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I am currently a Postdoctoral Research Associate at Uncertainty Quantification Group at MIT, working with Youssef Marzouk. I am interested in problems that lie at the intersection of applied mathematics, signal processing, and machine learning. Currently, I am researching new representations of sets and probability measures, with a focus on their application in the field of optimal experimental design. I completed my Ph.D. in theoretical signal processing and machine learning at Centrale Lille, under the supervision of Pierre Chainais and Rémi Bardenet. My work includes subset selection problems, quadrature rules and interpolation methods using determinantal point processes. Before joining MIT, I collaborated with Rémi Gribonval on compressive learning using sketching methods at ENS de Lyon.