What do we do?

We study specific AI models applied to network problems like mobile traffic forecasting and resource allocation and develop tools that augment the understanding of the corresponding models’ logic and their robustness. We strive to ensure that explanations are comprensible and actionable, i.e., network experts can relate the semantic of the explanations with their expert knowledge and the knowledge of the explanations can be capitalized by routines and algorithms for further optimizations. Examples of such tools are DeExp, EXPLORA, and AIChronoLens.

NEWS

• • ★ Nov – 24. Claudio joins the TPC of ACM CoNEXT 2025
  • ★ Sep – 24. ACM has evaluated the artifacts of our 5G study as available and functional!
  • ★ Aug – 24. Claudio joins the TPC of IEEE INFOCOM 2025
  • ★ Jun – 24. Our 5G cross-country measurement study is accepted at ACM SIGCOMM (congrats Ross, Eman, Jason, Lilian, Faaiq, Wei, Joerg, Feng and Zhi-li)
  • ★ Apr – 24. AIChronoLens is recipient of the Best Paper Award at IEEE INFOCOM 2024! Congrats to the team for the impressive achievement
  • ★ Mar – 24. Claudio will deliver a talk on Explainable AI for 6G Mobile Networks at the Applied Machine Learning Days at EPFL in Losanne
  • ★ Jan – 24. Abhishek joins as PhD student in the context of the national project bRAIN. Welcome aboard.
  • ★ Dec – 23. SAFE was very successful: more than 15 attendees contributed a fruitful discussion on topics of AI explainability, safety and robustenss.
  • ★ Dec – 23. Two papers accepted at IEEE INFOCOM 2024! One presents AIChronoLens, a new tool for AI time-series explainability (congrats to the team Eloy, Pablo, Hossein, Marco and Joerg). The second presents a study on roaming with 5G based on a measurement data campaing in Spain, France, Germany and Italy (congrats Ross, Eman, Jason, Daqing, Yiling, Feng, Joerg and Zhi-li).
  • ★ Dec – 23. MohammadErfan joins as research engineer in the context of the national project bRAIN. Welcome aboard.
  • ★ Nov – 23. Artifact available & functional & reproduced! ACM has evaluated EXPLORA’s artifacts and awarded all the reproducibility badges to our work.
  • ★ Nov – 23. Accepted paper at ACM CoNEXT! We will present our work EXPLORA, a tool that generates explanations to understand and control the logic of Deep Reinforcement Learning agents applied to network slicing in Open RAN systems. Work done in collaboration with Leonardo Bonati, Salvatore D’Oro, Michele Polese and Tommaso Melodia from Northeastern University and Joerg Widmer from IMDEA.
  • ★ Oct – 23. We received the Best Paper Runner-Up at ACM WiNTECH for our work that makes publicly available a unique dataset of LTE control information at millisecond level, the granularity of the actual operation of the LTE network. This dataset is instrumental to the design of AI/ML techniques.