Mayank Shekhar Jha

Orcid: 0000-0002-6926-1386

According to our database1, Mayank Shekhar Jha authored at least 23 papers between 2014 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
CAPSULE: Control-Theoretic Action Perturbations for Safe Uncertainty-Aware Reinforcement Learning.
CoRR, April, 2026

A comprehensive review on quantum deep neural networks for prognostics and health management: Fundamentals, challenges and opportunities.
Eng. Appl. Artif. Intell., 2026

2025
Off-policy safe reinforcement learning for nonlinear discrete-time systems.
Neurocomputing, 2025

Human-informed skill discovery: Controlled diversity with preference in reinforcement learning.
Expert Syst. Appl., 2025

Deep Learning Based Prognostics of Nonlinear Systems Under Degradation in Closed-Loop.
Proceedings of the 6th International Conference on Control and Fault-Tolerant Systems, 2025

Neural Ordinary Differential Equations based System Identification for Reinforcement Learning with Provable Guarantees.
Proceedings of the 64th IEEE Conference on Decision and Control, 2025

On-policy Safe Reinforcement Learning under Input Saturation and State Constraints for Nonlinear Discrete Time Systems.
Proceedings of the 64th IEEE Conference on Decision and Control, 2025

Safe Reinforcement Learning Tracking Control based on Tunable Input-to-State Safe Control Barrier Function.
Proceedings of the 2025 American Control Conference, 2025

2024
Remaining Useful Life prediction based on physics-informed data augmentation.
Reliab. Eng. Syst. Saf., 2024

Degradation tolerant optimal control design for stochastic linear systems.
Int. J. Appl. Math. Comput. Sci., 2024

A Weighted Linearization Approach to Gradient Descent Optimization.
Proceedings of the European Control Conference, 2024

Safe Reinforcement Learning Based on Off-Policy Approach for Nonlinear Discrete-Time Systems.
Proceedings of the American Control Conference, 2024

2023
Remaining Useful Life Prediction of Lithium-ion Batteries using Spatio-temporal Multimodal Attention Networks.
CoRR, 2023

Assessing a Statistical and a Set-based Approach for Remaining Useful Life Prediction.
Proceedings of the 31st Mediterranean Conference on Control and Automatio, 2023

Two-Stage Early Prediction Framework of Remaining Useful Life for Lithium-ion Batteries.
Proceedings of the 49th Annual Conference of the IEEE Industrial Electronics Society, 2023

Redundancy-Aware Physics Informed Neural Networks (R-PINNs) Based Learning of Nonlinear Algebraic Systems with Non-Measurable States.
Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

2022
Degradation Tolerant Optimal Control Design for Linear Discrete-Times Systems.
Proceedings of the Intelligent and Safe Computer Systems in Control and Diagnostics, 2022

2021
Remaining Useful Life Prediction for Liquid Propulsion Rocket Engine Combustion Chamber.
Proceedings of the 5th International Conference on Control and Fault-Tolerant Systems, 2021

2020
Supervised Health Stage Prediction Using Convolutional Neural Networks for Bearing Wear.
Sensors, 2020

2019
Approximate Q-learning approach for Health Aware Control Design.
Proceedings of the 4th Conference on Control and Fault Tolerant Systems, 2019

A Reinforcement Learning Approach to Health Aware Control Strategy.
Proceedings of the 27th Mediterranean Conference on Control and Automation, 2019

2016
Particle filter based hybrid prognostics of proton exchange membrane fuel cell in bond graph framework.
Comput. Chem. Eng., 2016

2014
Robust FDI based on LFT BG and relative activity at junction.
Proceedings of the 13th European Control Conference, 2014


  Loading...