activity
20202026
collaborators

5 papers

eess.SY2026

DER Allocation without Load Prediction via Reinforcement Learning

Abed AlRahman Al Makdah, Aravind Ramana, Shaofeng Zou +2

The growing variability of renewable generation increases the need for fast and flexible grid-balancing mechanisms. Existing frameworks for distributed energy resource aggregations…

math.OC2025

Linear Dynamics meets Linear MDPs: Closed-Form Optimal Policies via Reinforcement Learning

Abed AlRahman Al Makdah, Oliver Kosut, Lalitha Sankar +1

Many applications -- including power systems, robotics, and economics -- involve a dynamical system interacting with a stochastic and hard-to-model environment. We adopt a reinforc…

math.OC2025

Online Optimization with Unknown Time-varying Parameters

Shivanshu Tripathi, Abed AlRahman Al Makdah, Fabio Pasqualetti

In this paper, we study optimization problems where the cost function contains time-varying parameters that are unmeasurable and evolve according to linear, yet unknown, dynamics.…

cs.LG2021

Robust Adversarial Classification via Abstaining

Abed AlRahman Al Makdah, Vaibhav Katewa, Fabio Pasqualetti

In this work, we consider a binary classification problem and cast it into a binary hypothesis testing framework, where the observations can be perturbed by an adversary. To improv…

cs.LG2020

Lipschitz Bounds and Provably Robust Training by Laplacian Smoothing

Vishaal Krishnan, Abed AlRahman Al Makdah, Fabio Pasqualetti

In this work we propose a graph-based learning framework to train models with provable robustness to adversarial perturbations. In contrast to regularization-based approaches, we f…