刘斌，陕西省“三秦英才特殊支持计划”区域发展人才（省部级人才）、陕西省中青年科技创新领军人才（省部级人才）、秦创原“科学家+工程师”队伍建设首席科学家、beat365官方网站教授、博士生导师、中国计算机学会（CCF）西安秘书长（24-26年）、中国计算机学会青年计算机科技论坛（CCF YOCSEF）西安副主席（23-25年）、陕西省计算机学会高性能专委会副主任、陕西省计算机学会计算机视觉专委会副主任，CCF杰出会员、农业工程学会高级会员、CCF传播工委首届CCF“杰出传播者”、CCF数字农业分会委员、CCF高性能计算专业委员会委员、CCF分布式计算与系统专业委员会委员、陕西省计算机学会理事，陕西省图像图形学学会理事，农业农村部物联网重点实验室，陕西省农业信息智能感知与分析工程技术，陕西省农业信息处理与智能分析创新团队等实验室及团队核心成员。长期致力于农作物病害智能诊断研究，主持国家自然科学基金面上项目、CCF-百度松果基金等项目26项，相关成果在COMPUT ELECTRON AGR、TCBB和农业工程学报等刊物上发表论文70余篇，其中ESI高被引论文3篇，获陕西省计算机学会科技进步奖一等奖1项，获陕西省教学成果奖一等奖等奖项3项，制定农业物联网地方标准3项，申报发明专利7项，软著21项，指导学生获8项国家级学科竞赛奖项。此外，担任The Journal of Supercomputing、IEEE Trans. on Computers、Computers and Electronics in Agriculture、农业工程学报等权威期刊和ISPA、HPCC等国际会议的审稿人。

2026.4.13.研究生张钟皓同学的研究论文LIBPipe: Efficient Load Imbalance Pipeline Model Parallelism for Large Models Training[J]被CCF A类期刊计算机体系结构顶级刊物IEEE Transactions on Parallel and Distributed Systems录用。

2026.4.13.研究生李长乐、楚琦同学的研究论文FedCED: Consensus Enhancement in Decentralized Federated Learning via Distillation[J]被中科院一区TOP期刊人工智能刊物Knowledge-Based Systems录用。

2026.2.21. 课题组与博士生孙威同学合作的研究论文Rethinking Cross-Modal Anchor Alignment for Mitigating Error Accumulation[C]被CCF A类会议计算机视觉顶级会议CVPR录用。

2025.4.26.研究生马永耀、胡子健同学的研究论文GroPipe: A Grouped Pipeline Hybrid Parallel Method for Accelerating DCNNs Training[J]被CCF A类期刊计算机体系结构顶级刊物IEEE Transactions on Computers录用。

2025.8 深度学习科创组计算机系贾文旭，数据科学系郭紫阳等同学组成的参赛队伍参加了2025年中国机器人及人工智能大赛人工智能创新赛，获得2025年（第27届）中国机器人及人工智能大赛国家二等奖。

2025.7.4.研究生张钟皓、翟邦浩同学的研究论文PRT：An Efficient Pipeline Reuse Technology for Large Models Training [C]被CCF B类国际会议计算机体系结构与并行分布式计算领域IEEE International Conference on Cluster Computing录用。

2024.7.25，由中国大学生计算机设计大赛组织委员会指导举办的第十七届中国大学生计算机设计大赛软件应用与开发赛道全国总决赛在山东威海落幕。由我校beat365官方网站刘斌教授指导，beat365官方网站本科生谭博文、王业强、郝景新、石鑫、俞涛组成的团队斩获国家级二等奖。

2023.11 深度学习科创组数据科学系20级潘俊豪、21级谭博文、22级李婷婷、计科系21级赵绅凯组成的参赛队伍参加了2023年全国大学生数字媒体科技作品及创意竞赛，获得2023年（第11届）全国大学生数字媒体科技作品及创意竞赛国家一等奖，优秀指导教师。

2023.3.10.研究生任华坤、李佳欣、段楠楠同学的研究论文《RE-RCNN: A Novel Representation-Enhanced RCNN Model for Early Apple Leaf Disease Detection》被SCI期刊ACM Transactions on Sensor Networks(CCF B类期刊)录用。

2022.12.09. 研究生田靓靓、段楠楠同学的研究论文《VMF-SSD: A Novel V-Space based Multi-scale Feature Fusion SSD for Apple Leaf Disease Detection》被SCI期刊 IEEE/ACM Transactions on Computational Biology and Bioinformatics（CCF B类期刊）录用。

2022.08 深度学习科创组计科系19级朱先语，信管系19级贾润昌和软工系19级李锦江组成的参赛队伍参加了2022年中国大学生计算机设计大赛，获得西北赛区一等奖，2022 年(第 15 届)中国大学生计算机设计大赛国家三等奖。

2022.07.08. 本科生深度学习科创组，计算机科学与技术系2019级朱先语同学的研究论文《LAD-Net : A Novel Light Weight Model for Early Apple Leaf Pests and Diseases Classification》被SCI期刊 IEEE/ACM Transactions on Computational Biology and Bioinformatics（CCF B类期刊）录用。

2022.04.15. 本科生深度学习科创组，信管系2019级贾润昌同学的研究论文《面向移动端的苹果叶部病虫害轻量级识别模型》被EI期刊农业工程学报（同学科排名第一）录用。

