretical research has been continuously enriched with insight provided by real life problems. 

She is an applied mathematician specialized in optimization, both its theory and its numerical aspects. Her research interests lie primarily in the area of nonsmooth optimization, stochastic programming, and variational analysis, with an emphasis on applications in the energy sector.

Kim-Chuan Toh is the Leo Tan Professor in the Department of Mathematics at the National University of Singapore.

He works extensively on convex programming, particularly large-scale matrix optimization problems such as semidefinite programming,

and optimization problems arising from machine learning and statistics.

Currently he serves as a co-Editor for Mathematical Programming, an Area Editor for Mathematical Programming Computation,

an Associate Editor for SIAM J. on Optimization, Operations Research, and ACM Transactions on Mathematical Software.

He received the INFORMS Optimization Society Farkas Prize in 2017 and the triennial Mathematical Optimization Society Beale-Orchard Hays Prize in 2018.

He is a Fellow of SIAM.

Stephen J. Wright holds the George B. Dantzig Professorship, the Sheldon Lubar Chair, the Amar and Balinder Sohi Professorship of Computer Sciences, and is a Discovery Fellow at the University of Wisconsin-Madison. In February 2024, he was elected into the National Academy of Engineering in recognition of his achievements in the design and theory of optimization algorithms and the application of optimization to such areas as machine learning and signal processing.  In 2020 he won the Khachiyan Prize from INFORMS Optimization society. Prior to joining UW-Madison in 2001, Wright held positions at North Carolina State University (1986-90), Argonne National Laboratory (1990-2001), and the University of Chicago (2000-01). He has served as Chair of the Mathematical Optimization Society, and Trustee of SIAM. He is also a Fellow of SIAM. In 2014, he won the W.R.G. Baker award from IEEE. He has also been the Site Director of the Institute for Foundations of Data Science. Wright is the author and coauthor of widely used text/reference books in optimization, including Primal Dual Interior-Point Methods, and Numerical Optimization. He has published widely on optimization theory, algorithms, software, and applications. Wright is current editor-in-chief of the SIAM Journal on Optimization, and previously served variously as editor-in-chief or associate editor of Mathematical Programming (Series A), Mathematical Programming (Series B), SIAM Review, SIAM Journal on Scientific Computing, and several other journals and book series.