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e-mail andrea.araldo@telecom-sudparis.eu

Andrea Araldo is Associate Professor at Institut Polytechnique de Paris - Telecom SudParis, where he teaches Machine Learning for Networks.

His current research interests are Networked Systems Optimization, Edge Computing, Smart Mobility. He was awarded the French national Young Researcher funding (ANR JCJC) for the project "Multimodal Transit for Accessibility and Sustainability" (2022-26).

He received a MSc degree in Computer Engineering (2012) from Universita di Catania (Italy) and a PhD degree in Computer Science from Université Paris Saclay (France - 2016). He was visiting researcher at KTH Royal Institute of Technology (Sweden - 2016) and Postdoctoral Associate Researcher at the Massachusetts Institute of Technology (US - 2017-18) in the Intelligent Transportation Systems Lab.

He received the IEEE ComSoc Best Paper Award in 2018 (best paper among 16 IEEE conferences in 2016 and 2017) and a Best Paper Award at the International Workshop on TRaffic Analysis and Characterization(TRAC) in 2014.

He worked in Tripod, a project funded by the Department of Energy, US, where he led the design and the development of the Mobility on Demand module of the open source transport simulator "SimMobility" and the activities related to the scalability of the rolling horizon optimization. He led two 1-year French projects on smart mobility and obtained seed funding from BayFrance (Franco-Bavarian cooperation center) and Hi!Paris (Center on Data Analytics and Artificial Intelligence for Science, Business and Society). He was in the design and development teams of several open source projects related to simulation of computer and transportation networks.

He is in the editorial board Elsevier Computer Communications. He was co-chair of ACM Sigmetrics workshop on Distributed Cloud Computing and member of the TPC of International Teletraffic Congress, ACM Symposium on Applied Computing, Network Traffic and Analysis Conf., ACM SIGCOMM Workshop on Big Data Analytics and Machine Learning for Data Communication Networks (Big-DAMA).