R. Bhushan Gopaluni - Concepedia

Author

R. Bhushan Gopaluni

Also Known As

B. Gopaluni, Bhushan Gopaluni, Gopaluni, Bhushan, Gopaluni, R. Bhushan, R B Gopaluni, R. B. Gopaluni, R. Bhushan Gopaluni, R.B Gopaluni, R.B. GOPALUNI, R.B. Gopaluni

248

Publications

5.1K

Citations

H-Index

181

Concepts

All Affiliations

University of British Columbia University of Alberta Massachusetts Institute of Technology Honeywell (Canada)

About

R. Bhushan Gopaluni is an author at University of British Columbia specializing in engineering, systems engineering, and process control.

Top Concepts

#	Concept	H-Index	Publications	Citations
1	Engineering	30	70	3.1K
2	Business	11	11	358
3	Health Sciences	2	2	47
4	Education	1	1	11
5	Management	1	1	27

R. Bhushan Gopaluni

Publications

4.3K

Citations

H-Index

Page 1

	Year	Citations
Data-driven capacity estimation of commercial lithium-ion batteries from voltage relaxation Jiangong Zhu, Yixiu Wang, Yuan Huang, Nature Communications	2022	655
LIONSIMBA: A Matlab Framework Based on a Finite Volume Model Suitable for Li-Ion Battery Design, Simulation, and Control Marcello Torchio, Lalo Magni, R. Bhushan Gopaluni, Journal of The Electrochemical Society Consumer ElectronicsEngineeringSimulationPower ElectronicsAqueous Battery	2016	288
Model Predictive Control in Industry: Challenges and Opportunities Michael G. Forbes, Rohit S. Patwardhan, Hamza A. Hamadah, IFAC-PapersOnLine Automated Adaptive MpcControl StrategyEngineeringIndustrial EngineeringModel-based Control Technique	2015	282
Toward self‐driving processes: A deep reinforcement learning approach to control Steven Spielberg, Aditya Tulsyan, Nathan P. Lawrence, AIChE Journal	2019	143
Deep reinforcement learning approaches for process control Steven Spielberg, R. Bhushan Gopaluni, Philip D. Loewen Artificial IntelligenceDeep Neural NetworksEngineeringMachine LearningDeep Reinforcement Learning	2017	134
State-of-charge estimation in lithium-ion batteries: A particle filter approach Aditya Tulsyan, Yi-Ting Tsai, R. Bhushan Gopaluni, Journal of Power Sources State EstimationElectric BatteryElectrical EngineeringEngineeringMeasurement	2016	124
A particle filter approach to identification of nonlinear processes under missing observations R. Bhushan Gopaluni The Canadian Journal of Chemical Engineering Parameter EstimationNonlinear FilteringEngineeringState EstimationNonlinear System Identification	2008	123
Deep reinforcement learning with shallow controllers: An experimental application to PID tuning Nathan P. Lawrence, Michael G. Forbes, Philip D. Loewen, Control Engineering Practice Artificial IntelligenceExperimental ApplicationEngineeringDeep ReinforcementMachine Learning	2022	103
Identification of chemical processes with irregular output sampling Harigopal Raghavan, Arun K. Tangirala, R. Bhushan Gopaluni, Control Engineering Practice Irregular OutputEngineeringProcess MonitoringProcess ControlProcess Analysis	2005	99
Deep Learning of Complex Batch Process Data and Its Application on Quality Prediction Kai Wang, R. Bhushan Gopaluni, Junghui Chen, IEEE Transactions on Industrial Informatics Artificial IntelligenceEngineeringMachine LearningProcess TrajectoriesMachine Learning Tool	2018	94

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