2021.08.06. 本科生深度学习科创组，信管系2018级孙赫男同学和信管系2018级徐皓玮同学的研究论文《MEAN-SSD: A Novel Real-Time Detector for Apple Leaf Diseases Using Improved Light-weight Convolutional Neural Networks》被SCI期刊 Computers and Electronics in Agriculture（中科院1区）录用。

2021.04.15. 本科生深度学习科创组，信管系2019级袁信彬同学和软工系2019级于聪同学的研究论文《CGAN-IRB: A Novel Data Augmentation Method for Apple Leaf Diseases》被CCF会议International Computer Software and Applications Conference（CCF C类推荐会议）录用。

2020.08 深度学习科创组信管系18级徐皓玮，孙赫男组成的参赛队伍参加了2020年中国大学生计算机设计大赛，获得西北赛区一等奖，2020 年(第 13 届)中国大学生计算机设计大赛国家三等奖。

2020.06.30. 本科生深度学习科创组，电商系2017级丁泽锋同学的研究论文《Grape Leaf Disease Identification Using Improved Deep Convolutional Neural Networks》被SCI期刊Frontiers in Plant Science（中科院二区）录用。

2020.06.23 2020届本科毕业生信管161邱霁岩、电商162陈跃翰、电商162江鹏三位同学分别获得我校本科生百篇优秀毕业论文、校级优秀毕业论文和院级优秀毕业论文。

2020.05.12. 本科生深度学习科创组，信管系2017级谢霄玥和计科系2017级马源同学的研究论文《A Deep-Learning-Based Real-Time Detector for Grape Leaf Diseases Using Improved Convolutional Neural Networks》被SCI期刊Frontiers in Plant Science（中科院二区）录用。

2019.11.22 深度学习科创组江鹏、谢霄玥、马源、田靓靓、丁泽锋、杨丹妮组成的两支参赛队伍参加了2019年中国高校计算机大赛-人工智能创意赛总决赛，两支队伍均获得全国二等奖，奖金贰万元整。校新闻报道、院新闻报道、院新媒体报道。

2019.4.18 深度学习科创组江鹏、陈跃翰、丁泽锋、谭铖、获得2019年未来杯高校AI挑战赛西北赛区第二名，进入全国总决赛、田靓靓、张韵、邱霁岩、谢霄玥获得西北赛区优秀奖，校新闻报道。

2018.06.28 2018届本科毕业生电商141齐潇、信管143沈明珠、计算机141刘朝洋、信管141樊李行四位同学获得我校第一届本科生百篇优秀毕业论文。

1.人工智能与计算机视觉（博士生方向）

多模态学习、多模态融合、小样本学习、半监督学习，以及人工智能和计算机视觉领域前沿算法基础研究。

2.深度学习与农作物病虫害诊断（硕士研究生方向）      

针对农作物（苹果、猕猴桃和葡萄等）的病虫害信息进行识别与监测预警。研究通过图像处理技术总结农作物病虫害识别特征与规律，将深度卷积神经网络模型应用到农作物病虫害识别领域中，建立出适合农作物疾病诊断的预测模型；研究基于深度学习的目标检测算法SSD、Faster RCNN和YOLO等算法，提出兼顾准确率和即时检测需求的神经网络模型对病虫害进行实时监测与预警；研究基于深度学习的图像分割算法。

3.深度学习并行算法（硕士研究生方向）        

并行算法就是用多台处理机联合求解问题的方法和步骤，其执行过程是将给定的问题首先分解成若干个尽量相互独立的子问题，然后使用多台计算机同时求解它，从而最终求得原问题的解。本课题组针对深度学习算法中并行度不高的问题，开展面向多核/众核平台算法并行化研究。研究常见的并行编程模型（Python、CUDA和MPI），显式构造并行深度学习算法，提高并深度并行算法加速比性能，提高算法的加速比性能。

欢迎具有责任心、强烈的求知欲，学习积极主动和具有较强的自律性的优秀学生报考！只要你肯学，一切都不是问题，如果仅仅想混文凭，请绕道而行，培养方式采用例会制与随时讨论。如有意向报考我为导师的同学，请与我联系，电话微信：18710487673。

博士生（博士后）招生专业方向：0828Z2 农业工程

硕士生招生专业方向：0812 计算机科学与技术(学硕）0854 电子信息（专硕）095136 农业工程与信息技术（专硕）
beat365官方网站2025年博士研究生招生章程及专业目录

beat365官方网站2025年博士研究生招生申请-审核实施细则

2025年专业学位硕士研究生考试招生章程

2025年全日制学术学位硕士研究生考试招生章程

欢迎满足下列条件的同学报考：

（1）具有较好的英语水平；

（2）具有较强的编程能力；

（3）对算法研究及软件设计有浓厚兴趣。

常年招收英语和编程能力较强的本科同学参加科创项目实践。有意者欢迎与我联系。对在科创工作一年以上，各方面表现优异、取得一定科研成绩的本科同学，若取得我校推免资格，优先录取。若想保送外校（西安交大、西电、西工大、西理工，前提是优秀者）读研，将帮助推荐与联系。

