= Alexandre Belloni
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<Alexandre Belloni> works across <optimization>, <econometrics> and <high-dimensional statistics>. His Chicago Booth profile describes research connecting statistical inference with decisions under limited information.https://www.chicagobooth.edu/faculty/directory/b/alex-belloni[Institutional research biography]{ref}
With <Victor Chernozhukov> and <Lie Wang>, he formulated the <Square-root Lasso> as a convex conic optimization problem. This connects a statistically pivotal tuning rule with algorithms for <convex optimization>, giving a computable sparse regression estimator without a preliminary estimate of noise scale.<Square-Root Lasso: Pivotal Recovery of Sparse Signals via Conic Programming by Alexandre Belloni and others>[Abstract and section 1, optimization formulation]{ref}
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