Richard Oliveira

Hello! My name is Richard, and I'm a Marie Skłodowska-Curie doctoral fellow and Phd candidate at Politecnico di Milano, Italy, in the department of Electronics, Information Technology, and Bioengineering (DEIB) and the department of Mathematics (DMAT), under the supervision of Dr. Stefano Savazzi. Furthermore, I am also affiliated with the Institute of Electronics, Computer and Telecommunication Engineering (IEIIT) at the Consiglio Nazionale delle Ricerche.

My background can be broadly defined as that of a Mathematical Engineer with a focus on developing mathematical models for how information is acquired, communicated and processed in engineered systems, with applications in control, computation and Machine Learning. My research focuses on networked dynamical systems, ranging from social and socio-technical networks to sensor-actuator networks, and devising distributed optimization methods that integrate economic, engineering, social, and environmental goals. Specifically, my doctoral research focuses on Bayesian Federated Learning techniques for localization and mapping, employing incentive-driven, game-theoretic models to manage client participation in both centralized and decentralized settings, and studying frequentist and Bayesian approaches to guide complex networks toward targeted objectives.

I received my MSc. in Electrical Engineering, Signal and Image Processing and a BSc. in Electrical Engineering, Machine Learning and Controls from the Electrical and Computer Engineering Department at the University of California, San Diego, La Jolla, USA. During my MSc. studies I have worked on the theory of Discrete Pearson-Rayleigh Random Walks under the supervision of Prof. Massimo Franceschetti.

My additional research interests include inverse problems and mathematical signal processing.