教师主页移动版

综合介绍 General Introduction 张育培，西北工业大学、计算机学院、计算机科学与软件系长聘副教授，博士生导师、硕士生导师，工信部大数据存储与管理重点实验室成员，宾夕法尼亚大学（美）博士后研究员，中国计算机协会信息系统专委执行委员，教育部学位与研究生教育评审专家。2017年12月，毕业于西安交通大学计算机科学与技术系，获得博士学位；2018年至2020年，任职博士后研究员于埃默里大学(美)和佐治亚理工学院(美)；2020年至2021年，任职博士后研究员于宾夕法尼亚大学（美）；2018年至2023年，任职助理教授于西北工业大学计算机学院。国际教育数据挖掘协会会员、国际学习分析协会会员、IEEE协会会员，研究方向包含：大规模数据科学分析（教育数据科学、学习科学和生物医学数据分析）、科研及工程工具构建（深度学习、机器学习和统计学习）、理论计算基础（压缩感知、拓扑图论和信息论）。曾多次组织举办（协办）国际学术会议（ICDM、ER等）和任职于国际著名会议（IJCAI、LAK等），多次担任知名期刊（TPAMI、TMI、NN、PR等）客座编辑和审稿人，主持和参与多项国家级青年、面上、重点、和省部级重点研发等基金项目。（website：https://yupei-zhang.github.io/） 个人相册

教育教学

教育教学 Education and teaching 招生信息 教育信息 博士后：待遇丰厚，欢迎联系。博士生（1 ~ 2人/年）：方向1：复杂结构发现与表征学习；方向2：脑智机理与学习科学；方向3：类人智能建模与算法，等。硕士生（2～4人/年）：方向：机器学习、数据挖掘、大数据系统、神经影像分析。将针对个人兴趣，个性化定制研究课题。本科生（4～6人/年）：结合当前课题，加入研究组，与博士、硕士一起完成研究任务，并可以提前开始本科毕业设计。联系邮箱：ypzhaang AT nwpu DOT edu DOT cn 或 yupei.zhang@hotmail.com>> >>  >> >>目前团队已建立的国际合作高校：杜伦大学（英）、麻省大学（美）、宾夕法尼亚大学（美）、普林斯顿大学（美）、康奈尔大学（美）埃默里大学（美）、布朗大学（美）、莱斯大学（美）、九州大学（日）、多伦多大学（加）、赫尔辛基大学（芬） FEATURED COURSES+ 模式识别与机器学习. 本科. (课程支撑网站：https://yupei-zhang.github.io/machlearn-zhyp.html)>> >> 2022年春季. 32学时, 课程号：U10M11170.04，2019级信息大类基础课，96人。>> >> 2023年春季. 32学时, 课程号：U10M11170.03，2020级信息大类基础课，100人。>> >> 2023年春季. 32学时, 课程号：U10M11170.04，2021级信息大类基础课，55人。+ 机器智能与学习科学 （Machine Intelligence and Learning Science）. 研究生. >> >> 2022年秋季. 32学时, 课程号：M10L12004，2022级研究生，146人.（2022年学术论文研讨会主页）。>> >> 2023年秋季. 32学时, 课程号：M10L12004，2022级研究生，139人。OTHER COURSES+ 2021年秋季.  本科. 计算机系统基础实验, 24学时，课程号：U10M21003.08，2020-2021级信息大类基础课，73人。+ 2018年秋季.  本科. C语言编程（全英）, 48学时，课程号：U10G12030.01，2018级国际班，47人。[More] + 2018年秋季.  本科. C语言实验（全英）, 32学时，课程号：U10G22031.01，2018级国际班，48人。[More]

