Chetan S. Kulkarni

20 papers B 1C 1Journal 17Unranked 1
YearRankTypeTitle / Venue / Authors
2026 J jnl
Hybrid Physics-Informed Neural Networks for Prognosis and Fleet Management of Li-Ion Batteries Under Large Load Variations.
IEEE Trans Autom. Sci. Eng.
Kajetan Fricke, Renato Giorgiani Nascimento, Matteo Corbetta, Chetan S. Kulkarni, Felipe A. C. Viana
2025 J jnl
Prescribing optimal health-aware operation for urban air mobility with deep reinforcement learning.
Reliab. Eng. Syst. Saf.
Mina Montazeri, Chetan S. Kulkarni, Olga Fink
2024 C conf
Data-Driven RUL Prediction Using Performance Metrics (Short Paper).
DX
Abel Díaz-González, Austin Coursey, Marcos Quiñones-Grueiro, Chetan S. Kulkarni, Gautam Biswas
2024 J jnl
Physics-guided recurrent neural network trained with approximate Bayesian computation: A case study on structural response prognostics.
Reliab. Eng. Syst. Saf.
Juan Fernández Salas, Juan Chiachío, José Barros, Manuel Chiachío, Chetan S. Kulkarni
2024 J jnl
Prescribing Optimal Health-Aware Operation for Urban Air Mobility with Deep Reinforcement Learning.
CoRR
Mina Montazeri, Chetan S. Kulkarni, Olga Fink
2024 J jnl
Training of physics-informed Bayesian neural networks with ABC-SS for prognostic of Li-ion batteries.
Comput. Ind.
Juan Fernández Salas, Matteo Corbetta, Chetan S. Kulkarni, Juan Chiachío, Manuel Chiachío
2023 J jnl
ProgPy: Python Packages for Prognostics and Health Management of Engineering Systems.
J. Open Source Softw.
Christopher Teubert, Katelyn J. Jarvis, Matteo Corbetta, Chetan S. Kulkarni, Matthew J. Daigle
2022 J jnl
A Prescriptive Dirichlet Power Allocation Policy with Deep Reinforcement Learning.
CoRR
Yuan Tian, Minghao Han, Chetan S. Kulkarni, Olga Fink
2022 J jnl
A prescriptive Dirichlet power allocation policy with deep reinforcement learning.
Reliab. Eng. Syst. Saf.
Yuan Tian, Minghao Han, Chetan S. Kulkarni, Olga Fink
2022 J jnl
Dynaformer: A Deep Learning Model for Ageing-aware Battery Discharge Prediction.
CoRR
Luca Biggio, Tommaso Bendinelli, Chetan S. Kulkarni, Olga Fink
2022 J jnl
Fusing physics-based and deep learning models for prognostics.
Reliab. Eng. Syst. Saf.
Manuel Arias Chao, Chetan S. Kulkarni, Kai Goebel, Olga Fink
2021 J jnl
Aircraft Engine Run-to-Failure Dataset under Real Flight Conditions for Prognostics and Diagnostics.
Data
Manuel Arias Chao, Chetan S. Kulkarni, Kai Goebel, Olga Fink
2021 J jnl
Exploring Architectures for Integrated Resilience Optimization.
J. Aerosp. Inf. Syst.
Daniel E. Hulse, Arpan Biswas, Christopher Hoyle, Irem Y. Tumer, Chetan S. Kulkarni, Kai Goebel
2020 J jnl
Fusing Physics-based and Deep Learning Models for Prognostics.
CoRR
Manuel Arias Chao, Chetan S. Kulkarni, Kai Goebel, Olga Fink
2020 J jnl
Real-Time Model Calibration with Deep Reinforcement Learning.
CoRR
Yuan Tian, Manuel Arias Chao, Chetan S. Kulkarni, Kai Goebel, Olga Fink
2019 J jnl
Battery health management for small-size rotary-wing electric unmanned aerial vehicles: An efficient approach for constrained computing platforms.
Reliab. Eng. Syst. Saf.
Gina Sierra, Marcos E. Orchard, Kai Goebel, Chetan S. Kulkarni
2019 J jnl
Hybrid deep fault detection and isolation: Combining deep neural networks and system performance models.
CoRR
Manuel Arias Chao, Chetan S. Kulkarni, Kai Goebel, Olga Fink
2018 B conf
Short-Term Transit Decision Support System Using Multi-task Deep Neural Networks.
SMARTCOMP
Fangzhou Sun, Abhishek Dubey, Chinmaya Samal, Hiba Baroud, Chetan S. Kulkarni
2015 J jnl
A testbed for implementing prognostic methodologies on cryogenic propellant loading systems.
IEEE Instrum. Meas. Mag.
Chetan S. Kulkarni, George Gorospe, Matthew J. Daigle, Kai Goebel
2012 — conf
Prognostics Health Management and Physics Based Failure Models for Electrolytic Capacitors.
Infotech@Aerospace
Chetan S. Kulkarni, Jose Celaya, Gautam Biswas, Kai Goebel