activity
20102026
most citedWasserstein Distributionally Robust Look-Ahead Economic Dispatch

101 citations · 303 across the 42 of their papers we have counts for

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Showing 2023Show all

6 papers · 1 filter

eess.SY2023★ 1 cited

Bayesian Persuasion for Containing SIS Epidemics with Asymptomatic Infection

Ashish R. Hota, Abhisek Satapathi, Urmee Maitra

We investigate the strategic behavior of a large population of agents who decide whether to adopt a costly partially effective protection or remain unprotected against the suscepti…

eess.SY2023

Adaptive Identification of SIS Models

Chi Ho Leung, William E. Retnaraj, Ashish R. Hota +1

Effective containment of spreading processes such as epidemics requires accurate knowledge of several key parameters that govern their dynamics. In this work, we first show that th…

eess.SY2023

Energy Consumption of Electric Vehicles: Effect of Lateral Dynamics

Simran Kumari, Susenjit Ghosh, Ashish R. Hota +1

Current research on energy related problems such as eco-routing, eco-driving and range prediction for electric vehicles (EVs) primarily considers the effect of longitudinal dynamic…

eess.SY2023★ 8 cited

Distributed Coordination of Multi-Microgrids in Active Distribution Networks for Provisioning Ancillary Services

Arghya Mallick, Abhishek Mishra, Ashish R. Hota +1

With the phenomenal growth in renewable energy generation, the conventional synchronous generator-based power plants are gradually getting replaced by renewable energy sources-base…

eess.SY2023★ 4 cited

Data-Driven Robust Optimization for Energy-Aware Safe Motion Planning of Electric Vehicles

Simran Kumari, Ashish R. Hota, Siddhartha Mukhopadhyay

In this paper, we simultaneously address the problems of energy optimal and safe motion planning of electric vehicles (EVs) in a data-driven robust optimization framework. Safe man…

eess.SY2023

Distributionally Robust Optimal and Safe Control of Stochastic Systems via Kernel Conditional Mean Embedding

Licio Romao, Ashish R. Hota, Alessandro Abate

We present a novel distributionally robust framework for dynamic programming that uses kernel methods to design feedback control policies. Specifically, we leverage kernel mean emb…