[1]国家级创新训练项目,基于物联网的苹果病虫害预测预报模型研究,2020,结题优秀，软工系18级李承泽主持

[2]省级创新训练项目,基于云端协同和卷积神经网络的苹果叶部病害识别与检测,2020,结题优秀，信管18级孙赫男主持。

[3] 国家级创新训练项目,基于卷积神经网络的葡萄叶部病害识别与检测研究,2019,结题优秀，计科系17级谭铖主持。

[4] 省级创新训练项目,基于卷积神经网络的苹果叶部病理图像识别研究,2017,结题优秀，电商15级张昀主持。

研究生课程：深度学习        

本科生课程：云计算（Cloud Computing）、 C语言程序设计、并行程序设计

1.承担科研项目国家级省级等科研项目：

[21]国家自然科学基金面上项目，62376226，多源图像信息融合的苹果叶片病害早期检测方法研究， 2024/01-2027/12，主持人。

[20] 陕西省重点研发计划重点产业链，2024NC-ZDCYL-05-05，主要粮食作物病虫害早期监测与预警平台研究与集成示范,2024/01至2025/12，子课题主持人。

[19] 杨凌示范区科技计划项目，2024NY-14，小麦叶片早期病虫害智能预测预报与防治处方推荐研究，2024/12-2026/11，主持人。

[18]秦创原“科学家+工程师”队伍建设，2024QCY-KXJ-094，猕猴桃病害智能监测预警研发“科学家+工程师”队伍， 2024/01-2026/12， 首席科学家。

[17]陕西省重点研发计划，2024NC-YBXM-191，基于高光谱的苹果叶片病害早期快速智能诊断研究与巡检装备研发， 2024/01-2025/12，主持人。

[16]西安市农业重点产业链关键技术攻关项目，2024JH-NYZD-0027，小麦病害智能监测和预警技术开发与示范， 2024/01-2025/12，主持人。

[15]咸阳市重点研发计划，L2020-ZDYF-NY-019，基于人工智能和知识图谱的苹果叶部病虫害诊断及防治方法推荐研究,2023/01至2024/12，主持人。

[14]陕西省重点研发计划重点产业链，2023-ZDLNY-63，农作物病虫害人工智能诊断预警研究与示范， 2023/01-2024/12，子课题主持人。

[13]横向项目，2023110801，猕猴桃叶片病害智能诊断与巡检装备研发， 2023/11-2023/12，主持人。

[12]横向项目，信号处理算法与仿真实现， 2022/09-2025/03，主持人。

[11]国家自然科学基金青年项目，61602388，基于线程级推测的非规则算法并行化研究， 2017/01-2019/12，主持人。

[10]国家重点研发项目，2020YFD1100601-02-13， 基于知识图谱的农业先进适用技术推荐研究与应用，2020/01至2022/10，子任务主持人。

[9]2021年度CCF-百度松果基金，基于PaddlePaddle端云协同的苹果叶部早期病虫害监测与预警，2021/07至2022/07，主持人。

[8]陕西省重点研发计划项目，2021NY-138，基于人工智能的苹果叶部病虫害早期监测预警研究与巡检装备研发 ，2021/01至2022/12，主持人。

[7] 陕西省重点研发计划重点产业链,2019ZDLNY07-06-01,基于大数据与AI 技术的苹果病害智能诊断与监测预警研究, 2019/01-2021/12,子课题主持人。

[6]宁夏智慧农业产业技术协同创新中心,2017DC53-01,基于卷积神经网络的葡萄病害实时检测研究与应用, 2017/10-2020/10,子课题主持人。

[5]陕西省自然科学基金面上项目,2017JM6059,面向循环结构的基于机器学习推测多线程划分方法研究,2017/01-2018/12,主持人。

[4] 中国博士后科学基金, 2017M613216,云计算环境下农业图像分割算法并行化研究,2017/09-2019/08,主持人。

[3] 陕西省博士后基金,2016BSHEDZZ121,基于Spark异构集群的农业图像分割算法并行化研究,2016/01-2018/01,主持人。

[2]横向项目，2022031001，农业物联网大数据分析与可视化系统研发,2022031001,2022/03至2023/02，主持人。

[1]横向项目，2020SZNY-06，肉牛养殖场户和管理平台大数据看板子系统开发，2020/12月-2021/11,子课题主持人。

2.主要论文（5项代表作）：

[1]Bin Liu, Zhonghao Zhang, Hengzhao Li, Zeyu Ji*, Hongming Zhang, Keqin Li. LIBPipe: Efficient Load Imbalance Pipeline Model Parallelism for Large Models Training [J]. IEEE Transactions on Parallel and Distributed Systems, 2026:4-13 已录用.(CCF A类, 计算机体系结构顶级期刊)

[2]Bin Liu, Wei Sun, Qianqian Wang, Wei Feng, Yijie Chen, Haixi Zhang*. Rethinking Cross-Modal Anchor Alignment for Mitigating Error Accumulation[C]. IEEE Conference on Computer Vision and Pattern Recognition, 2026:1-8 已录用.(CCF A类,计算机视觉顶级会议)

[3]Bin Liu, Yongyao Ma, Zijian Hu, Zeyu Ji*, Zhenli He*, and Keqin Li. GroPipe: A Grouped Pipeline Hybrid Parallel Method for Accelerating DCNNs Training[J]. IEEE Transactions on Computers, 2025:1-14 已录用.(CCF A类,计算机体系结构顶级期刊)

[4]Wei Feng; Danting Liu; Qianqian Wang; Mengping Jiang; Bin Liu*. Federated Incomplete Multi-View Clustering with Tensorized Low-Rank Constraint[C]. The 40th Annual AAAI Conference on Artificial Intelligence,2025:1-15. (CCF A类,人工智能顶级会议)

[5]Henan Sun#, Haowei Xu#, Bin Liu*, Dongjian He, Jinrong He, Haixi Zhang and Nan Geng. MEAN-SSD: A Novel Real-Time Detector for Apple Leaf Diseases Using Improved Light-weight Convolutional Neural Networks[J]. Computers and Electronics in Agriculture, 2021.08 (SCI; IF:6.757; 中科院1区)

