Publications | Pages Perso Mayank-Shekhar Jha

Publications (Peer Reviewed International Journals and International conferences)

2025

To appear Théo Rutschke, Mayank Shekhar JHA*, Hugues Garnier, Neural Ordinary Differential Equations based System Identification for Reinforcement Learning with Provable Guarantees, IEEE CDC 2025, Brazil.
To appear Satya Vinay Chavan Marthi, Mayank Shekhar JHA*, Soha KANSO, Jean-Christophe Ponsart, Didier Theilliol, On-policy Safe Reinforcement Learning under Input Saturation and State Constraints for Nonlinear Discrete Time Systems, IEEE CDC 2025, Brazil .

Mayank S JHA and Prasanna Date, Adiabatic Quantum Linear Optimal Control for Discrete Time Dynamical Systems, IEEE International Conference on Quantum Computing and Engineering (QCE), 2025.

Soha Kanso, Mayank Shekhar Jha, Didier Theilliol, Safe Reinforcement Learning Tracking Control Based on Tunable Input-To-State Safe Control Barrier Function, American Control Conference, Denver, 2025.

S. Kanso, M. S. Jha, D. Theilliol, Reinforcement learning-based degradation-tolerant control design for affine nonlinear systems, Asian J. Control (2025), 1–17, DOI 10.1002/asjc.3780.

Hussonnois, Maxence, Thommen George Karimpanal, Mayank Shekhar Jha, and Santu Rana. "Human-Informed Skill Discovery: Controlled Diversity with Preference in Reinforcement Learning." Expert Systems with Applications (2025): 128604.

2024

Nordeide, M. S., Kampen, A. L., Kulkarni, C. S., Jha, M. S., & Singh, M. (2024, November). Assessment of ProgPy as an Open-Source Condition Monitoring and Diagnostics Tool. In The Unified International Conference on Emerging Technologies in Cyber-Physical Systems and Industrial AI (pp. 585-602). Cham: Springer Nature Switzerland.

Mayank Shekhar Jha, Bahare Kiumarsi,
Off-policy safe reinforcement learning for nonlinear discrete-time systems,
Neurocomputing, Elsevier, Volume 611, 2025, 128677, ISSN 0925-2312,
https://doi.org/10.1016/j.neucom.2024.128677.

Martin Hervé de Beaulieu, Mayank Shekhar Jha, Hugues Garnier, Farid Cerbah,
Remaining Useful Life prediction based on physics-informed data augmentation,
Reliability Engineering & System Safety,
Volume 252, 2024, 110451, ISSN 0951-8320.

Sungho Suh, Dhruv Aditya Mittal, Hymalai Bello, Bo Zhou, Mayank Shekhar Jha, Paul Lukowicz,
Remaining useful life prediction of Lithium-ion batteries using spatio-temporal multimodal attention networks, Heliyon, Volume 10, Issue 16, 2024,e36236, ISSN 2405-8440,
https://doi.org/10.1016/j.heliyon.2024.e36236.

Rotondo, D., & Jha, M. S. (2024, June). A weighted linearization approach to gradient descent optimization. In 2024 European Control Conference (ECC) (pp. 3606-3611). IEEE.

Jha, M. S., Kiumarsi, B., & Theilliol, D. (2024, July). Safe Reinforcement Learning Based on Off-Policy Approach for Nonlinear Discrete-Time Systems. In 2024 American Control Conference (ACC) (pp. 1574-1579). IEEE.

Julien Thuillier, Mayank Shekhar Jha, Sebastien Le Martelot, and Didier Theilliol, Prognostics Aware Control Design for Extended Remaining Useful Life: Application to Liquid Propellant Reusable Rocket Engine, International Journal of Prognostics and Health Management, ISSN2153-2648, 2024, https://doi.org/10.36001/IJPHM.2024.v15i1.3789.

