معرفی
Alessio Mora is a postdoctoral researcher at the Department of Computer Science and Engineering (DISI), University of Bologna, specializing in decentralized learning techniques such as Federated Learning. His work focuses on communication efficiency, heterogeneous data handling, and distributed AI systems.
- PhD in Computer Science and Engineering, University of Bologna (2023)
- Master in Computer Engineering, University of Bologna (2019)
- Bachelor in Computer Engineering, University of Bologna (2016)
His research spans decentralized learning, federated learning, and their applications in Industry 4.0, IoT, and edge computing. Key themes include model optimization, communication efficiency, and heterogeneous data distribution in cross-device settings.
Recent publications highlight trends in federated learning infrastructure, including unlearning methods, knowledge distillation, and sparse compression techniques. His work integrates theoretical analysis with practical implementations in industrial and IoT contexts.
- Summer of Reproducibility Award – Flower Labs (2023)
Awarded $2,000 USD for implementing and reproducing the FedMLB baseline in Flower, advancing reproducibility in federated learning.
Mora has contributed to European projects like OntoTrans and SimDOME, focusing on ontology-based systems for materials modeling and industrial data translation. His technical expertise includes Docker, Stardog triplestore, FastAPI, and Python wrappers for chemical simulation tools.
