Research output per year
Research output per year
Personal profile
Research Overview
Professor Canini‘s research interests are in the principled construction and operation of large scale networked computer systems, specifically in distributed systems, large-scale computing and computer networking with emphasis on cloud computing and programmable networks. His current work focuses on improving networked systems design, implementation and operation along several vital properties such as reliability, performance, security and energy efficiency.
Key Research Areas
Computer Science, Extreme Computing
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
Education
Communication, Computer and System Sciences, Ph.D., University of Genoa
2009
Award Date: Jan 1 2009
Communication, Computer and System Sciences, B.S., University of Genoa
2005
Award Date: Jan 1 2005
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Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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A Comprehensive Empirical Study of Heterogeneity in Federated Learning
Abdelmoniem, A. M., Ho, C-Y., Papageorgiou, P. & Canini, M., Mar 7 2023, In: IEEE Internet of Things Journal. p. 1-1 1 p.Research output: Contribution to journal › Article › peer-review
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In-Network Aggregation with Transport Transparency for Distributed Training
Liu, S., Wang, Q., Zhang, J., Wu, W., Lin, Q., Liu, Y., Xu, M., Canini, M., Cheung, R. C. C. & He, J., Mar 25 2023, Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 3. ACM, p. 376-391 16 p.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
1 Scopus citations -
TENSOR: Lightweight BGP Non-Stop Routing
Miao, C., Xiao, Y., Canini, M., Dai, R., Zheng, S., Wang, J., Bu, J., Kuzmanovic, A. & Wang, Y., Sep 2023, Proceedings of the ACM SIGCOMM 2023 Conference. ACMResearch output: Chapter in Book/Report/Conference proceeding › Conference contribution
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With Great Freedom Comes Great Opportunity: Rethinking Resource Allocation for Serverless Functions
Bilal, M., Canini, M., Fonseca, R. & Rodrigues, R., May 5 2023, Proceedings of the Eighteenth European Conference on Computer Systems. ACMResearch output: Chapter in Book/Report/Conference proceeding › Conference contribution
1 Scopus citations -
Empirical analysis of federated learning in heterogeneous environments
Abdelmoniem, A. M., Ho, C-Y., Papageorgiou, P. & Canini, M., Apr 5 2022, Proceedings of the 2nd European Workshop on Machine Learning and Systems. ACM, p. 1-9 9 p.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
7 Scopus citations -
RDMA is Turing complete, we just did not know it yet!
Reda, W., Canini, M., Kostic, D. & Peter, S., 2022, 19th USENIX Symposium on Networked Systems Design and Implementation (NSDI). arXiv, p. 71-85 15 p.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
8 Scopus citations -
Analyzing Learning-Based Networked Systems with Formal Verification
Dethise, A., Canini, M. & Narodytska, N., 2021, IEEE INFOCOM 2021 - IEEE Conference on Computer Communications. IEEEResearch output: Chapter in Book/Report/Conference proceeding › Conference contribution
4 Scopus citations -
AUTOLRS: AUTOMATIC LEARNING-RATE SCHEDULE BY BAYESIAN OPTIMIZATION ON THE FLY
Jin, Y., Zhou, T., Zhao, L., Zhu, Y., Guo, C., Canini, M. & Krishnamurthy, A., 2021, ICLR 2021.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Prizes
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Full Ph.D. scholarship from the University of Genoa
Canini, Marco (Recipient), 2006
Prize: Award or Honor › Early Career or Student Award
Press/Media
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Microsoft at EuroSys 2023: Systems innovation across the stack to help support an easier, faster, safer, and smarter cloud
05/12/23
1 item of Media coverage
Press/Media: Press / Media
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Improve Machine Learning Performance by Dropping the Zeros
08/24/21
1 item of Media coverage
Press/Media: Press / Media
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KAUST Collaboration with Intel, Microsoft and University of Washington Accelerates Training in ML Models
04/12/21
1 item of Media coverage
Press/Media: Press / Media
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Machine learning at speed
Marco Canini, Panos Kalnis & Peter Richtarik
04/12/21
5 items of Media coverage
Press/Media: Press / Media
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What’s New in HPC Research: Tundra, Fugaku, µHPC & More
04/6/21
1 item of Media coverage
Press/Media: Press / Media