简历

教育经历

• 2023.09至今, 南开大学环境科学与工程学院 硕士
• 2019.09-2023.07, 四川大学建筑与环境学院 学士

研究领域及成果

• OBD数据远程监控
  • 灵感来源：表格数据图形转换，卫星数据机器学习填补
  • 创新点：建立一套全流程的数据处理框架，使用可用数据重建真实事件的NOx排放，调查OBD数据的机器学习可用性
  • 对应出版物：A Comprehensive OBD Data Analysis Framework: Identification and Factor Analysis of High-Emission Heavy-Duty Vehicles, Reconstructing Missing NOx Emissions in Heavy-Duty Diesel Vehicle OBD Data：A Machine learning approach
  • 对应期刊：Environmental Pollution, journal of Hazard Materials
  • 导师：毛洪钧
• 驾驶循环构建
  • 创新点：建立了一套跨地区的机动车能耗消耗框架
  • 对应出版物：A transferable vehicle energy consumption evaluation framework for quantifying vehicle electrification energy benefits
  • 对应期刊：NPJ Sustainable Mobility and Transport
  • 导师：毛洪钧

技能

• 英语 六级
• 编程 python计算机二级
  • pandas、numpy、matplotlib等数据处理库。
  • sklearn,pytorch等机器学习、深度学习库。
  • request、tkinter等其他python库。
• 机器学习算法：XGBOOST、Randomforest、Lightgbm，深度学习算法（较为擅长CNN）：ResNet，VGG，GoogleNet等

出版物

Reconstructing Missing NOx Emissions in Heavy-Duty Diesel Vehicle OBD Data：A Machine learning approach

Cao, Z. et al. Reconstructing missing NOx emissions in heavy-duty diesel vehicle OBD data: A machine learning approach. Journal of Hazardous Materials 494, 138619, doi:https://doi.org/10.1016/j.jhazmat.2025.138619 (2025).

A transferable vehicle energy consumption evaluation framework for quantifying vehicle electrification energy benefits

A Comprehensive OBD Data Analysis Framework: Identification and Factor Analysis of High-Emission Heavy-Duty Vehicles

Cao Z, Shi K, Qin H, et al. A Comprehensive OBD Data Analysis Framework: Identification and Factor Analysis of High-Emission Heavy-Duty Vehicles[J]. Environmental Pollution, 2025: 125751.

荣誉奖项

• 2024,“挑战杯”国赛铜奖
• 2024,“挑战杯”市赛金奖
• 2021,“互联网+”校级银奖