2023

Kanso, S, Jha, MS, Theilliol, D. Off-policy model-based end-to-end safe reinforcement learning. Int J Robust Nonlinear Control. 2023; 1-26. doi: 10.1002/rnc.7109 (Author copy here)

S Kanso, M S JHA, D Theilliol, Degradation Tolerant Optimal Control Design for Stochastic Linear Systems, International Journal of Applied Mathematics and Computer Science (AMCS), 2024, Vol. 34, No. 1. (Author copy here)

Suh, Sungho, Dhruv Aditya Mittal, Hymalai Bello, Bo Zhou, Mayank Shekhar Jha, and Paul Lukowicz. "Remaining Useful Life Prediction of Lithium-ion Batteries using Spatio-temporal Multimodal Attention Networks." arXiv preprint arXiv:2310.18924 (2023).

Jha, M. S., Theilliol, D., & Weber, P. Model‐free optimal tracking over finite horizon using adaptive dynamic programming. Optimal Control Applications and Methods, 2023; 1-25. doi: 10.1002/oca.3028

Mayank Shekhar Jha*, Hugues Garnier, Didier Theilliol,Redundancy-Aware Physics Informed Neural Networks (R-PINNs) based Learning of Nonlinear Algebraic Systems with Non-Measurable States, Accepted in 62nd IEEE Conference on Decision and Control, Dec. 13-15, 2023, Singapore.

Two-stage Early Prediction Framework of Remaining Useful Life for Lithium-ion Batteries (paper)

2022

Kumar, Deepak, Sahil Kalra, and Mayank Shekhar Jha. "A concise review on degradation of gun barrels and its health monitoring techniques." Engineering Failure Analysis (2022): 106791.

Andrei, G. C., Jha, M. S., & Theillol, D. (2022, November). Complementary Reward Function Based Learning Enhancement for Deep Reinforcement Learning. In European Workshop on Advanced Control and Diagnosis (pp. 237-247). Cham: Springer Nature Switzerland.

Thuillier, Julien, Mayank Shekhar Jha, Marco Galeotta, and Didier Theilliol. "Control reconfiguration strategies for Remaining Useful Life extension." In 8th IFAC Symposium on System Structure and Control, SSSC 2022, vol. 55, no. 34, pp. 114-119. 2022. Link

Thuillier, Julien, Marco Galeotta, Mayank Shekhar Jha, and Didier Theilliol. "Impact of control gain design on Remaining Useful Life for a Liquid Propellant Reusable Engine." In 9th European Conference for Aeronautics and Space Sciences, EUCASS 2022. 2022. Link

Martin Herve De Beaulieu, Mayank Shekhar JHA, Hugues Garnier, Farid Cerbah, Unsupervised Remaining Useful Life Estimation Based on Deep Virtual Health Index Long-range Prediction, to appear in &th European conference of PHM Society, Turin, Italy 2022.

Martin Herve De Beaulieu, Mayank Shekhar JHA, Hugues Garnier, Farid Cerbah, “Unsupervised Remaining Useful Life Prediction through Long Range Health Index Estimation based on Encoders-Decoders” In 11th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes - SAFEPROCESS 2022 Pafos, Cyprus

Soha KANSO, Mayank Shekhar JHA, and Didier THEILLIOL, Degradation tolerant optimal control design for linear discrete-time systems, DPS 2022, Poland.

Soha Kanso, Mayank S. Jha, Marco Galeotta, Didier Theilliol , Remaining Useful Life Prediction with Uncertainty Quantification of Liquid Propulsion Rocket Engine Combustion Chamber , SAFEPROCESS 2022, Cyprus.

2021 and before
Suh, Sungho, Joel Jang, Seungjae Won, Mayank Shekhar Jha, and Yong Oh Lee. "Supervised Health Stage Prediction Using Convolutional Neural Networks for Bearing Wear." Sensors 20, no. 20 (2020): 5846.

