Marco Claudio Campi is an engineer and a mathematician who specializes in data science and inductive methods. He is a co-creator of the so-called "scenario approach"[1][2][3][4][5][6][7][8] (see scenario optimization). In 2012 he was elevated to the grade of Fellow of the Institute of Electrical and Electronics Engineers (IEEE) for contributions to stochastic and randomized methods in systems and control. In 2008, he was bestowed the George S. Axelby Award. He holds a permanent appointment with the University of Brescia, Italy, while also collaborating with various research institutions, universities and NASA.
References
^M.C. Campi and S. Garatti. Introduction to the Scenario Approach., MOS-SIAM Series on Optimization, 2018. [1]
^G. Calafiore and M.C. Campi. Uncertain Convex Programs: Randomized Solutions and Confidence Levels. Mathematical Programming, 102: 25–46, 2005. [2]
^G. Calafiore and M.C. Campi. "The scenario approach to robust control design," IEEE Transactions on Automatic Control, 51(5). 742-753, 2006. [3]
^M.C. Campi and S. Garatti. The Exact Feasibility of Randomized Solutions of Uncertain Convex Programs. SIAM J. on Optimization, 19, no.3: 1211–1230, 2008.[4]
^A. Caré, S. Garatti and M.C. Campi.Scenario min-max optimization and the risk of empirical costs. SIAM Journal on Optimization, 25, no.4: 2061-2080, 2015, Mathematical Programming, published online, 2016. [5]
^M.C. Campi and S. Garatti. A Sampling-and-Discarding Approach to Chance-Constrained Optimization: Feasibility and Optimality. Journal of Optimization Theory and Applications, 148, Number 2, 257–280, 2011. [6]
^M.C. Campi and S. Garatti. Wait-and-judge scenario optimization. Mathematical Programming, vol.16, pp. 481-499, 2019. [7]
^S. Garatti and M.C. Campi. Risk and complexity in scenario optimization. Mathematical Programming, published online, 2019. [8]
