Towards a generic deep learning pipeline for traffic measurements. - Raphaël Azorin; Massimo Gallo; Alessandro Finamore; Maurizio Filippone; Pietro Michiardi; Dario Rossi 001 (StudentWorkshop@CoNEXT, 2021)

A Reproducible Approach for Mining Business Activities from Emails for Process Analytics. - Raphaël Azorin; Daniela Grigori; Khalid Belhajjame (ICSOC Workshops, 2021)

Learned data structures for per-flow measurements. - Andrea Monterubbiano; Raphaël Azorin; Gabriele Castellano; Massimo Gallo; Salvatore Pontarelli (StudentWorkshop@CoNEXT, 2022)

Towards a systematic multi-modal representation learning for network data. - Zied Ben-Houidi; Raphaël Azorin; Massimo Gallo; Alessandro Finamore; Dario Rossi 001 (HotNets, 2022)

Memory-efficient Random Forests in FPGA SmartNICs. - Andrea Monterubbiano; Raphaël Azorin; Gabriele Castellano; Massimo Gallo; Salvatore Pontarelli; Dario Rossi 001 (CoNEXT (Short Papers), 2023)

"It's a Match!" - A Benchmark of Task Affinity Scores for Joint Learning. - Raphaël Azorin; Massimo Gallo; Alessandro Finamore; Dario Rossi 001; Pietro Michiardi (CoRR, 2023)

SPADA: A Sparse Approximate Data Structure Representation for Data Plane Per-flow Monitoring. - Andrea Monterubbiano; Raphaël Azorin; Gabriele Castellano; Massimo Gallo; Salvatore Pontarelli; Dario Rossi 001 (PACMNET, 2023)

Fine-grained Attention in Hierarchical Transformers for Tabular Time-series. - Raphaël Azorin; Zied Ben-Houidi; Massimo Gallo; Alessandro Finamore; Pietro Michiardi (CoRR, 2024)

Taming the Elephants: Affordable Flow Length Prediction in the Data Plane. - Raphaël Azorin; Andrea Monterubbiano; Gabriele Castellano; Massimo Gallo; Salvatore Pontarelli; Dario Rossi 001 (Proc. ACM Netw., 2024)