Lorenzo Maggi holds a PhD in applied mathematics and a Master’s Degree in telecommunication engineering from Eurecom (France) and University of Pavia (Italy), respectively.
He is research scientist at Nokia Bell Labs, where he designs algorithmic solutions for 5G networks on beamforming, energy efficiency, power control, and radiation mitigation. Several of such use cases have been showcased in customer network trials.
Prior to that, Lorenzo worked at Huawei Technologies on algorithmic solution for fixed network, and routing in particular.
He relishes working at the border between theory and practice.
Selected articles and publications
- Lorenzo Maggi, Alvaro Valcarce, and Jakob Hoydis. "Bayesian optimization for radio resource management: Open loop power control." IEEE Journal on Selected Areas in Communications 39.7 (2021): 1858-1871.
- Stephan Kunne, Lorenzo Maggi, Johanne Cohen, and Xinneng Xu. "Anytime Backtrack Unimodal Bandits and Applications to Cloud Computing." 2020 IFIP Networking Conference (Networking). IEEE, 2020.
- Antonio Massaro, Francesco De Pellegrini, and Lorenzo Maggi. "Optimal trunk-reservation by policy learning." IEEE INFOCOM 2019-IEEE Conference on Computer Communications. IEEE, 2019.
Honors & Awards
Best paper award at WiOpt 2014 and ITC 2017