204 citations · 414 across the 37 of their papers we have counts for
9 papers · 1 filter
Spatio-Temporal Scene-Graph Embedding for Autonomous Vehicle Collision Prediction
Arnav V. Malawade, Shih-Yuan Yu, Brandon Hsu +3
In autonomous vehicles (AVs), early warning systems rely on collision prediction to ensure occupant safety. However, state-of-the-art methods using deep convolutional networks eith…
Online Robust Control of Linear Dynamical Systems with Limited Prediction
Deepan Muthirayan, Dileep Kalathil, Pramod P. Khargonekar
We study the online robust control problem for linear dynamical systems with disturbances and uncertainties in the cost functions, with limited preview of the future disturbances a…
Online Learning for Predictive Control with Provable Regret Guarantees
Deepan Muthirayan, Jianjun Yuan, Dileep Kalathil +1
We study the problem of online learning in predictive control of an unknown linear dynamical system with time varying cost functions which are unknown apriori. Specifically, we stu…
Graph Learning for Cognitive Digital Twins in Manufacturing Systems
Trier Mortlock, Deepan Muthirayan, Shih-Yuan Yu +2
Future manufacturing requires complex systems that connect simulation platforms and virtualization with physical data from industrial processes. Digital twins incorporate a physica…
Online Learning Robust Control of Nonlinear Dynamical Systems
Deepan Muthirayan, Pramod P. Khargonekar
In this work we address the problem of the online robust control of nonlinear dynamical systems perturbed by disturbance. We study the problem of attenuation of the total cost over…
Online Algorithms for Network Robustness under Connectivity Constraints
Deepan Muthirayan, Pramod P. Khargonekar
In this paper, we present algorithms for designing networks that are robust to node failures with minimal or limited number of links. We present algorithms for both the static netw…
Generative Adversarial Imitation Learning for Empathy-based AI
Pratyush Muthukumar, Karishma Muthukumar, Deepan Muthirayan +1
Generative adversarial imitation learning (GAIL) is a model-free algorithm that has been shown to provide strong results in imitating complex behaviors in high-dimensional environm…
Dynamic Matching Markets in Power Grid: Concepts and Solution using Deep Reinforcement Learning
Majid Majidi, Deepan Muthirayan, Masood Parvania +1
Traditional bulk load flexibility options, such as load shifting and load curtailment, for managing uncertainty in power markets limit the diversity of options and ignore the prefe…
Adaptive Gradient Online Control
Deepan Muthirayan, Jianjun Yuan, Pramod P. Khargonekar
In this work we consider the online control of a known linear dynamic system with adversarial disturbance and adversarial controller cost. The goal in online control is to minimize…