Marco Guazzone
Associate Professor
Piedmont, Italy
Summary
👤
Senior🎓
Top SchoolMarco Guazzone is an Associate Professor and researcher with 13 years of experience specializing in distributed systems, Grid and Cloud computing, and energy- and performance-aware resource management. Based in Piedmont, Italy, he blends academic rigor from a PhD in Computer Science with practical contributions to open-source numerical libraries, notably implementing the Hyper-Exponential distribution in Boost.Math. His work focuses on green computing, workload characterization, and performance models that inform automatic resource management and SLA preservation for next-generation distributed platforms. Marco’s career progressed through successive research and faculty roles where he led studies on power-performance trade-offs and mobile forensics automation, demonstrating a strong track record of applied research. He is comfortable bridging deep mathematical implementation details with system-level strategies, making him effective at translating models into deployable resource-management solutions.
14 years of coding experience
7 years of employment as a software developer
Master's degree, Computer Science, Master's degree, Computer Science at University of Piemonte OrientaleDoctor of Philosophy (PhD), Science and High Technology (spec. Computer Science), Doctor of Philosophy (PhD), Science and High Technology (spec. Computer Science) at Università degli Studi di Torino
English, Italian
Github Skills (7)
mathematical10
c-language10
probability-distribution10
cprogramming-language10
distributions10
modeling10
testing9
Programming languages (7)
Github contributions (5)
boostorg/math
Aug 2014 - Sep 2014
Boost.org math module
Role in this project:
Back-end Developer
Back-end DeveloperContributions:36 commits in 18 days
Contributions summary:Marco's primary contribution involved the implementation of the Hyper-Exponential distribution within the Boost.org math module. This included adding the core functionality for the distribution, modifying existing code to implement the distribution effectively, and solving related warnings, and fixing testing issues. The user's work focused on the mathematical aspects of the distribution and its integration within the existing math library. The user's work also included improving test units to support the `long double` type and cleaning up and finalizing the documentation.
eigenvaluesmathmathematicsmultiprecisiondeterministic
sguazt/dcsxx-testbed
Apr 2015 - Jul 2017
Contributions:103 pushes, 1 tag in 2 years 3 months
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