Leonardo Badia

Prof.
Leonardo Badia

leonardo.badia@gmail.com

Website

Leonardo Badia was born in Ferrara, Italy on May 22th, 1977. He received both the Laurea degree (summa cum laude) in electrical engineering and the Ph.D. in information engineering (with highest mark) from the University of Ferrara, in year 2000 and 2004, respectively. From 2000 to 2006 he was with the Department of Engineering, University of Ferrara. Between 2002 and 2003 he visited the RST Labs (now Wireless@KTH) at the Royal Institute of Technology (KTH), Stockholm, Sweden. In May 2006, he moved to the IMT Lucca Institute for Advanced Studies, Lucca, Italy, as an Assistant Professor. In March 2011 he joined the faculty of the University of Padova as an Assistant Professor. In 2016, he was promoted to Associate Professor.

He is author of more than 200 scientific papers published in international peer-reviewed journals or conferences. He is a frequent reviewer for several periodicals in the areas of telecommunications, computer engineering and networking. His research interests are in the broad area of mathematical optimization for communication networks, including: analysis of transmission protocols via Markov models; cross-layer optimization of routing/scheduling/resource allocation; Age-of-Information; models for energy harvesting; applications of game theory to communication networks.

Research

Network cross-layer optimization

Cross-layer optimization breaks the boundaries between layers of a communication model by consider joint optimization of multiple aspects at once. In particular, topics investigated relate to joint routing and scheduling, channel assignment, node positioning, and resource allocation. Such a complex task often requires resorting to meta-heuristic techniques such as genetic algorithms, multi-armed bandits, or other machine learning techniques.

Age-of-Information

Especially useful for remote sensing scenarios, Age-of-information (AoI) quantifies freshness of data by characterizing it as the time elapsed since the latest useful update. It involves closed-form computations from classic dynamic programming and queueing theory, also with possible repercussions on Game theory and linear programming.

Transmission protocol modelling via stochastic approaches

Markov models allow for rigorous analytical characterization of many transmission techniques. In particular, retransmission-based techniques such as ARQ or hybrid ARQ have been analyzed, considering different aspects such as delay characterization, performance of multimedia transmissions, resulting AoI.

Game theory

Game theory is the study of multi-person multi-objective problems. Yes, albeit the name is cool, it has little to do with video games (even though, strictly speaking even multi-player games belong to the category of multi-agent optimization). It allows precise representation of distributed management scenarios, which is extremely useful when analyzing network scenarios. Notably, it is not necessarily restricted to conflict situations, but it can also describe contexts where multiple players act without any coordination and therefore the management can be improved.

Teaching

My teaching activity spans several subjects in the broad area of Computer Science and Information Engineering.
I have taught university courses of Digital Signal Processing, Computer Networks, Fourier Analysis, Game Theory, Programming Languages. A full list is reported in the CV attached below.

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