Carla Fabiana Chiasserini
Carla Fabiana Chiasserini is Full Professor at Politecnico di Torino, Italy, and a Research Associate with the CNR-IEIIT and CNIT. She is currently a Wallenberg AI, Autonomous Systems and Software Program (WASP) Guest Professor at Chalmers University, Computer Science and Engineering Department. She was a Visiting Researcher at UC San Diego (1998-2003), and a Visiting Professor at Monash University (2012, 2016) , at the Berlin Technische Universität (2021, 2022), and at HPI, Potsdam University (2023), Germany. She is an IEEE Fellow and a Senior Member of ACM. Wallenberg AI, Autonomous Systems and Software Program (WASP) Guest Professor
Her research interests include NextG Networks, Edge Computing, Machine Learning, and Connected Vehicles. She has published over 350 journal and conference papers and has received several awards for her scientific work. She serves as Editor-in-Chief of Computer Communications and Associate EiC for IEEE Transactions on Network Science and Engineering, and as Editor-at-Large of the IEEE/ACM Transactions on Networking.
Showing 24 publications
Fenics: A Modular Framework for Security Evaluation in Decentralized Federated Learning
Integrating Homomorphic Encryption and Synthetic Data in FL for Privacy and Learning Quality
Human-centric decision-making in cell-less 6G networks
O-RAN Intelligence Orchestration Framework for Quality-Driven Xapp Deployment and Sharing
Combining Relevance and Magnitude for Resource-saving DNN Pruning
Enabling efficient collection and usage of network performance metrics at the edge
Enabling Wearables towards the Metaverse: Trade-Offs Involving Blockage and Heat
Distributing Inference Tasks Over Interconnected Systems Through Dynamic DNNs
Dynamic Management of Constrained Computing Resources for Serverless Services
MOSE: A Novel Orchestration Framework for Stateful Microservice Migration at the Edge
Resource-Efficient Sensor Fusion at the Edge via System-wide Dynamic Gated Neural Networks
Achieving Machine Learning Dependability Through Model Switching and Compression
Distributed Learning with Memory: Optimizing Model Usage across Training Tasks
Tensor Compression and Reconstruction in Split DNN for Real-time Object Detection at the Edge
Adaptive Autopilot: Constrained Drl for Diverse Driving Behaviors
Resource-aware Deployment of Dynamic DNNs over Multi-tiered Interconnected Systems
Resource-Efficient Sensor Fusion via System-Wide Dynamic Gated Neural Networks
OREO: O-RAN intElligence Orchestration of xApp-based network services
Morphable Networks for Cross-Layer and Cross-Domain Programmability: A Novel Network Paradigm
AI/ML-based services and applications for 6G-connected and autonomous vehicles
Dependable Distributed Training of Compressed Machine Learning Models
Target Wake Time Scheduling for Time-Sensitive Networking in the Industrial IoT
Data-Driven and Privacy-Preserving Cooperation in Decentralized Learning
OffloaDNN: Shaping DNNs for Scalable Offloading of Computer Vision Tasks at the Edge
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