3.获奖情况（代表作）：

[1]陕西省高等教育教学成果奖一等奖,优化体系，革新模式，厚植资源，农林人才计算机应用创新能力培养探索与实践,2019,6/7。

[2]陕西省学位与研究生教育学会教学成果奖一等奖,需求导向，分类培养，学科协同，提升农林高校研究生计算机创新和应用能力,2023,3/5。

[3]beat365官方网站研究生教育校级教学成果奖一等奖,学科牵引， 交叉赋能， 协同育人， 培养农林高校非信息类研究生创新实践能力,2023,3/7。

[4]2022、2023年CCF传播工委优秀传播大使，首届CCF“杰出传播者”。

[5]2018、2020、2022届本科生百篇优秀毕业论文（设计）优秀指导老师获得者。

[6]2018、2019、2023年大学生创新创业优秀指导老师。

[7]2019年校级先进个人。

[8]第11届全国大学生数字媒体科技作品及创意竞赛国家一等奖优秀指导教师。

4.学科竞赛（5项代表作）：

[1]第11届全国大学生数字媒体科技作品及创意竞赛,2023,全国一等奖。

[2]第二届中国高校计算机大赛-人工智能创意赛,2019,两支队伍均获得全国二等奖2项，奖金贰万元整。

[3]第十三届中国大学生计算机设计大赛,2020,全国三等奖。

[4] 第十三届中国大学生计算机设计大赛,2021,全国三等奖。

[5]ACM中国-国际并行计算挑战赛,2021, 超级云计算教育基金奖。

5.教改项目（代表作）：

[1]陕西省专业学位研究生教学案例，基于人工智能的农作物病害智能诊断教学案例研究，2025年,主持。

[2]教育部高教司国家级虚拟教研室,智能+新农科课程虚拟教研室.2022年,4/16。

[3]陕西本科和高等继续教育教学改革研究重点攻关项目,基于能力导向的新农科人工智能课程群及新形态教学资源构建模式研究与实践.2024/01-2025/12,beat365官方网站，4/5。

[4]陕西本科和高等继续教育教学改革研究重点攻关项目,四新专业建设背景下AI+课程群教学研究中心构建与实践.2022/01-2023/12,beat365官方网站，3/5。

[5]beat365官方网站一流本科课程名单.《云计算》.2022年,主持。

6.本科生人才培养（5项代表作）：

[1]邱霁岩，信管161，基于GPU的快速水墨画生成算法，校级百篇。

[2]沈明珠，信管143，Stack Overflow论坛问题解答满意度的预测研究，校级百篇。

[3]刘朝洋，计算机141，基于CUDA的并行快速铅笔画生成算法研究，校级百篇。

[4]樊李行，信管141，基于顶点划分的并行图再分割算法研究，校级百篇。

[5]齐潇，电商141，基于OpenMP的并行Boyer-Moore-Horspool匹配算法研究，校级百篇。

Professor Bin Liu is a Professor and Ph.D. Supervisor at Northwest A&F University. He has been selected as a Regional Development Talent under the Shaanxi “Sanqin Talent Special Support Program” at the provincial level, a Young and Middle‑aged Leading Talent in Scientific and Technological Innovation of Shaanxi Province at the provincial level, and the Chief Scientist of a “Scientist + Engineer” team under the Qinchuangyuan Innovation‑driven Platform.

Professor Liu currently serves as Secretary‑General of CCF Xi'an（24-26 year）, Vice Chair of CCF YOCSEF Xi'an（23-25 year）, Vice Director of the High Performance Computing Committee of the Shaanxi Computer Society, and Vice Director of the Computer Vision Committee of the Shaanxi Computer Society. He is also a Distinguished Member of the China Computer Federation, a Senior Member of the Chinese Society of Agricultural Engineering, a member of the CCF Digital Agriculture Committee, a member of the CCF High Performance Computing Committee, a member of the CCF Distributed Computing and Systems Committee, a council member of the Shaanxi Computer Society, and a council member of the Shaanxi Society of Image and Graphics.

Professor Liu is a core member of several laboratories and research teams, including the Key Laboratory of Agricultural Internet of Things of the Ministry of Agriculture and Rural Affairs, the Shaanxi Engineering Technology Research Center for Intelligent Perception and Analysis of Agricultural Information, and the Shaanxi Innovation Team for Agricultural Information Processing and Intelligent Analysis.

Professor Liu has long been engaged in research on intelligent diagnosis of crop diseases. He has led 26 research projects, including projects funded by the National Natural Science Foundation of China and the CCF‑Baidu Songguo Fund. His research achievements have been published in journals such as Computers and Electronics in Agriculture, IEEE/ACM Transactions on Computational Biology and Bioinformatics, and Transactions of the Chinese Society of Agricultural Engineering. He has published more than 70 papers, including three ESI highly cited papers. He has received three awards, including the First Prize of the Shaanxi Provincial Teaching Achievement Award, participated in the formulation of three local standards for agricultural Internet of Things, applied for seven invention patents, obtained 21 software copyrights, and guided students to win eight national discipline competition awards.

In addition, Professor Liu serves as a reviewer for authoritative journals and international conferences, including The Journal of Supercomputing, IEEE Transactions on Computers, Computers and Electronics in Agriculture, Transactions of the Chinese Society of Agricultural Engineering, ISPA, and HPCC.

