Our paper entitled “A Distributed Multi-Sensor Machine Learning Approach to Earthquake Early Warning” was selected in the Artificial Intelligence for Social Impact track at AAAI-20. This work addresses the challenges of characterizing earthquake and issuing broadcast alerts in a matter of seconds by relying on an effective use of scientific instruments and large-scale detection. As … Read More
Two papers accepted at the 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGrid2020, rank A) next May in Melbourne. “Enhancing microservices architectures using data-driven discovery and QoS guarantees”. This work proposes a service discovery framework using a data-centric approach while ensuring performance guarantees for microservices. First publication of Zeina Houmani, my very … Read More
Our article “A Distributed Multi-Sensor Machine Learning Approach to Earthquake Early Warning” has been accepted at AAAI20, the 34th Conference on Artificial Intelligence. This paper introduces the Distributed Multi-Sensor Earthquake Early Warning (DMSEEW) system, a novel machine learning-based approach that combines data from GPS stations and seismometers to detect medium and large earthquakes. Preprint is … Read More
Programming reactive services with a fluid integration of EdgeComputing, Cloud and in-transit resources
Our recent work using R-Pulsar on operator placement and programming models for edge-based streaming analytics have been accepted to CCGRID2019 and PAISE2019.
Our paper Nu@ge: A container‐based cloud computing service federation is now published and available on Concurrency and Computation: Practice and Experience.