Lorenzo Pappone

Saint Louis University

Dept. of Computer Science

1 N. Grand Blvd.

St. Louis, MO 63103 USA

I am a PhD student in Computer Science under the advisement of Dr. Flavio Esposito, at Saint Louis University, where I am part of the Networking Research Group (NRG). My research interests are Machine Learning Systems, Datacenter Networks and Network Optimization.

My research can be divided in two areas: one is exploring the design and deployment of DL/ML models for network optimization tasks; a second area is distributed DL training acceleration using in-network computing. Some of my recently published work and ongoing projects are specifically investigating: reinforcement learning for congestion control, super-resolution for traffic matrix estimation, in-network machine learning and in-network aggregation (INA) for distributed deep learning.

News

[Feb 2025]	I am excited to announce that I will join Cisco as a Machine Learning Engineer Intern in San Francisco, CA!
[Jan 2025]	I have been selected for the 2025-26 Saint Louis University (SLU) Dissertation Fellowship Award! This award is given to only one Ph.D. student across the entire University. I am honored to receive this award and grateful for the support from my advisor and the department.
[Jan 2025]	Great news! Our paper “RobinHood: Collaborative Burst Mitigation Through In-Network Packet Deflection” has been accepted at 2025 IEEE International Conference on Communications (ICC)!
[Dec 2024]	Our paper “On Traffic Matrix Estimation via Super-Resolution and Federated Learning” has been accepted at Transactions of Network and Service Management (special issue)!
[Aug 2024]	Our paper “ResCue: Inferring Fine-Grained Traffic Matrices via Distributed Deep Residual Networks” has been accepted at IEEE/IFIP 20th International Conference on Network and Service Management (CNSM) in Prague, Czech Republic! 🎉
[Jul 2024]	Great news! Our work “Mutant: Learning Congestion Control from Existing Transport Protocols” has been accepted at the 22nd USENIX Symposium on Networked Systems Design and Implementation (NSDI)! 🎉
[Jul 2024]	We got a paper accepted at the IEEE/IFIP 20th International Conference on Network and Service Management (CNSM): “Addressing Data Security in IoT: Minimum Sample Size and Denoising Diffusion Models for Improved Malware Detection”.
[Jun 2023]	Our work entitled “Dealing with Changes: Resilient Routing via Graph Neural Networks and Multi-Agent Deep Reinforcement Learning” has been accepted at IEEE Transactions on Network and Service Management.
[May 2023]	Started an internship as a Visiting Researcher at Boston University, Boston, MA, USA, under the advisement of Dr. Abraham Matta.
[Nov 2022]	Our work entitled “A Federated Learning Approach to Traffic Matrix Estimation using Super-resolution Techniques” has been accepted at CCNC ‘23 (Las Vegas, NV, USA)! 🎉
[Sep 2022]	Our work entitled “Routing with Graph Convolutional Networks and Multi-Agent Deep Reinforcement Learning” has been accepted at NFV-SDN ‘22. Check it out!
[Jun 2022]	Exciting news! Our paper “Prediction of Mobile-App Network-Video-Traffic Aggregates using Multi-task Deep Learning” has been accepted at NI 2022 Workshop (IFIP Networking).
[May 2022]	Started an internship as a Visiting Researcher at KTH Royal Institute of Technology, Sweden, Stockholm, under the advisement of Dr. Marco Chiesa.
[Oct 2021]	We have a poster accepted at IMC ‘21. Check it out here!