2018年在北京工业大学机械工程与应用电子技术学院智能化设计与制造专业获得博士学位，博士导师赵春江、范晋伟。2019年到2020年，在加拿大圭尔夫大学/工程学院高级机器人实验室做博士后研究，导师Simon.X.Yang。国家数字畜牧业创新中心，现代农业产业技术体系北京市数字农业创新团队专家成员，中国畜牧业协会信息分会理事，中国图形图像技术委员会3D视觉与中国人工智能学会具身智能专业委员会委员。中国农业机械化协会畜牧水产分会委员与中国人工智能学会智能农业专委会永久会员，中德青年农业实用人才，Intelligence & Robotics期刊编委，Agriculture Communication期刊学术编辑。重庆科技大学，华中农业大学，山东农业大学，河南科技大学，北京农学院，东华理工大学等硕士生导师。

动物智能表型高通量获取、行为分析和动物福利。

1 肉牛繁育性状在线评定技术研究与应用，国家重点研发计划中加合作（课题） 2019.8-2022.7

2 奶牛个体目标识别技术研究与应用，国家重点研发计划中英合作（课题） 2021.2-2023.1

3 生猪省力化智能养殖关键技术研发与示范，北京市农业农村局，2022.1-2022.12

4 北京市农林科学院专家工作站生猪数字化繁育专家工作站，院推广项目 2022.1-2024.12

5 川猪精细化智能养殖与环境精准控制，四川省重大科技专项 2021.7-2026.6

6 蛋鸡疾病智能诊断与移动巡检技术示范推广 ，北京市农业科技项目 2020.01-2021.12

7 种猪体重无应激测量设备与系统，科技创新2030子课题 2022.12-2025.11

8 种猪体型外貌在线智能评分设备与系统，科技创新2030子课题 2022.12-2025.11

9 牛羊体尺体重表型信息的高通量测量技术平台，国家重点研发计划子课题 2021.12-2026.11

发表论文：

2025年

1. Xu Z，Li Q，Ma W, et al.A geodesic distance regression-based semantic keypoints detection method for pig point clouds and body size measurement，Computers and Electronics in Agriculture, 2025.

2024年

1. Ma W, Wang X, Yang S X, et al. Autonomous inspection robot for dead laying hens in caged layer house[J]. Computers and Electronics in Agriculture, 2024, 227: 109595.

2. Ma W, Qi X, Sun Y, et al. Computer vision-based measurement techniques for livestock body dimension and weight: a review[J]. Agriculture, 2024, 14(2): 306.

3. Ma W, Sun Y, Qi X, et al. Computer-vision-based sensing technologies for livestock body dimension measurement: A survey[J]. Sensors, 2024, 24(5): 1504.

4. Ma W, Ji X, Ding L, et al. Automatic Monitoring Methods for Greenhouse and Hazardous Gases Emitted from Ruminant Production Systems: A Review[J]. Sensors, 2024, 24(13): 4423.

5. Chang K, Ma W, Xu X, et al. A Point Cloud Segmentation Method for Pigs from Complex Point Cloud Environments Based on the Improved PointNet++[J]. Agriculture, 2024, 14(5): 720.

6. Ma W, Wang X, Xue X, et al. A Dataset of Visible Light and Thermal Infrared Images for Health Monitoring of Caged Laying Hens in Large-Scale Farming[J]. Sensors, 2024, 24(19): 6385.

7. Ma W, Wang X, Yang S X, et al. Leveraging Thermal Infrared Imaging for Pig Ear Detection Research: The TIRPigEar Dataset and Performances of Deep Learning Models[J]. Animals, 2024, 15(1): 41.

8. Sun Y, Li Q, Ma W, et al. A Multi-View Real-Time Approach for Rapid Point Cloud Acquisition and Reconstruction in Goats[J]. Agriculture, 2024, 14(10): 1785.

9. Han H, Xue X, Li Q, et al. Pig-eardetection fromthethermalinfrared imagebased on improved YOLOv8n[J]. 2024.

2023年

1. Ma W, Fan J, Li Q, et al. A raw milk service platform using BP Neural Network and Fuzzy Inference[J]. Information Processing in Agriculture, 2018, 5(3): 308-319.

2. Li J, Ma W, Bai Q, et al. A posture-based measurement adjustment method for improving the accuracy of beef cattle body size measurement based on point cloud data[J]. Biosystems engineering, 2023, 230: 171-190.

3. Ma W, Wang K, Li J, et al. Infrared and visible image fusion technology and application: A review[J]. Sensors, 2023, 23(2): 599.

2022年

1. Li J, Ma W, Zhao C, et al. Extraction of key regions of beef cattle based on bidirectional tomographic slice features from point cloud data[J]. Computers and Electronics in Agriculture, 2022, 199: 107190.

2. Li J, Li Q, Ma W, et al. Key region extraction and body dimension measurement of beef cattle using 3D point clouds[J]. Agriculture, 2022, 12(7): 1012.

3. Jiawei L I, Weihong M A, Qifeng L I, et al. Automatic Acquisition and target extraction of beef cattle 3D point cloud from complex environment[J]. Smart Agriculture, 2022, 4(2): 64.

4. Li J, Ma W, Li Q, et al. Multi-view real-time acquisition and 3D reconstruction of point clouds for beef cattle[J]. Computers and Electronics in Agriculture, 2022, 197: 106987.

5. Li J, Li Q, Ma W, et al. Key Region Extraction and Body Dimension Measurement of Beef Cattle Using 3D Point Clouds. Agriculture 2022, 12, 1012

2021年

1.Ma W, Li Q, Li J, et al. A method for weighing broiler chickens using improved amplitude-limiting filtering algorithm and BP neural networks[J]. Information Processing in Agriculture, 2021, 8(2): 299-309.

授权发明专利：