Bio
I am an engineering researcher and algorithm developer with experience in control engineering, battery energy storage systems, photovoltaic power forecasting, and simulation-based analysis for complex engineering systems. My current interests include optimization, machine learning, data-driven modeling, and computational methods for engineering or energy systems.
My industrial experience is in algorithm development for energy storage equipment used in renewable-energy systems. As an algorithm engineer in the energy storage sector, I worked on BMS/EMS-related algorithms, including SOC/SOX estimation, fault diagnosis, state-machine testing, and simulink-based validation. I also worked on PV power forecasting for solar PV plant operation, with tasks involving PV generation-data processing, operating-condition feature analysis, time-series prediction, model validation, forecast-error analysis, and power-output estimation for plant operation.
My previous academic research was mainly conducted in digital-twin-oriented well logging measurement systems. I worked on well logging algorithms, data-model synchronization between measured and simulated data, Monte Carlo-based numerical simulation, simulation acceleration through variance-reduction and parallel computing methods, and computational workflows on HPC platforms. I also participated in the team development of analysis and visualization interfaces for model validation and engineering interpretation.
Research Interests
Education
Selected courses: optimization theory, machine learning, pattern recognition, computational intelligence, and AI data processing.
Foundation in C, database systems, data mining, machine learning, microcontrollers, analog circuits, and digital circuits.
Work Experience
Worked on BMS/EMS-related algorithm development and validation for large-scale battery energy storage systems. The work covered SOC/SOX estimation logic, equalization-control, fault-diagnosis testing, state-machine checks, boundary-condition and abnormal-data analysis, simulink-based validation, photovoltaic power prediction, and data-analysis in energy systems.
Selected Engineering & Research Experience
- Worked on BMS/EMS-related algorithm development and validation for large-scale battery energy storage systems.
- Participated in SOC/SOX estimation logic, equalization-control, fault-diagnosis testing, state-machine checks, and abnormal-data analysis.
- Supported Simulink-based validation, interface consistency testing, and system-level algorithm verification for renewable energy storage applications.
- Worked on EMS UI design and data-analysis workflows for solar-storage system operation.
- Applied data mining and machine-learning methods to support EMS functions, system status analysis, operational performance evaluation, and PV output forecasting.
- Supported preliminary edge-AI deployment testing for photovoltaic communication applications.
- Built lithium-ion battery SOC estimation models using OCV/HPPC data, equivalent circuit modeling, and Simulink validation.
- Applied particle filtering and particle swarm optimization to improve SOC estimation for lithium-ion batteries.
- Related output: first-author publication on SOC estimation for lithium-ion batteries.
- Conducted graduate research on simulation-based response modeling and engineering data processing for complex petroleum engineering measurement systems.
- Worked with Geant4, Monte Carlo simulation, importance sampling, parallel computing, and Linux/Shell workflows for large-scale computational tasks.
- Applied optimization and machine learning methods to support engineering data interpretation and formation composition-estimation tasks.
- Related outputs include SCI publications, conference presentations, and a patent.
Publications
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2024Boron shielding design for neutron and gamma detectors of a pulsed neutron toolNuclear Science and Techniques, 2024
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2023High-efficiency Monte Carlo simulation based on CADIS method for Gamma Density MeasurementAnnals of Nuclear Energy, 2023
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2023GMAC: A Geant4-based Monte Carlo Automated computational platform for developing nuclear tool digital twinsApplied Radiation and Isotopes, 2023
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2022Hybrid Monte Carlo methods for Geant4-based nuclear well logging implementationAnnals of Nuclear Energy, 2022
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2022New development of sensitivity improvement for compensated neutron porosity tool in gas-filled boreholesApplied Radiation and Isotopes, 2022
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2022Dracarys: High-fidelity nuclear well logging benchmark problems with experimental resultsAnnals of Nuclear Energy, 2022
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2022Development and verification of Geant4-based parallel computing Monte Carlo simulations for nuclear logging applicationsAnnals of Nuclear Energy, 2022
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2020A novel gaussian particle swarms optimized particle filter algorithm for the state of charge estimation of lithium-ion batteriesInternational Journal of Electrochemical Science, 2020
Selected Awards & Presentations
- Outstanding Academic Performance Scholarship for two years, UESTC.
- Outstanding Graduate Student, UESTC.
- Academic Potential Scholarship, UESTC (Top 3%).
- Outstanding Student Cadre, School of Information Engineering, SWUST.
- Science and Technology Innovation Scholarship, SWUST (Rank 1 of 400).
- Merit Student, School of Information Engineering, SWUST.
- First Prize, Complex Oil & Gas Reservoir Exploration and Development and Logging Technology Seminar.
- Second Prize, Provincial Level, HuaQiao Cup National Mathematics Competition for College Students.
- Oral presentations at the 15th and 16th National Monte Carlo Conferences.