Chuan XU
Office L002, Bât. Lagrange,
Inria Sophia Antipolis,
2004, route des Lucioles, Valbonne, France
Email: chuan.xu@inria.fr
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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
F. Diana, A. Nusser, C. Xu, G. Neglia, Cutting through privacy: a hyperplane-based data reconstruction attack in federated learning. The 41st Conference on Uncertainty in Artificial Intelligence, July 2025, Rio de Janeiro, Brazil.
F. Diana, O. Marfoq, C. Xu, G. Neglia, F. Giroire, E. Thomas, Attribute inference Attacks for federeated regression tasks. 39th Annual AAAI Conference on Artificial Intelligence, Feb 2025, Philadelphia , United States.
O. Zari, C. Xu, J. Parra-Arnau, A. Ünsal, M. Önen, Link Inference Attacks in Vertical Federated Graph Learning. ACSAC 2024 - 40th Annual Computer Security Applications Conference. Honolulu, United States, 9th Dec. 2024
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:
Francesco Diana (co-supervised with 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
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
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