Jha, Mayank-Shekhar, Genevieve Dauphin-Tanguy, and Belkacem Ould-Bouamama. "Robust fault detection with interval valued uncertainties in bond graph framework." Control Engineering Practice 71 (2018): 61-78.

Jha, Mayank Shekhar, Nizar Chatti, and Philippe Declerck. "Robust fault detection in bond graph framework using interval analysis and Fourier-Motzkin elimination technique." Mechanical Systems and Signal Processing 93 (2017): 494-514.

Jha, Mayank Shekhar, et al. "Particle Filter based hybrid prognostics of proton exchange membrane fuel cell in bond graph framework." Computers & Chemical Engineering 95 (2016): 216-230.

JHA, Mayank Shekhar, et al. "Particle Filter Based Prognostics of PEM Fuel Cell Under Constant Load." International Journal of Renewable Energy Research (IJRER) 6.2 (2016): 644-657.

Jha, Mayank Shekhar, Geneviève Dauphin-Tanguy, and B. Ould-Bouamama. “Particle filter based hybrid prognostics for health monitoring of uncertain systems in bond graph framework.” Mechanical Systems and Signal Processing 75 (2016) : 301-329.

Book Chapter: Jha, Mayank S., Geneviève Dauphin-Tanguy, and B. Ould-Bouamama. "Particle Filter Based Integrated Health Monitoring in Bond Graph Framework." Bond Graphs for Modelling, Control and Fault Diagnosis of Engineering Systems. Springer, Cham, 2017. 233-270.

M. Chelouati, M. S. Jha, M. Galeotta and D. Theilliol, "Remaining Useful Life Prediction for Liquid Propulsion Rocket Engine Combustion Chamber," 2021 5th International Conference on Control and Fault-Tolerant Systems (SysTol), 2021, pp. 225-230, doi: 10.1109/SysTol52990.2021.9595286

Jha, M. S., Weber, P., Theilliol, D., Ponsart, J. C., & Maquin, D. (2019, July). A Reinforcement Learning Approach to Health Aware Control Strategy. In 2019 27th Mediterranean Conference on Control and Automation (MED) (pp. 171-176). IEEE.

M. S. Jha, D. Theilliol, G. Biswas, and P. Weber, “Approximate Q-learning approach for Health Aware Control Design,” in 4th International Conference on Control and Fault-Tolerant Systems (SYSTOL), 18-20 September 2019, Casablanca, Morocco, 2019.

Liu, Bin, Phuc Do, Benoît Iung, Min Xie, Flavien Peysson, and Mayank Jha. "A study on the use of discrete event data for prognostics and health management: discovery of association rules." In PHM Society European Conference, vol. 4, no. 1. 2018.

Vu, Hai Canh, Phuc Do Van, Mayank Shekhar Jha, Didier Theilliol, and Flavien Peysson. "On the use of particle filters for prognostics in industrial applications." PHM Europe Conference 2018.

Jha, Mayank Shekhar, Geneviève Dauphin-Tanguy, and B. Ould Bouamama. "Robust FDI based on LFT BG and relative activity at junction." 2014 European Control Conference (ECC). IEEE, 2014.

Vaz, A., Jha, M. S., Seth, R., & Saxena, A. (2012, July). Design and Development of an Instrument for Measurement of Biting Force in Human Beings. In ASME 2012 11th Biennial Conference on Engineering Systems Design and Analysis (pp. 227-232). American Society of Mechanical Engineers.

Vaz, A., Jha, M. S., Mahajan, K., & Parashar, A. (2013, August). Experimental Study of Switching Behaviour in the Transmission of Tension to the Joints of the Finger. In ASME 2012 11th Biennial Conference on Engineering Systems Design and Analysis (pp. 321-327). American Society of Mechanical Engineers Digital Collection.

PhD Thesis: Diagnostics and Prognostics of Uncertain Dynamical Systems in a Bond Graph Framework