Romaric Duvignau
Associate Professor at Chalmers University of Technology with expertise in distributed systems, network security, and IoT/CPS applications. My research focuses on optimizing communication and computational efficiency for different distributed applications. Through the design and evaluation of data-driven algorithms and continuous optimization methods, my research aims to enhance real-world distributed platforms e.g., data management in vehicular networks, optimizing energy resources at the smart grid's edge, and improving the privacy of popular protocols. I’m also interested in federated learning, network traffic classification, and cybersecurity challenges. Engaged in advancing engineering education, I am exploring the integration of novel pedagogic techniques and tools within my teaching. Open to collaborations and seeking innovative approaches and formal analysis to enhance the resilience and performance of distributed networked systems in diverse, real-world contexts.
Visar 21 publikationer
Self-stabilizing Byzantine Multivalued Consensus: (extended abstract)
Efficient Monitoring of CPS and IoT Systems: A Deployment Guide for Empirical Evaluations
How to Better Teach Computer Networks to Freshman Engineers Post-Pandemic, A Case Study
Cost-Optimization for Win-Win P2P Energy Systems
Self-stabilizing Byzantine fault-tolerant repeated reliable broadcast
How to Better Teach Computer Networks to First Year Engineering Students Post-pandemic, A Case Study
Greediness is not always a vice: Efficient Discovery Algorithms for Assignment Problems
Efficient and scalable geographical peer matching for P2P energy sharing communities
Metainformation Extraction from Encrypted Streaming Video Packet Traces
GeoRep - Resilient Storage for Wide Area Networks
Self-stabilizing Byzantine Fault-Tolerant Repeated Reliable Broadcast
Time- and Computation-Efficient Data Localization at Vehicular Networks' Edge
Benefits of small-size communities for continuous cost-optimization in peer-to-peer energy sharing
Small-Scale Communities Are Sufficient for Cost- and Data-Efficient Peer-to-Peer Energy Sharing
DRIVEN: A framework for efficient Data Retrieval and clustering in Vehicular Networks
Streaming Piecewise Linear Approximation for Efficient Data Management in Edge Computing
Querying Large Vehicular Networks: How to Balance On-Board Workload and Queries Response Time?
Continuous Distributed Monitoring in the Evolved Packet Core
DRIVEN: a Framework for Efficient Data Retrieval and Clustering in Vehicular Networks
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Visar 9 forskningsprojekt
READY: Rethinking Monitoring for Large Distributed Systems
TRUSTCOM: Paketspårningsigenkänning över instabila kommunikationskanaler
HyperP2P: Bipartite hypergrafmatchningar för peer-to-peer energidelning
SESBC TANDEM: Intelligent hantering av energidata och beslutsfattande i realtid
DEEP: Dynamic and Efficient Energy-sharing P2P networks
AutoSPADA (Automotive Stream Processing and Distributed Analytics) OODIDA Phase 2
INDEED: Information and Data-processing in Focus for Energy Efficiency
BADA - On-board Off-board Distributed Data Analytics