5 citations · 5 across the 5 of their papers we have counts for
5 papers
A Sociotechnical, Practitioner-Centered Approach to Technology Adoption in Cybersecurity Operations: An LLM Case
Francis Hahn, Mohd Mamoon, Alexandru G. Bardas +4
Technology for security operations centers (SOCs) has a storied history of slow adoption due to concerns about trust and reliability. These concerns are amplified with artificial i…
Distributed Energy Management and Demand Response in Smart Grids: A Multi-Agent Deep Reinforcement Learning Framework
Amin Shojaeighadikolaei, Arman Ghasemi, Kailani Jones +4
This paper presents a multi-agent Deep Reinforcement Learning (DRL) framework for autonomous control and integration of renewable energy resources into smart power grid systems. In…
Security Issues and Challenges in Service Meshes -- An Extended Study
Dalton A. Hahn, Drew Davidson, Alexandru G. Bardas
Service meshes have emerged as an attractive DevOps solution for collecting, managing, and coordinating microservice deployments. However, current service meshes leave fundamental…
A Multi-Agent Deep Reinforcement Learning Approach for a Distributed Energy Marketplace in Smart Grids
Arman Ghasemi, Amin Shojaeighadikolaei, Kailani Jones +3
This paper presents a Reinforcement Learning (RL) based energy market for a prosumer dominated microgrid. The proposed market model facilitates a real-time and demanddependent dyna…
Demand Responsive Dynamic Pricing Framework for Prosumer Dominated Microgrids using Multiagent Reinforcement Learning
Amin Shojaeighadikolaei, Arman Ghasemi, Kailani R. Jones +3
Demand Response (DR) has a widely recognized potential for improving grid stability and reliability while reducing customers energy bills. However, the conventional DR techniques c…