2026.4.13 The research paper “LIBPipe: Efficient Load Imbalance Pipeline Model Parallelism for Large Models Training” [J], authored by graduate student Zhonghao Zhang, was accepted by IEEE Transactions on Parallel and Distributed Systems, a CCF‑A journal and a top journal in computer architecture.

2026.4.13 The research paper “FedCED: Consensus Enhancement in Decentralized Federated Learning via Distillation” [J], authored by graduate students Changle Li and Qi Chu, was accepted by Knowledge‑Based Systems, a CAS Q1 TOP journal in artificial intelligence.

2026.2.21 The research paper “Rethinking Cross‑Modal Anchor Alignment for Mitigating Error Accumulation” [C], completed by the research group in collaboration with doctoral student Wei Sun, was accepted by CVPR, a CCF‑A conference and a top conference in computer vision.

2025.4.26 The research paper “GroPipe: A Grouped Pipeline Hybrid Parallel Method for Accelerating DCNNs Training” [J], authored by graduate students Yongyao Ma and Zijian Hu, was accepted by IEEE Transactions on Computers, a CCF‑A journal and a top journal in computer architecture.

2025.8 A student team from the Deep Learning Innovation Group, including Wenxu Jia from the Department of Computer Science and Ziyang Guo from the Department of Data Science, participated in the Artificial Intelligence Innovation Competition of the 2025 China Robotics and Artificial Intelligence Competition and won the National Second Prize in the 27th China Robotics and Artificial Intelligence Competition.

2025.7.4 The research paper “PRT: An Efficient Pipeline Reuse Technology for Large Models Training” [C], authored by graduate students Zhonghao Zhang and Banghao Zhai, was accepted by IEEE International Conference on Cluster Computing, a CCF‑B international conference in computer architecture and parallel/distributed computing.

2024.7.25 The national final of the Software Application and Development Track of the 17th China Collegiate Computer Design Competition, organized under the guidance of the Organizing Committee of the China Collegiate Computer Design Competition, concluded in Weihai, Shandong Province. Under the guidance of Professor Liu from the College of Information Engineering, the undergraduate team composed of Bowen Tan, Yeqiang Wang, Jingxin Hao, Xin Shi, and Tao Yu from the College of Information Engineering won the National Second Prize.

2023.11 A team from the Deep Learning Innovation Group, composed of Junhao Pan from Data Science Class 2020, Bowen Tan from Data Science Class 2021, Tingting Li from Data Science Class 2022, and Shenkai Zhao from Computer Science Class 2021, participated in the 2023 National College Student Digital Media Technology Works and Creativity Competition. The team won the National First Prize in the 11th National College Student Digital Media Technology Works and Creativity Competition, and Professor Liu was awarded Outstanding Supervisor.

2023.3.10 The research paper “RE‑RCNN: A Novel Representation‑Enhanced RCNN Model for Early Apple Leaf Disease Detection”, authored by graduate students Huakun Ren, Jiaxin Li, and Nannan Duan, was accepted by the SCI journal ACM Transactions on Sensor Networks, a CCF‑B journal.

2022.12.09 The research paper “VMF‑SSD: A Novel V‑Space based Multi‑scale Feature Fusion SSD for Apple Leaf Disease Detection”, authored by graduate students Liangliang Tian and Nannan Duan, was accepted by the SCI journal IEEE/ACM Transactions on Computational Biology and Bioinformatics, a CCF‑B journal.

2022.08 A team from the Deep Learning Innovation Group, composed of Xianyu Zhu from Computer Science Class 2019, Runchang Jia from Information Management Class 2019, and Jinjiang Li from Software Engineering Class 2019, participated in the 2022 China Collegiate Computer Design Competition. The team won the First Prize in the Northwest Division and the National Third Prize in the 15th China Collegiate Computer Design Competition.

2022.07.08 The research paper “LAD‑Net: A Novel Light Weight Model for Early Apple Leaf Pests and Diseases Classification”, authored by Xianyu Zhu, an undergraduate student from Computer Science Class 2019 in the Deep Learning Innovation Group, was accepted by the SCI journal IEEE/ACM Transactions on Computational Biology and Bioinformatics, a CCF‑B journal.

2022.04.15 The research paper “A Lightweight Recognition Model for Apple Leaf Diseases and Pests on Mobile Devices”, authored by Runchang Jia, an undergraduate student from Information Management Class 2019 in the Deep Learning Innovation Group, was accepted by the EI‑indexed journal Transactions of the Chinese Society of Agricultural Engineering, the top journal in the discipline.

2021.08.06 The research paper “MEAN‑SSD: A Novel Real‑Time Detector for Apple Leaf Diseases Using Improved Light‑weight Convolutional Neural Networks”, authored by undergraduate students Henan Sun and Haowei Xu from Information Management Class 2018 in the Deep Learning Innovation Group, was accepted by the SCI journal Computers and Electronics in Agriculture, a CAS Q1 journal.

2021.04.15 The research paper “CGAN‑IRB: A Novel Data Augmentation Method for Apple Leaf Diseases”, authored by undergraduate students Xinbin Yuan from Information Management Class 2019 and Cong Yu from Software Engineering Class 2019 in the Deep Learning Innovation Group, was accepted by International Computer Software and Applications Conference, a CCF‑C recommended conference.

2020.08 A team from the Deep Learning Innovation Group, composed of Haowei Xu and Henan Sun from Information Management Class 2018, participated in the 2020 China Collegiate Computer Design Competition. The team won the First Prize in the Northwest Division and the National Third Prize in the 13th China Collegiate Computer Design Competition.

