AI services over a software-defined, multi-layer network
Ryan McCann
Ph.D. Student, joined 2024
Co-founder and lead developer of FUSION (github.com/SDNNetSim/FUSION), supported by MIT I-Corps and AT&T; reinforcement learning for software-defined elastic optical networks; failure-aware routing and realistic simulation of elastic optical and mesh networks.
3 journal papers, 9 conference papers with the center
FUSION: reinforcement learning over a software-defined optical mesh
Ken Patrick Watts
Ph.D. Student, joined 2022
Scalable, real-time detection of cyber attacks on smart power grids with machine learning; adaptive transfer learning for day-zero network intrusion detection; the NATIG cyber-physical co-simulation testbed (HELICS, GridLAB-D, ns-3).
NATIG co-simulation of a distribution grid and its wireless network
Mehran Sasaninia
Ph.D. Student, joined 2023
Federated learning to detect cyber attacks in the smart grid; smart false data injection attacks and anomaly detection in smart meters (IEEE SmartGridComm 2025); centralized versus federated learning for grid anomaly detection.