荣誉获奖

团队信息 Team Information >> 隶属：国家工业和信息化部大数据存储与管理重点实验室 <<>> >> 数据挖掘实验室 负责人：尚学群教授. https://teacher.nwpu.edu.cn/Shang.html >> >> 研究组 ：机器与人类学习科学（MAchine and People LEarning Science, Maples）导师：尚学群教授、张育培副教授研究助理：李承欣博士生：代欢、云岳、崔嘉琪、张雯鑫、安蕊硕士生：韦双双、王亦菲、徐宇楠、李钰心、曲希然、伍智广、刘梦飞、圣贤、Riyan Hasan本科生：曹家赫、杨力维、李长顺、陆骏、任梓涵、孙海岩、孙丽倩、曾雨来、田菁菁、龙世宏、孙安澜、张一平、王景珩>> >>  >> >> 毕业生及去向-- 博士生：刘树慧（2022年毕业，清华大学博后）-- 硕士生：安蕊（2022级硕士毕业，转博）, 云岳（2019级硕士毕业，转博）, 代欢（2018级硕士毕业，转博），周娅娅（2023硕士毕业，银行）-- 本科生：2018级本科毕业：安蕊（西工大读硕）                   2022级本科毕业：李钰心（西工大读硕）, 曲希然（西工大读硕）, 陈昊琦（南京大学读硕）, Khan Md Shahedul Islam（西工大读硕）, 李向博（深圳传音）                   2023级本科毕业：刘梦飞（西工大读硕）, 申延（西工大读硕）, 朱迪（西工大读硕）,  刘毅勇（清华大学读硕）, 刘颖（西工大读硕）, 胡博岩（布里斯托大学（英）读硕）

科学研究

科学研究 Scientific Research >> >> 深究理论计算基础，研建深度、统计与机器学习模型工具，发掘大数据科学规律与自然存在，关注国家战略、人类生存与知识 << <<欢迎擅长数学和计算机编程的、积极主动的本科生、研究生加入数据挖掘实验室（带头人尚学群教授）或联合开展科学研究。Welcome to highly motivated students with exceptional skills in Mathematics and Computer Science to join Our Lab, under the leadership of Professor Shang.欢迎访问、加入机器学习与学习科学研究组：https://yupei-zhang.github.io/people.html联系邮箱：yupei DOT zhang AT hotmail DOT comFUNDING+ 教育数据挖掘. 2023-2025，中央高校基本经费（重点布局），No. G2023KY0603，主持.+ 基于多源异构大数据的智能导学系统研究. 2023-2024，陕西省重点研发计划，No. 2023-YBGY-405. 主持.+ 智能网联车多模态数据管理理论与关键技术研究. 2023-2026，国家自然科学基金（联合重点），No. U22A2025. 参与.+ 基于多维关联网络表征的导学链接预测方法研究. 2023-2026， 国家自然科学基金（面上项目），No. 62272392.  主持.+ 教育信息学—交叉学科培育. 2022-2024，“双一流”建设项目，执行负责人.+ 学生出国（境）交流项目管理与评价机制研究. 2022-2023，西北工业大学高等教育研究基金（重点项目），No. GJGZZD202202.  主持.+ 教与学的路径智能规划研究. 2021-2022，西北工业大学教改项目（一般项目），No. 2021JGY31.  主持.+ 基于金融时序知识图谱的舆情分析与风险防控. 2021-2025，科技部“新一代人工智能”（重大项目），No. 2020AAA0108504. 参与.+ 基于脑影像数据和基因表达数据融合的脑基因网络构建与疾病基因预测. 2021-2024，国家自然科学基金(面上项目)，No. 62072376. 参与.+ 癌症动态演化机制及其驱动因子识别研究. 2020-2023，国家自然科学基金(面上项目)，No. 61972320. 参与.+ 基于大数据的精准教学评价和学习行为预测理论与方法研究. 2019-2022，国家自然科学基金(联合重点)，No. U1811262. 执行团队负责人.+ 面向个性化教学问题的结构化稀疏表示方法研究. 2019-2021，国家自然科学基金(青年项目)，No. 61802313. 主持.+ 机器学习与个性化教育. 2018-2019，西北工业大学创新团队建设基金，No. 18GZ040113. 主持.+ 基于结构化稀疏表示方法的认知诊断和成绩预测研究. 2018-2020，中央高校基本研究经费，No. G2018KY0301. 主持.