2020.06.30 The research paper “Grape Leaf Disease Identification Using Improved Deep Convolutional Neural Networks”, authored by Zefeng Ding, an undergraduate student from E‑commerce Class 2017 in the Deep Learning Innovation Group, was accepted by the SCI journal Frontiers in Plant Science, a CAS Q2 journal.

2020.06.23 Three undergraduate students of the Class of 2020, Jiyan Qiu from Information Management Class 161, Yuehan Chen from E‑commerce Class 162, and Peng Jiang from E‑commerce Class 162, respectively received the University‑level Top 100 Undergraduate Thesis Award, the University‑level Outstanding Undergraduate Thesis Award, and the College‑level Outstanding Undergraduate Thesis Award.

2020.05.12 The research paper “A Deep‑Learning‑Based Real‑Time Detector for Grape Leaf Diseases Using Improved Convolutional Neural Networks”, authored by Xiaoyue Xie from Information Management Class 2017 and Yuan Ma from Computer Science Class 2017 in the Deep Learning Innovation Group, was accepted by the SCI journal Frontiers in Plant Science, a CAS Q2 journal.

2019.11.22 Two teams from the Deep Learning Innovation Group, composed of Peng Jiang, Xiaoyue Xie, Yuan Ma, Liangliang Tian, Zefeng Ding, and Danni Yang, participated in the final of the 2019 China Collegiate Computing Contest — Artificial Intelligence Innovation Competition. Both teams won National Second Prizes, with a total cash award of RMB 20,000.

2019.4.18 Members of the Deep Learning Innovation Group, including Peng Jiang, Yuehan Chen, Zefeng Ding, and Cheng Tan, won Second Place in the Northwest Division of the 2019 Future Cup University AI Challenge and entered the national final. Liangliang Tian, Yun Zhang, Jiyan Qiu, and Xiaoyue Xie won the Excellence Award in the Northwest Division.

2018.06.28 Four undergraduate students of the Class of 2018, Xiao Qi from E‑commerce Class 141, Mingzhu Shen from Information Management Class 143, Chaoyang Liu from Computer Science Class 141, and Lixing Fan from Information Management Class 141, received the first University‑level Top 100 Undergraduate Thesis Award.

1. Artificial Intelligence and Computer Vision, Ph.D. Research Direction

This direction focuses on multimodal learning, multimodal fusion, few-shot learning, semi-supervised learning, and frontier basic research on algorithms in artificial intelligence and computer vision.

2. Deep Learning and Crop Disease and Pest Diagnosis, Master’s Research Direction

This direction focuses on the identification, monitoring, and early warning of crop diseases and pests, especially for crops such as apple, kiwifruit, and grape. The research summarizes the features and patterns of crop disease and pest recognition through image processing technologies, applies deep convolutional neural network models to crop disease and pest identification, and builds prediction models suitable for crop disease diagnosis.

The group also studies deep learning-based object detection algorithms such as SSD, Faster R‑CNN, and YOLO, and proposes neural network models that balance accuracy and real-time detection requirements for real-time monitoring and early warning of crop diseases and pests. In addition, the group conducts research on deep learning-based image segmentation algorithms.

3. Parallel Algorithms for Deep Learning, Master’s Research Direction

Parallel algorithms refer to methods and procedures that use multiple processors to jointly solve problems. The execution process first decomposes a given problem into several relatively independent subproblems, then uses multiple computers to solve them simultaneously, and finally obtains the solution to the original problem.

To address the limited parallelism in deep learning algorithms, Professor Liu’s group conducts research on algorithm parallelization for multi‑core and many‑core platforms. The research focuses on common parallel programming models such as Python, CUDA, and MPI, explicitly constructs parallel deep learning algorithms, and improves the speedup performance of deep learning parallel algorithms.

Outstanding students with a strong sense of responsibility, a strong curiosity for knowledge, active learning ability, and strong self‑discipline are welcome to apply. As long as you are willing to learn, everything is possible. Applicants who merely seek a diploma without serious academic commitment are not encouraged to apply. The training model combines regular group meetings with timely discussions.

Students who are interested in applying to work with Professor Liu as their supervisor are welcome to contact him by phone or WeChat: 18710487673.

Ph.D. and Postdoctoral Research Direction: 0828Z2 Agricultural Engineering

Master’s Research Directions: 0812 Computer Science and Technology, Academic Master’s Program; 0854 Electronic Information, Professional Master’s Program; 095136 Agricultural Engineering and Information Technology, Professional Master’s Program

2026 Doctoral Admission Brochure and Major Catalogue

Implementation Rules for 2026 Doctoral Application‑Assessment System (College of Information Engineering)

2026 Master Admission Brochure

Students who meet the following requirements are welcome to apply:

(1) A good command of English;

(2) Strong programming ability;

(3) Strong interest in algorithm research and software design.

Graduate Course: Deep Learning

Undergraduate Courses: Cloud Computing, C Programming, Parallel Programming

1. Research Projects: National‑Level, Provincial/Ministerial‑Level, and Other Research Projects

[21] National Natural Science Foundation of China, General Program, 62376226, “Research on Early Detection Methods for Apple Leaf Diseases Based on Multi‑source Image Information Fusion”, 2024/01–2027/12, Principal Investigator.

[20] Shaanxi Key R&D Program, Key Industrial Chain Project, 2024NC‑ZDCYL‑05‑05, “Research and Integrated Demonstration of an Early Monitoring and Early Warning Platform for Major Grain Crop Diseases and Pests”, 2024/01–2025/12, Sub‑project Principal Investigator.

