郝凤琦
副研究员
郝凤琦,副研究员,博士生/硕士生导师。主要从事时空数据挖掘、智能农机装备、农业信息化、机器视觉与异常检测等方向研究,在嵌入式系统、计算机网络、智能控制等领域具有较为扎实的研发基础和丰富的工程实践经验。近年来承担国家重点研发计划、山东省科技重大专项等科技专项10余项,获山东省科技进步二等奖2项、中国机械工业科学技术奖二等奖1项、济南市科技进步二等奖1项、山东省高等学校科学技术奖三等奖1项,并获泰山农业机械科学技术奖一等奖、德州市科技合作奖一等奖。已授权发明专利10余项,发表学术论文20余篇。指导研究生在“挑战杯”等学科竞赛中获国赛三等奖、省赛一等奖等成绩。
研究方向:人工智能(时空数据挖掘、机器视觉与异常检测)、嵌入式系统、网络协议
联系方式:0531-82605225;haofq@sdas.org
指导专业:计算机科学与技术、电子信息(计算机技术)
1、主持或参与项目
[1] 智能农机装备关键技术研发及产业化示范,省科技重大专项,100万元,2015.03-2017.12,技术负责人
[2] 基于物联网的夏玉米大面积均衡增产关键技术研究,省重点研发计划,30万元,2016.06-2018.05,主持
[3] 花生智能化两段式收获关键技术与装备研发,国家重点研发计划子课题,69万元,2016.07-2020.12,技术负责人
[4] 农业机械化与信息化技术融合应用研究与验证,省农机装备研发创新计划,460万元,2018.01-2020.12,技术负责人
[5] 种子繁育机械装备智能控制系统研发,国家重点研发计划子课题,80万元,2017.07-2020.12,技术负责人
[6] 甜玉米精准耕种关键技术与装备研发,省重大科技创新工程,100万元,2019.1-2021.12,主持
[7] 土壤信息智能检测装置研制与健康状况监测平台研发,省重大科技创新工程,146万元,2024.09-2027.08,主持
[8] 温室作物生长要素及生命体征传感关键技术研发,山东省科技型中小企业创新能力提升计划,40万元,2023.07-2025.07,主持
2、奖励
[1] 先进制造装备数字化控制系统的研究与应用,山东省科技进步二等奖,2014.02
[2] 大容量装液体食品无菌转型纸盒灌装机的研发及产业化,中国机械工业科学技术二等奖,2015.10
[3] 黄河流域水资源调度及流域安全监测系统,济南市科技进步二等奖,2016.10
[4] 农机装备智能化控制技术的研究与应用,山东省高等学校科学技术奖三等奖,2020.12
[5] 大型拖拉机动力换挡与自动驾驶关键技术研发及应用,泰山农业机械科学技术奖一等奖,2022.09
[6] 甜玉米标准化生产及高值化产品研发关键技术研究与产业化示范,德州市科技合作奖一等奖,2022.07
[7] 水肥精准调控关键技术与智能装备研发及应用,山东省科技进步二等奖,2022.11
3、 论文、著作
[1]. Gao, L., Bai, J., Xu, J., Du, B., Zhao, J., Ma, D., Hao, F., "Detection of Miss-Seeding of Sweet Corn in a Plug Tray Using a Residual Attention Network," *Applied Sciences*, vol. 12, no. 24, pp. 12604, 2022. (中科院三区)
[2]. Bai, J., Hao, F., Cheng, G., Li, C., "Machine vision-based supplemental seeding device for plug seedling of sweet corn," *Computers and Electronics in Agriculture*, vol. 188, pp. 106345, 2021. (中科院一区)
[3]. Wu, X., Bai, J., Hao, F., Cheng, G., Tang, Y., Li, X., "Field complete coverage path planning based on improved genetic algorithm for transplanting robot," *Machines*, vol. 11, no. 6, pp. 659, 2023. (中科院三区)
[4]. Bian, C., Bai, J., Cheng, G., Hao, F., Zhao, X., "ConvTEBiLSTM: A Neural Network Fusing Local and Global Trajectory Features for Field-Road Mode Classification," *ISPRS International Journal of Geo-Information*, vol. 13, no. 3, pp. 90, 2024. (中科院三区)
[5]. Zhu, R., Hao, F., Ma, D., "Research on polygon pest-infected leaf region detection based on YOLOv8," *Agriculture*, vol. 13, no. 12, pp. 2253, 2023. (中科院二区)
[6]. Hao, F., Zhang, Z., Ma, D., Kong, H., "GSBF-YOLO: a lightweight model for tomato ripeness detection in natural environments," *Journal of Real-Time Image Processing*, vol. 22, no. 1, pp. 47, 2025. (中科院四区)
[7]. Hao, F., Wang, Y., Kong, H., Ma, D., Zhao, X., "Research on Optimization and Scheduling of MPTCP Data Networks in GNSS Network Reference Stations," *Proceedings of 2024 IEEE International Conference on Systems, Man, and Cybernetics (SMC)*, pp. 1838-1845, 2024. (CCF C)
