activity
20202026
most citedA Digital Twin Framework for Generation-IV Reactors with Reinforcement Learning-Enabled Health-Aware Supervisory Control

3 citations · 3 across the 2 of their papers we have counts for

collaborators

5 papers

eess.SY2026

Mission-critical spectrum sharing with decentralized Multi-Agent Reinforcement Learning

Dimitrios Pylorof, Imtiaz Nasim, Humberto E. Garcia +3

Motivated by emerging mission-critical applications and an increasingly congested spectrum, we develop a decentralized multi-agent reinforcement learning (MARL) model for dynamic s…

eess.SY2026

Adaptive control of pool-type research nuclear reactors: theory limits, pragmatic actuation constraints, and realized performance and adaptation

Dimitrios Pylorof, Linyu Lin

Adaptive control is attractive for nuclear reactors expected to operate predictably with extensive automation or bounded autonomy under dynamic electric and nonelectric demands, ev…

eess.SY2026

Closing the loop in learning with missing data

Dimitrios Pylorof, Humberto E. Garcia

What should a machine learning model learn when data is missing during training? We look at the learning process from a dynamical systems perspective, cast data missingness as a st…

eess.SY2025★ 3 cited

A Digital Twin Framework for Generation-IV Reactors with Reinforcement Learning-Enabled Health-Aware Supervisory Control

Jasmin Y. Lim, Dimitrios Pylorof, Humberto E. Garcia +1

Generation IV (Gen-IV) nuclear power plants are envisioned to replace the current reactor fleet, bringing improvements in performance, safety, reliability, and sustainability. Howe…

cs.NI2020

Rapid Top-Down Synthesis of Large-Scale IoT Networks

Pradipta Ghosh, Jonathan Bunton, Dimitrios Pylorof +6

Advances in optimization and constraint satisfaction techniques, together with the availability of elastic computing resources, have spurred interest in large-scale network verific…