学术成果

学术成果 Academic Achievements >> >> 更新日期：2023-5-21谷歌学术：https://scholar.google.com.hk/citations?user=shTTzw0AAAAJ&hl=zh-CN&oi=ao 研究方向1: 时空结构与机器学习[51]  Y Zhang, Y Wang, et al. Federated discriminative representation learning for image classification[J]. IEEE transactions on neural networks and learning systems, 2023.（1区, IF=10.2）[51]  Y Zhang, Y Xu, et al. Doubly contrastive representation learning for federated image recognition[J]. Pattern Recognition, 2023, 139: 109507.（1区, IF=8.5）研究方向2: 学习科学与教育大数据[51]  Y Zhang, Y Li, et al. Federated learning-outcome prediction with multi-layer privacy protection[J]. Frontiers of Computer Science, 2024.（CCF B, IF=4）[51]  H Dai, Y Zhang*, et al. Adaptive meta-knowledge dictionary learning for incremental knowledge tracing[J]. Engineering Applications of Artificial Intelligence, 2024.（1区, IF=8.0）[51]  Y Yue,..,Y Zhang, et al. Doubly constrained offline reinforcement learning for learning path recommendation[J]. Knowledge-Based Systems, 2024.（1区, IF=8.8）[51]  Y Zhang, R An, et al. Predicting and understanding student learning performance using multi-source sparse attention convolutional neural networks[J]. IEEE Transactions on Big Data, 2023.（ESI高被引,IF=7.2）研究方向3: 生-医-神数据分析与理解[50]  Liu S, Yupei Zhang, et al. An improved hierarchical variational autoencoder for cell–cell communication estimation using single-cell RNA-seq data[J]. Briefings in Functional Genomics, 2023.（IF=4.8）[51]  Y Zhang, D Xian, et al. Landmark tracking in liver US images using cascade convolutional neural networks with lstm[J]. Measurement Science and Technology, 2023.（国合,IF=3.1）[51]  Y Zhang, X He, et al. Multi-needle detection in 3D ultrasound images using unsupervised order-graph regularized sparse dictionary learning[J]. IEEE transactions on medical imaging, 2020.（1区, IF=10.1）[48]  Yupei Zhang, Xu Y, Wei S, et al. Personalized Federated Contrastive Learning[C]. IEEE International Conference on Big Data, 2022: 4218-4225.机器学习、教育数据挖掘，IF=领域会议）[47]  Yupei Zhang, Wei S, Wang Y, et al. A Personalized Federated Learning Framework Using Side Information for Heterogeneous Data Classification[C]. IEEE International Conference on Big Data, 2022: 3455-3461.（机器学习、教育数据挖掘，IF=领域会议）[46]  Yupei Zhang, Xu Y, An R, et al. Markov Guided Spatio-Temporal Networks for Brain Image Classification[C]. IEEE International Conference on Bioinformatics and Biomedicine, 2022: 2035-2041.（机器学习、学习认知科学，IF=领域国际会议）[45]  Yupei Zhang, Wei S, Liu S, et al. Graph-regularized federated learning with shareable side information[J]. Knowledge-Based Systems, 2022, 257: 109960.（机器学习，IF=8.0）[44]  Zhang W, Yupei Zhang*, Liu S, et al. Online Deep Knowledge Tracing[C]. 2022 IEEE International Conference on Data Mining Workshops (ICDMW). IEEE, 2022: 292-297.（机器学习、教育数据挖掘，IF=领域国际会议）[43]  Liu S, Yupei Zhang*, Shang X. GLassonet: Identifying Discriminative Gene Sets among Molecular Subtypes of Breast Cancer[J]. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2022.（机器学习、生物数据挖掘，IF=3.0）[42]  Yun Y, Dai H, Yupei Zhang*, et al. Interpretable Educational Recommendation: An Open Framework based on Bayesian Principal Component Analysis[C]. IEEE International Conference on SMC, 2022.（机器学习、教育数据挖掘，IF=领域国际会议）[41]  Yupei Zhang*, Zhou Y, Liu S, et al. WeStcoin: Weakly-Supervised Contextualized Text Classification with Imbalance and Noisy Labels[C]. 