I joined  Université Côte d'Azur (UCA) as an assistant professor ("maître de conférences")  in Sept. 2021 and I am a member of the I3S laboratory and of project-team COATI. Before that, I was a postdoctoral researcher  working in the NEO team with Prof. Giovanni Neglia at Inria Sophia Antipolis from 2018 to 2021. I received my PhD in Computer Science from Université Paris-Saclay in Dec. 2017 under the supervision of Prof. Joffroy Beauquier et Prof. Janna Burman. 

My research interests include :

• Distributed machine learning, federated learning

• Population protocols, self-stabilizing distributed algorithms

• Energy problems in mobile wireless sensor networks

• Chance constrained program (stochastic optimization)

PUBLICATIONS 

• C. Kaplan, C.Xu,  O.Marfoq, G.Neglia, A. Santana de Oliveira. A Cautionary Tale: On the Role of Reference Data in Empirical Privacy Defences. Proceedings on Privacy Enhancing Technologies 2024(1), 525–548.

• I.Driouich, C.Xu, G.Neglia, F.Giroire, E.Thomas, A novel model-based attribute inference attack in federated learning, FL-NeurIPS22, Dec 2022.

• O. Zari, C. Xu, G. Neglia, Efficient Passive Membership Inference Attack in Federated Learning, NeurIPS workshop on Privacy in Machine Learning (PriML), Dec 2021, Online. 

• C. Xu, G. Neglia, What else is leaked when eavesdropping Federated Learning?, ACM CCS workshop on Privacy Preserving Machine Learning (PPML), selected contributed talk, Nov 2021, Online. 

• J. Burman,  H. Chen, H. Chen, D. Doty, T. Nowak, E. Severson, C. Xu, Efficient self-stabilizing leader election in population protocols, PODC 2021.

• K. Pan, D. He, C.Xu, Local Model Privacy-preserving Study for Federated Learning, SecureComm 2021.

• C. Xu, G. Neglia, N. Sebastianelli, Dynamic Backup Workers for Parallel Machine Learning, Elsevier Computer Networks, Volume 188, 7 April 2021.

• O. Marfoq, C. Xu, G. Neglia, R. Vidal. Throughput-Optimal Topology Design for Cross-Silo Federated Learning , NIPS 2020. 

• C. Xu, G. Neglia, N. Sebastianelli, Dynamic Backup Workers for Parallel Machine Learning, IFIP Networking 2020. 

• G. Neglia, C. Xu, D. Towsley, G. Calbi. Decentralized gradient methods: does topology matter?,  AISTATS2020

• C. Xu, J. Beauquier, J. Burman, S. Kutten, T. Nowak, Data collection in population protocols with non-uniformly random scheduler, Theorectical Computer Science, Volume 806, pp. 516-530, 2020

• C. Xu, G. Bouvier, B. Bardiaux, M. Nilges, T. Malliavin, A. Lisser , Ordering protein contact matrices, Computational and Structural Biotechnology Journal, Volume 16, pp. 140-156, Elsevier, 2018.

• C. Xu, J. Burman, and J. Beauquier, "Power-aware population protocols," in IEEE 37th International Conference on Distributed Computing Systems (ICDCS), pp. 2067-2074, June 2017. 

• J. Beauquier, J. Burman, S. Kutten, T. Nowak, and C. Xu,  "Data Collection in Population Protocols with Non-uniformly Random Scheduler," in Algorithms for Sensor Systems - 13th ALGOSENSORS, Vienna, Austria, September 2017. 

• C. Xu, J. Cheng, and A. Lisser, "A sampling method to chance-constrained semidefinite optimization," in ICORES 2015 - Proceedings of the International Conference on Operations Research and Enterprise Systems, pp. 75-81, 2015. 

• C. Xu, A. A. Gaivoronski, and A. Lisser, "Stochastic bilevel network design problems," in 13th Cologne Twente Workshop on Graphs and Combinatorial Optimization, pp. 261-264, 2015.

• P. Adasme, A. Lisser, and C. Xu, "A multicommodity formulation for routing in healthcare wireless body area networks," in ICORES 2014- Proceedings of the 3rd International Conference on Operations Research and Enterprise Systems, pp. 409-416, 2014.

• C. Xu, A. Lisser, J. Leung, and M. Letournel, "The p-median problem with concave costs.," in ICORES 2014- Proceedings of the 3rd International Conference on Operations Research and Enterprise Systems, pp. 205-212, 2014.

SUPERVISION

PhD students:

• Ilias Driouich (co-supervised with Frédéric Giroire et Giovanni Neglia)

• Caelin Kaplan (co-supervised with Giovanni Neglia)

DISSERTATION

• C. Xu, Power-Aware Protocols for Wireless Sensor Networks. University of Paris Saclay, France, Dec. 2017. 

Advisors: Prof. Joffroy Beauquier and Prof. Janna Burman

CONFERENCE PRESENTATIONS 

• C. Xu, "Communication topologies for decentralized gradient methods", InThingS 2020, Invited talk. 

• J. Beauquier, J. Burman, and C. Xu, "Économie d' energie dans les protocoles de population," in ALGOTEL 2017-19èmes Rencontres Francophones sur les Aspects Algorithmiques des Télécommunications, 2017. 

• C. Xu, A. Lisser, and R. Frenz, "A semidefinite programming relaxation for vertex separator problem," in ROADEF-15 eme congrès annuel de la Société française de recherche opérationnelle et d'aide à la décision, 2014. 

• C. Wang, C. Xu, and A. Lisser, "Bandwidth minimization problem," in MOSIM 2014, 10ème Conférence Francophone de Modélisation, Optimisation et Simulation, 2014.

TEACHING

• Federated Learning, 09/2024, Université Côte d'Azur, Master 2 IF, 2024

• Python3, 10/2023, Université Côte d'Azur, MIAGE IA2, 2023

• Python pour l'IA, 10/2022, Université Côte d'Azur, License 3 spécialité IA, 2022

• Programmation fonctionnelle, 09/2022, Université Côte d'Azur, License 3 d'Informatique, 2022

• Python pour l'IA, 10/2021, Université Côte d'Azur, License 3 spécialité IA, 2021

• Programmation fonctionnelle, 09/2021, Université Côte d'Azur, License 3 d'Informatique, 2021

• Optimization for Machine Learning, 03/2021, Université Cote d'Azur, MSc Data Science and Artificial Intelligence,  2021

• Distributed Optimization and Games, 02/2020, Université Cote d'Azur, Ubinet Master and MSc Data Science and Artificial Intelligence, 2020

• Hands-on Machine Learning ,Winter School 2019, Université Cote d'Azur,  Master 1 International in Computer Science, 2019

• Continuous and combinatorial optimization, Paris-Salcay, M1

• Advanced algorithms, Paris-Saclay, M1

• Operations research, Paris-Saclay, M1 

• Formal languages and automata , Paris-Saclay, L2