[8]. Hao, F., Zhu, S., Ma, D., Dong, X., Kong, H., Liu, X., Mu, C., "Rapid Maize Seedling Detection Based on Receptive-Field and Cross-Dimensional Information Interaction," *Proceedings of 2024 IEEE International Conference on Systems, Man, and Cybernetics (SMC)*, pp. 2120-2125, 2024. (CCF C)
[9]. Hao, F., Zhao, X., Bian, C., Kong, H., Dong, X., & Bai, J. (2024). VEBiLSTM: A Neural Network for Field-road Classification using Enhanced Spatiotemporal Features. In *International Conference on Neural Information Processing* (pp). Cham: Springer International Publishing. (CCF C)
[10]. Hao, F., Zhang, Z., Ma, D., & Kong, H. (2025). GSBF-YOLO: a lightweight model for tomato ripeness detection in natural environments. Journal of Real-Time Image Processing, 22(1), 47. (CCF C)
[11]. Hao, F., Xia, J., Xu, H., Kong, H., Dong, X., & Bai, J. (2024). An Efficient Model for the Detection of Wood Surface Defects. In 2024 27th International Conference on Computer Supported Cooperative Work in Design (CSCWD) (pp. 1650-1655). IEEE. (CCF C)
[12]. Hao, F., Zhao, X., Bian, C., Bai, J., & Ding, Q. (2024, May). Neural Network Driven by Density and Parallel Features for Field-road Mode Mining.In 2024 27th International Conference on Computer Supported Cooperative Work in Design (CSCWD) (pp. 1650-1655). IEEE. (CCF C)
[13]. Hou, Y., Hao, F., Bai, J., Gao, C., Ding, Q., & Kong, H. (2025). VE-ResBiLSTM: A Deep Spatiotemporal Model for Field-Road Classification with DBSCAN-Based Data Augmentation. In *International Conference on Intelligent Computing*(pp. 199-212). Cham: Springer International Publishing. (CCF C)
[14]. Gao, C., Hao, F., Bai, J., Hou, Y., Ding, Q., & Kong, H. (2025). TS-CPC: A Self-Supervised Framework for Trajectory Similarity with Contrastive Predictive Coding and Enhanced Augmentation. In *International Conference on Intelligent Computing*(pp. 159-172). Cham: Springer International Publishing. (CCF C)
[15]. Guo, Y., Hao, F,. Ding, Q., Bai, J., Ma, D., & Hao, H. (2025). Unsupervised Wood Surface Anomaly Detection via Enhanced GAN with Residual Dense and Attention Modules. In *International Conference on Intelligent Computing*(pp). Cham: Springer International Publishing. (CCF C)
4、专利
[1] 发明专利(首位): 一种基于无线传感网的建筑热损数据追补方法,ZL201310289086.X
[2] 发明专利(首位):一种霍尔传感器批量快速检测与校准系统及其通讯方法与应用,ZL201811062740.2
[3] 发明专利(首位):一种基于北斗导航的小区播种机精准定位与控制方法,ZL201810520697.3
[4] 发明专利(首位):一种数字下推式磁悬浮装置及其控制方法,ZL201911252096.X
[5] 发明专利(首位):一种用于穴盘育苗的甜玉米种子识别方法及装置,ZL202110113679.5
[6] 发明专利(首位):一种基于惯性传感器的智能扭矩扳手角度精确测量方法,ZL202211520031.0
[7] 发明专利(首位):一种基于串行Flash芯片的嵌入式文件系统及数据管理方法,ZL 2022 1 1342537.7
[8] 发明专利(首位):基于多视角异常检测的木材表面缺陷检测方法及装置,ZL 2025 1 0474235.2
[9] 发明专利(首位):农机轨迹数据分类方法、装置、电子设备及存储介质,ZL 2025 1 0592963.3
[10] 发明专利(首位):基于动态对比学习与多尺度3D卷积的交通流量预测方法及装置,ZL 2025 1 0742205.5
5、欢迎具有扎实编程与英文基础,对多模态、大模型及人工智能交叉研究有浓厚兴趣、具备良好自驱力和科研耐力的小伙伴随时联系交流!


学部微信
地址:山东省济南市长清区大学路3501号(250300)
电话:0531-82605822
邮编:250300