We develop techniques and algorithms for building and managing key networked systems that are worthy of society’s trust. Our core interests lie in improving the modern computing environment where distributed systems and computer networks are a pervasive component.
Our goal is to enrich the human knowledge of how to build future-proof systems that can stand the test of time.
Marco’s research area is cloud computing, distributed systems and networking. His current interest is in designing better systems support for AI/ML and provide practical implementations deployable in the real-world.
Marco is an associate professor of Computer Science at King Abdullah University of Science and Technology (KAUST). Marco obtained his PhD from the University of Genoa in 2009 after spending the last year as a visiting student at the University of Cambridge. He was a postdoctoral researcher at EPFL and then a Senior Research Scientist at Deutsche Telekom Innovation Labs & TU Berlin. In 2013, he assumed an assistant professor position at UCLouvain, and in 2016 he became an Assistant Professor at KAUST. He was promoted to the rank of Associate Professor at KAUST in 2019. He also held positions at Intel Research, Google and Microsoft Research.
A Flexible and High-Fidelity Approach to Distributed DNN Training Emulation
Collaborative Learning Experimentation Testbed
An Efficient Statistical-Based Gradient Compression Technique for Distributed Training Systems
Efficient Sparse Collective Communication
GRAdient ComprEssion for distributed deep learning
A Systems Approach to Tackling Fairness in Federated Learning
Delay-aware Communication Control for Distributed ML
Scaling Distributed Machine Learning with In-Network Aggregation
In-Network Computation is a Dumb Idea Whose Time Has Come
Previous major projects focusing on SDN and programmable networks include:
I’m always looking for bright and enthusiastic people to join my group. If you are looking to do a PhD with me, thank you for your interest, but please read this first. If you don’t I will know, and I’m afraid I will have to ignore your message.