龙思放，博士，2025年6月毕业于浙江大学生物系统工程与食品科学学院，机械专业。参加省部重点研发项目两项，发表论文十余篇。担任Biosystems Engineering, Computers and Electronics in Agriculture, Industrial Crops and Products, Results in Engineering, Smart Agricultural Technology等期刊审稿人。研究方向包括智能农林装备研发（块茎类中药材收获装备、林果振动采收装备）、离散元数值模拟（MBD-DEM, CFD-DEM, AI-DEM）、人工智能（目标检测跟踪、时序预测等）。每年计划招收1-2硕士研究生，欢迎具有机械工程、农业工程、人工智能、计算机科学等相关专业背景的学生申请，同时非常欢迎优秀本科生提前到本课题组参与科研项目。

代表性研究成果：

[1] Study on separation of the tuber-soil binary mixture based on vibration and airflow coupling. Biosystems Engineering (2024), 239, 13-24.

[2] Parameter calibration of the angle of repose of particle materials based on convolutional neural net-work. Biosystems Engineering, (2024), 245, 152-163.

[3] Parameter optimization of vibration and crushing combination digging device based on soil root tuber breakage model. Computers and Electronics in Agriculture, (2025) 230, 109861.

[4] Method of soil-elastoplastic DEM parameter calibration based on recurrent neural network. Powder Technology, (2023), 416,118222.

[5] Effect of modeling parameters on the mechanical response of macroscopic crushing of agglomerate. Powder Technology, (2022), 408, 117720.

[6] A stepped vibrating screening device with a crushing function based on the difference in tuber-soil aggregate breakage behavior. Powder Technology, (2024), 446, 120192.

[7] 机收麻山药离散元模型构建及其仿真参数标定[J].农业工程学报,2019,35(20):34-42.

[8] 麻山药种植田沙壤土流动性离散元模型颗粒放尺效应[J].农业工程学报,2020,36(21):56-64.

[1] Altair离散元仿真技术大会优秀论文奖

[2] 浙江大学优秀研究生、南都奖学金、优秀毕业生等荣誉