[19] Yangling Demonstration Zone Science and Technology Program, 2024NY‑14, “Research on Intelligent Prediction, Forecasting and Control Prescription Recommendation for Early Wheat Leaf Diseases and Pests”, 2024/12–2026/11, Principal Investigator.

[18] Qinchuangyuan “Scientist + Engineer” Team Building Program, 2024QCY‑KXJ‑094, “‘Scientist + Engineer’ Team for Intelligent Monitoring and Early Warning of Kiwifruit Diseases”, 2024/01–2026/12, Chief Scientist.

[17] Shaanxi Key R&D Program, 2024NC‑YBXM‑191, “Research on Hyperspectral‑based Early Rapid Intelligent Diagnosis of Apple Leaf Diseases and Development of Inspection Equipment”, 2024/01–2025/12, Principal Investigator.

[16] Xi’an Key Technology Research Project for Key Agricultural Industry Chains, 2024JH‑NYZD‑0027, “Development and Demonstration of Intelligent Monitoring and Early Warning Technologies for Wheat Diseases”, 2024/01–2025/12, Principal Investigator.

[15] Xianyang Key R&D Program, L2020‑ZDYF‑NY‑019, “Research on Diagnosis and Control Recommendation Methods for Apple Leaf Diseases and Pests Based on Artificial Intelligence and Knowledge Graphs”, 2023/01–2024/12, Principal Investigator.

[14] Shaanxi Key R&D Program, Key Industrial Chain Project, 2023‑ZDLNY‑63, “Research and Demonstration of Artificial Intelligence‑based Diagnosis and Early Warning for Crop Diseases and Pests”, 2023/01–2024/12, Sub‑project Principal Investigator.

[13] Industry‑sponsored Project, 2023110801, “Development of Intelligent Diagnosis and Inspection Equipment for Kiwifruit Leaf Diseases”, 2023/11–2023/12, Principal Investigator.

[12] Industry‑sponsored Project, “Signal Processing Algorithms and Simulation Implementation”, 2022/09–2025/03, Principal Investigator.

[11] National Natural Science Foundation of China, Young Scientists Fund, 61602388, “Research on Irregular Algorithm Parallelization Based on Thread‑level Speculation”, 2017/01–2019/12, Principal Investigator.

[10] National Key R&D Program of China, 2020YFD1100601‑02‑13, “Research and Application of Knowledge Graph‑based Recommendation of Advanced and Applicable Agricultural Technologies”, 2020/01–2022/10, Sub‑task Principal Investigator.

[9] 2021 CCF‑Baidu Songguo Fund, “Cloud‑edge Collaborative Early Monitoring and Early Warning of Apple Leaf Diseases and Pests Based on PaddlePaddle”, 2021/07–2022/07, Principal Investigator.

[8] Shaanxi Key R&D Program, 2021NY‑138, “Research on Early Monitoring and Early Warning of Apple Leaf Diseases and Pests Based on Artificial Intelligence and Development of Inspection Equipment”, 2021/01–2022/12, Principal Investigator.

[7] Shaanxi Key R&D Program, Key Industrial Chain Project, 2019ZDLNY07‑06‑01, “Research on Intelligent Diagnosis, Monitoring and Early Warning of Apple Diseases Based on Big Data and AI Technology”, 2019/01–2021/12, Sub‑project Principal Investigator.

[6] Ningxia Smart Agriculture Industrial Technology Collaborative Innovation Center, 2017DC53‑01, “Research and Application of Real‑time Detection of Grape Diseases Based on Convolutional Neural Networks”, 2017/10–2020/10, Sub‑project Principal Investigator.

[5] Natural Science Foundation of Shaanxi Province, General Program, 2017JM6059, “Research on Machine Learning‑based Speculative Multithreading Partitioning Methods for Loop Structures”, 2017/01–2018/12, Principal Investigator.

[4] China Postdoctoral Science Foundation, 2017M613216, “Research on Parallelization of Agricultural Image Segmentation Algorithms in Cloud Computing Environments”, 2017/09–2019/08, Principal Investigator.

[3] Shaanxi Postdoctoral Science Foundation, 2016BSHEDZZ121, “Research on Parallelization of Agricultural Image Segmentation Algorithms Based on Spark Heterogeneous Clusters”, 2016/01–2018/01, Principal Investigator.

[2] Industry‑sponsored Project, 2022031001, “Development of an Agricultural Internet of Things Big Data Analysis and Visualization System”, 2022/03–2023/02, Principal Investigator.

[1] Industry‑sponsored Project, 2020SZNY‑06, “Development of a Big Data Dashboard Subsystem for Beef Cattle Farms and Management Platforms”, 2020/12–2021/11, Sub‑project Principal Investigator.

