高洪波

教育背景

(1) 2012.09-2016.11 北京航空航天大学计算机应用技术，智能驾驶方向，工学博士

(2) 2008.09-2011.07 安徽师范大学应用心理学，理学硕士

(3) 2002.09-2006.07 安徽师范大学教育技术，学士

工作经历

(1) 2022.02 -至今，中国科学技术大学，自动化系，研究员

(1) 2019.07 -2022.01，中国科学技术大学，自动化系，副研究员

(2) 2016.11-2019.06，清华大学车辆与运载学院，博士后（助理研究员）

(3) 2011.08-2012.08，兆盈科技，CTO

研究方向

(1) 智能驾驶车辆感知、规划、决策与控制研究

(2) 迁移学习、不确定性人工智能及其智能驾驶车辆应用

(3) 智能驾驶车辆智能测试与评价标准体系研究

招生

(1) 推免阶段欢迎招收985/211高校自动化、计算机、应用数学等相关专业优秀本科生

(2) 态度踏实、数学基础扎实，英语基础扎实，肯学想学要学的同学将优先考虑

(3) 常年欢迎本校本科生加入研究组，国创、大研、本科毕设等形式皆可

代表性论文

[1]      Deyi Li, H. Gao(*). A Hardware Platform Framework for an Intelligent Vehicle Based on a Driving Brain [J]. Engineering, 2018, 4(2018):464-470.

[2]      H. Gao, D. Li, K. Li, et al. Object Classification using CNN-Based Fusion of Vision and LIDAR in Autonomous Vehicle Environment. IEEE Trans. on Industrial Informatics, 2018, 14(9):4224-4231.

[3]      H. Gao, J. Zhu, T. Zhang, et al. Situational Assessment for Intelligent Vehicles based on Stochastic Model and Gaussian Distributions in Typical Traffic Scenarios. IEEE Trans. on Systems Man Cybernetics-Systems, 2020, DOI: 10.1109/TSMC.2020.3019512.

[4]      H. Gao, J. Zhu, H. Su, et al. Automatic Parking Control of Unmanned Vehicle Based on Switching Control Algorithm and Backstepping. IEEE/ASME Trans. on Mechatronics, 2020, DOI :10.1109/TMECH.2020.3037215.

[5]      H. Gao, J. Wang, K. Li, et al. Trajectory Prediction of Cyclist Based on Dynamic Bayesian Network and Long Short-Term Memory Model at Unsignalized Intersections. SCIENCE CHINA: Information Sciences, 2021, 64(7), 172207:1–172207:13.

[6]      H. Gao, C. Lv, T. Zhang, et al. A Structure Constraint Matrix Factorization Framework for Human Behavior Segmentation. IEEE Trans. on Cybernetics, 2021, DOI: 10.1109/TCYB.2021.3095357.

[7]      H. Gao, Z. Kan; K. Li. Robust Lateral Trajectory Following Control of Unmanned Vehicle Based on Model Predictive Control. IEEE/ASME Trans. on Mechatronics, 2021, DOI: 10.1109/TMECH.2021.3087605.

[8]      H. Gao,C. Hu, K. Li, et al. An Interacting Multiple Model for Trajectory Prediction of Intelligent Vehicles in Typical Road Traffic Scenario. IEEE Trans. on Neural Network and Learning Systems, 2021, DOI: 10.1109/TNNLS.2021.3136866

[9]      H. Gao, K. Li, Z. Kan, et al. Adaptive Finite Time Trajectory Tracking Control of Autonomous Vehicles with Disturbance and Actuator Saturation. IEEE Intelligent Transportation Systems Magazine,2021,DOI: 10.1109/MITS.2021.3080075

[10]    H. Gao, C. Hu, G. Xie, et al. Discretionary Cut-in Driving Behavior Risk Assessment based on Naturalistic Driving Data. IEEE Intelligent Transportation Systems Magazine,2021, DOI:10.1109/MITS.2021.3093349.