activity
20192024
most citedQuantum computing for energy systems optimization: Challenges and opportunities

292 citations · 660 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2024★ 63 cited

Generative AI and Process Systems Engineering: The Next Frontier

Benjamin Decardi-Nelson, Abdulelah S. Alshehri, Akshay Ajagekar +1

This article explores how emerging generative artificial intelligence (GenAI) models, such as large language models (LLMs), can enhance solution methodologies within process system…

quant-ph2021★ 47 cited

Quantum Machine Learning for Finance

Marco Pistoia, Syed Farhan Ahmad, Akshay Ajagekar +10

Quantum computers are expected to surpass the computational capabilities of classical computers during this decade, and achieve disruptive impact on numerous industry sectors, part…

quant-ph2020★ 66 cited

Quantum Computing Assisted Deep Learning for Fault Detection and Diagnosis in Industrial Process Systems

Akshay Ajagekar, Fengqi You

Quantum computing (QC) and deep learning techniques have attracted widespread attention in the recent years. This paper proposes QC-based deep learning methods for fault diagnosis…

quant-ph2020★ 292 cited

Quantum computing for energy systems optimization: Challenges and opportunities

Akshay Ajagekar, Fengqi You

The purpose of this paper is to explore the applications of quantum computing to energy systems optimization problems and discuss some of the challenges faced by quantum computers…

quant-ph2019★ 192 cited

Quantum Computing based Hybrid Solution Strategies for Large-scale Discrete-Continuous Optimization Problems

Akshay Ajagekar, Travis Humble, Fengqi You

Quantum computing (QC) has gained popularity due to its unique capabilities that are quite different from that of classical computers in terms of speed and methods of operations. T…