2. Selected Publications: Five Representative Works

[1] Bin Liu, Zhonghao Zhang, Hengzhao Li, Zeyu Ji*, Hongming Zhang, Keqin Li. LIBPipe: Efficient Load Imbalance Pipeline Model Parallelism for Large Models Training [J]. IEEE Transactions on Parallel and Distributed Systems, 2026: 4–13. Accepted. (CCF‑A, top journal in computer architecture)

[2] Bin Liu, Wei Sun, Qianqian Wang, Wei Feng, Yijie Chen, Haixi Zhang*. Rethinking Cross‑Modal Anchor Alignment for Mitigating Error Accumulation [C]. IEEE Conference on Computer Vision and Pattern Recognition, 2026: 1–8. Accepted. (CCF‑A, top conference in computer vision)

[3] Bin Liu, Yongyao Ma, Zijian Hu, Zeyu Ji*, Zhenli He*, and Keqin Li. GroPipe: A Grouped Pipeline Hybrid Parallel Method for Accelerating DCNNs Training [J]. IEEE Transactions on Computers, 2025: 1–14. Accepted. (CCF‑A, top journal in computer architecture)

[4] Wei Feng; Danting Liu; Qianqian Wang; Mengping Jiang; Bin Liu*. Federated Incomplete Multi‑View Clustering with Tensorized Low‑Rank Constraint [C]. The 40th Annual AAAI Conference on Artificial Intelligence, 2025: 1–15. (CCF‑A, top conference in artificial intelligence)

[5] Henan Sun#, Haowei Xu#, Bin Liu*, Dongjian He, Jinrong He, Haixi Zhang and Nan Geng. MEAN‑SSD: A Novel Real‑Time Detector for Apple Leaf Diseases Using Improved Light‑weight Convolutional Neural Networks [J]. Computers and Electronics in Agriculture, 2021.08. SCI; IF: 6.757; CAS Q1.

3. Awards and Honors: Representative Awards

[1] First Prize, Shaanxi Provincial Higher Education Teaching Achievement Award, “Exploration and Practice of Cultivating Innovative Computer Application Ability of Agricultural and Forestry Talents through System Optimization, Model Innovation, and Resource Enhancement”, 2019, ranked 6/7.

[2] First Prize, Teaching Achievement Award of Shaanxi Academic Degrees and Graduate Education Society, “Demand‑oriented, Classified Training, Discipline Collaboration: Improving the Computer Innovation and Application Ability of Graduate Students in Agricultural and Forestry Universities”, 2023, ranked 3/5.

[3] First Prize, Graduate Education Teaching Achievement Award of Northwest A&F University, “Discipline‑led, Interdisciplinary Empowerment, Collaborative Education: Cultivating the Innovation and Practical Ability of Non‑information Graduate Students in Agricultural and Forestry Universities”, 2023, ranked 3/7.

[4] Outstanding Communication Ambassador of the CCF Communication Committee in 2022 and 2023; the first CCF “Outstanding Communicator”.

[5] Outstanding Supervisor of Top 100 Undergraduate Theses/Designs for the Classes of 2018, 2020, and 2022.

[6] Outstanding Supervisor for Student Innovation and Entrepreneurship in 2018, 2019, and 2023.

[7] University‑level Advanced Individual in 2019.

[8] Outstanding Supervisor for the National First Prize in the 11th National College Student Digital Media Technology Works and Creativity Competition.

4. Discipline Competitions: Five Representative Awards

[1] The 11th National College Student Digital Media Technology Works and Creativity Competition, 2023, National First Prize.

[2] The 2nd China Collegiate Computing Contest — Artificial Intelligence Innovation Competition, 2019, two teams both won National Second Prizes, with a total cash award of RMB 20,000.

[3] The 13th China Collegiate Computer Design Competition, 2020, National Third Prize.

[4] The 13th China Collegiate Computer Design Competition, 2021, National Third Prize.

[5] ACM China International Parallel Computing Challenge, 2021, Super Cloud Computing Education Fund Award.

5. Teaching Reform Projects: Representative Projects

[1] Shaanxi Provincial Professional Degree Graduate Teaching Case, “Research on Teaching Cases for Intelligent Diagnosis of Crop Diseases Based on Artificial Intelligence”, 2025, Principal Investigator.

[2] National Virtual Teaching and Research Office of the Department of Higher Education, Ministry of Education, “Intelligence + New Agricultural Science” Curriculum Virtual Teaching and Research Office, 2022, ranked 4/16.

[3] Shaanxi Key Teaching Reform Research Project for Undergraduate and Continuing Education, “Research and Practice on the Construction Model of Competency‑oriented New Agricultural Science Artificial Intelligence Course Groups and New‑form Teaching Resources”, 2024/01–2025/12, Northwest A&F University, ranked 4/5.

[4] Shaanxi Key Teaching Reform Research Project for Undergraduate and Continuing Education, “Construction and Practice of an AI + Course Group Teaching Research Center under the Background of Four‑New Major Development”,2022/01–2023/12, Northwest A&F University, ranked 3/5.

[5] Northwest A&F University First‑class Undergraduate Course, “Cloud Computing”, 2022, Principal Investigator.

6. Undergraduate Talent Training: Five Representative Works

[1] Jiyan Qiu, Information Management Class 161, “GPU‑based Fast Ink Painting Generation Algorithm”, University‑level Top 100 Undergraduate Thesis.

[2] Mingzhu Shen, Information Management Class 143, “Prediction of Question Answering Satisfaction on the Stack Overflow Forum”, University‑level Top 100 Undergraduate Thesis.

[3] Chaoyang Liu, Computer Science Class 141, “Research on CUDA‑based Parallel Fast Pencil Drawing Generation Algorithm”, University‑level Top 100 Undergraduate Thesis.

[4] Lixing Fan, Information Management Class 141, “Research on Parallel Graph Repartitioning Algorithm Based on Vertex Partitioning”, University‑level Top 100 Undergraduate Thesis.

[5] Xiao Qi, E‑commerce Class 141, “Research on Parallel Boyer‑Moore‑Horspool Matching Algorithm Based on OpenMP”, University‑level Top 100 Undergraduate Thesis.