5 citations · 6 across the 7 of their papers we have counts for
7 papers
Toward Adaptive Grid Resilience: A Gradient-Free Meta-RL Framework for Critical Load Restoration
Zain ul Abdeen, Waris Gill, Ming Jin
Restoring critical loads after extreme events demands adaptive control to maintain distribution-grid resilience, yet uncertainty in renewable generation, limited dispatchable resou…
Cloud Revolution: Tracing the Origins and Rise of Cloud Computing
Deepa Gurung, S M Zia Ur Rashid, Zain ul Abdeen +1
The history behind the development of cloud computing is more than several decades of technological progress in the fields of virtualization, distributed systems, and high-speed ne…
A Scalable Approach for Safe and Robust Learning via Lipschitz-Constrained Networks
Zain ul Abdeen, Vassilis Kekatos, Ming Jin
Certified robustness is a critical property for deploying neural networks (NN) in safety-critical applications. A principle approach to achieving such guarantees is to constrain th…
Parameter Stress Analysis in Reinforcement Learning: Applying Synaptic Filtering to Policy Networks
Zain ul Abdeen, Ming Jin
This paper explores reinforcement learning (RL) policy robustness by systematically analyzing network parameters under internal and external stresses. \textcolor{black}{We apply sy…
Defense against Joint Poison and Evasion Attacks: A Case Study of DERMS
Zain ul Abdeen, Padmaksha Roy, Ahmad Al-Tawaha +6
There is an upward trend of deploying distributed energy resource management systems (DERMS) to control modern power grids. However, DERMS controller communication lines are vulner…
IP-FL: Incentivized and Personalized Federated Learning
Ahmad Faraz Khan, Xinran Wang, Qi Le +7
Existing incentive solutions for traditional Federated Learning (FL) focus on individual contributions to a single global objective, neglecting the nuances of clustered personaliza…
Learning Neural Networks under Input-Output Specifications
Zain ul Abdeen, He Yin, Vassilis Kekatos +1
In this paper, we examine an important problem of learning neural networks that certifiably meet certain specifications on input-output behaviors. Our strategy is to find an inner…