26th International Conference on Pattern Recognition, 2022.（机器学习、教育数据挖掘，IF=领域国际会议）[40]  Yupei Zhang*, Khan M S I, Zhou Y, et al. An Effective Chinese Text Classification Method with Contextualized Weak Supervision for Review Autograding[C].18th ICIC,  2022.（机器学习、教育大数据挖掘，IF=领域国际会议）[39]  Liu S, Yupei Zhang*, Shang X. Functional Analysis of Molecular Subtypes with Deep Similarity Learning Model Based on Multi-omics Data[C]. 18th ICIC,  2022.（机器学习）[38]  Dai H, Yun Y, Yupei Zhang*, et al. Contrastive Deep Knowledge Tracing[C]. Artificial Intelligence in Education. AIED, 2022: 289-292.（机器学习、教育数据挖掘，IF=领域国际会议）[37]  Liu S, Yupei Zhang*, Peng J, et al. Identifying non-math students from brain mris with an ensemble classifier based on subspace-enhanced contrastive learning[J]. Brain Sciences, 2022, 12(7): 908.（机器学习、学习科学，IF=3.3）[36]  Yupei Zhang, Liu S, Qu X, et al. Multi-instance discriminative contrastive learning for brain image representation[J]. Neural Computing and Applications, 2022: 1-14.（机器学习、学习科学，IF=5.1）[35]  Yupei Zhang, Dai X, Tian Z, et al. Liver motion tracking in ultrasound images using attention guided mask R-CNN with long-short-term-memory network[C]. SPIE, 2022, 12038: 156-161.（机器学习、医学影像，IF=领域国际会议）[34]  Jiaqi Cui, Yupei Zhang*, Rui An, Yue Yun, Huan Dai, and Xuequn Shang. "Identifying Key Features in Student Grade Prediction", IEEE_PIC, 2021.（机器学习、教育信息学，IF=领域国际会议）[33]  Yupei Zhang, Yaya Zhou, Yue Yun, Rui An, Xuequn Shang. "Comment Text Grading for Chinese Graduate Academic Dissertation Using Attention Convolutional Neural Network", IEEE_ICSAI, 2021.（机器学习、教育文本分析，IF=领域国际会议）[32]  Huan Dai, Yupei Zhang*, Yue Yun, Xuequn Shang. "VarSKD: A Variational Student Knowledge Diagnosis for Efficiently Representing Student Latent Knowledge Space", IEEE_BigData, 2021.（机器学习、认知诊断与追踪，IF=领域国际会议）[31]  Yupei Zhang, Yue Yun, Rui An, Huan Dai, Jiaqi Cui, Xuequn Shang. "Educational Data Mining Techniques for Student Performance Prediction: Method Review and Comparison Analysis", Frontiers in Psychology, 2021.（机器学习、教育心理学, IF = 3.0 SSCI）[30]  Huan Dai, Yupei Zhang*, Yue Yun, Xuequn Shang. "An Improved Deep Model for Knowledge Tracing and Question-Difficulty Discovery", PRICAI, 2021.（机器学习、教育大数据分析）[29]  Yupei Zhang, Rui An, Shuhui Liu, Jiaqi Cui, Xuequn Shang. "Predicting and Understanding Student Learning Performance Using Multi-source Sparse Attention Convolutional Neural Networks", IEEE Transactions on Big Data, 2021.（机器学习、教育大数据分析, IF = 3.4）[28] Yue Yun, Huan Dai, Yupei Zhang*, Xuequn Shang, Zhanhuai Li. "State-of-the-art Survey of Personalized Learning Path Recommendation", Journal of Software, 2021.（机器学习、计算教育学，IF = 中文期刊）[27] Yue Yun, Huan Dai, R Cao, Yupei Zhang*, and Xunqun Shang. "Self-paced graph memory network for student GPA prediction and abnormal student detection", Internation Conference on Artificial Intelligence in Education. 2021.（国际智能教育顶级会议，IF = Top4）[26] Yupei Zhang, Shuhui Liu, Xuqun Shang. "A MRI Study on Effects of Math Education on Brain Developments Using Multi-instance Contrastive Learning", Frontiers in Fsychology. 2021. （机器学习、脑认知科学、IF=3.0 SSCI）[25] Shuhui Liu#, Yupei Zhang#, Xuequn Shang, Zhaolei Zhang. "ProTICS reveals prognostic impact of tumor infiltrating immune cells in different molecular subtypes". Briefings in Bioinformatics, 2021.