Michel Baes
Michel Baes
I am an Engineer in Applied Mathematics from UCLouvain, where I also did my PhD under supervision of Pr. Yurii Nesterov, in which I've worked on extensions of his Smoothing Techniques to symmetric cones using the framework of Jordan algebras. After stays at the Electrical Engineering Department of KULeuven, at the Institute for Operations Research at ETH Zurich, and at the Department of Mathematics at the University of Zurich, I was an Oberassistant in the RiskLab at ETH Zurich. And now, I have the good fortune of having joined a team of top-notch experts in Optimization and Data Science at Fortum, working on making energy greener.
Optimization is my primary field of expertise. Among other things, I have worked in the design of efficient algorithms for large-scale Convex Optimization and Mixed-Integer problems. I am using Artificial Intelligence and Optimization methods in a variety of application fields, notably in Data Analysis, in Optimal Control, and Mathematical Finance. The fields that attracts nowadays my deepest enthusiasm is green electricity generation and the market challenges it conveys.
Here is a list of my newest papers and those that have been cited at least 10 times in papers not written by myself.
Low-Rank plus Sparse Decomposition of Covariance Matrices using Neural Network Parametrization (with A. Neufeld, C. Herrera, and P. Ruyssen), [Arxiv], IEEE Transactions on Neural Networks and Learning Systems 34(1), 171-185, 2023.
Money Market Funds vulnerabilities and systemic liquidity crises, (with A. Bouveret (ESMA) and E. Schaanning (ECB)), accepted for publication in Journal of Banking and Finance [ssrn of an earlier version].
Reverse Stress Testing: Scenario Design for Macroprudential Stress Tests (with E. Schaanning), accepted for publication in Mathematical Finance (free access), top 5 paper at the Swiss Risk Award 2020 (Evidently, they got my first name incorrectly, the family name of my co-author has a spelling mistake, and they gave me an erroneous affiliation. But it's us!).
Existence, uniqueness, and stability of optimal payoffs of eligible assets (with P. Koch-Medina and C. Munari), Mathematical Finance 30 (1), 128-166, 2020.
A continuous selection for optimal portfolios under convex risk measures does not always exist (with C. Munari), Mathematical Methods of Operations Research 91 (1: Special issue - Set Optimization and Applications), 5-23, 2020.
Duality for Mixed-integer minimization (with T. Oertel and R. Weimantel), Mathematical Programming 158, 547–564, 2016.
Mirror-Descent Methods in Mixed-Integer Convex Optimization (with T. Oertel, C. Wagner, and R. Weismantel) In Facets of Combinatorial Optimization, 101-131, 2013.
A Randomized Mirror-Prox Method for Solving Structured Large-Scale Matrix Saddle-Point Problems (with M. Buergisser and A. Nemirovski), SIAM Journal on Optimization 23(2), 934–962, 2013.
Robust Risk Management (with A. Fertis and H.-J. Luethi), European Journal on Operations Research 222(3), 663-672, 2012.
Positive Polynomial Constraints for POD-based Model Predictive Controllers (with O. Aguledo, J. Espinoza, and M. Diehl), IEEE Transactions on Automatic Control 54(5), 988-999, 2009.
Every Continuous Nonlinear Control System Can be Obtained by Parametric Convex Programming (with M. Diehl and I. Necoara), IEEE Transactions on Automatic Control 53(8), 1963-1967, 2008.
Convexity and differentiability properties of spectral functions and spectral mappings on Euclidean Jordan algebras, Linear Algebra and its Applications 422(2-3), 664-700, 2007.
A manuscript often asked: Estimate sequence methods: extensions and approximations, 2009.
A book also often asked: Spectral Functions and Smoothing Techniques on Jordan Algebras: How algebraic techniques can help to design efficient optimization algorithms, 268 pages, Lambert Academic Publishing, 2009. Curiously available on ebay.
Robust Risk Aggregation under Covariance Uncertainty (with P. Cheridito, A. Neufeld, and M. Stefanik).
Cooking, hiking, reading literature. Albeit quasi tone-deaf, I am also an avid music listener.
Erdős Number: 3
Proof:
Minimizing Lipschitz-continuous strongly convex functions over integer points in polytopes (with A. Del Pia, S. Onn, Y. Nesterov, and R. Weismantel), Mathematical Programming 134, 305-322, 2012.
N. Alon, S. Onn, Separable Partitions, Discret. Appl. Math. 91(1-3), 39-51, 1999.
N. Alon, P. Erdős, Disjoint Edges in Geometric Graphs, Discret. Comput. Geom. 4, 287-290, 1989.