（生物信息学、机器学习，IF = 11.6）[24] Yupei Zhang, Rui An, Jiaqi Cui, et. al. "Undergraduate grade prediction in Chinese higher education using convolutional neural networks", International Learning Analytics and Knowledge Conference. 2021. （计算机>>教育技术顶级会议，IF = Top1）[23] Xianjian Dai, Yang Lei, Yupei Zhang, et. al. "Deep learning-based multi-catheter reconstruction for MRI-guided HDR prostate brachytherapy", SPIE Medical Imaging, 2021.（机器学习、医学影像,  IF = 第49届国际光学会议）[22] Yupei Zhang, Yang Lei, et. al. "Region of interest discovery using discriminative concrete autoencoder for COVID-19 lung CT images", SPIE Medical Imaging, 2021.（机器学习、医学影像,  IF = 第49届国际光学会议）[21] Yupei Zhang, Zhen Tian, et. al., "Multi-needle detection in ultrasound image using max-margin mask R-CNN", SPIE Medical Imaging, 2021.（机器学习、医学影像,  IF = 第49届国际光学会议）[20] Yupei Zhang, Yang Lei, Xiuxiu He, et. al. "Ultrasound multi-needle detection using deep attention U-Net with TV regularizations", SPIE Medical Imaging, 2021.（机器学习、医学影像,  IF = 第49届国际光学会议）[19] Yupei Zhang, Huan Dai, Yue Yun, Shuhui Liu, Andrew Lan, and Xuequn Shang, "Meta-knowledge dictionary learning on 1-bit response data for student knowledge diagnosis", Knowledge-Based Systems, 2020.（教育数据科学、机器学习， IF = 8.0）[18] Yupei Zhang, Zhen Tian, Yang Lei, et. al. "Automatic multi-needle localization in ultrasound image using large margin mask RCNN for ultrasound-guided prostate brachytherapy", Physics in Medicine & Biology, 2020.（机器学习、医学影像，IF = 3.6）[17] Yupei Zhang, Shuhui Liu. "Integrated Sparse Coding With Graph Learning for Robust Data Representation", IEEE Access, 2020.（机器学习、流行学习, IF = 3.7）[16] Xianjin Dai, Yang Lei, Yupei Zhang, et. al. Automatic multi‐catheter detection using deeply supervised convolutional neural network in MRI‐guided HDR prostate brachytherapy", Medical Physics, 2020.（机器学习、医学影像，IF = 4.1）[15] Yupei Zhang, Yang Lei, R Qiu, et. al. "Multi-needle localization with attention U-Net in US-guided HDR prostate brachytherapy", Medical Physics, 2020.（机器学习、医学影像，IF = 4.1）[14] Qiulan, Zeng, Yabo Fu, Zhen Tian, Yang Lei, Yupei Zhang, et. al. "Label-driven magnetic resonance imaging (MRI)-transrectal ultrasound (TRUS) registration using weakly supervised learning for MRI-guided prostate radiotherapy", SPIE Medical Imaging, 2020.（机器学习、医学影像, IF = 国际光学医学影像第48届会议）[13] Yupei Zhang, Xiuxiu He, Zhen Tian, J Jeong, et. al. "Multi-needle detection in 3D ultrasound images with sparse dictionary learning", SPIE Medical Imaging, 2020.（机器学习、医学影像, IF = 国际光学医学影像第48届会议）[12] Yupei Zhang, J Harms, Yang Lei, T Wang, et. al. "Weakly supervised multi-needle detection in 3D ultrasound images with bidirectional convolutional sparse coding", SPIE Medical Imaging, 2020.（IF = 国际光学医学影像第48届会议，最佳论文奖，机器学习、医学影像）[11] Yupei Zhang, Yue Yun, Huan Dai, et. al. "Graphs regularized robust matrix factorization and its application on student grade prediction". Applied Science, 2020. （机器学习、教育数据科学，IF = 2.7）[10] Yupei Zhang, Xiuxiu He, Zhen Tian, Jiwoong Jason Jeong, et al. " Multi-needle detection in 3D ultrasound images using unsupervised order-graph regularized sparse dictionary learning", IEEE Transactions on Medical Imaging, 2020.（机器学习、医学影像分析，IF = 10.1）[9] Yupei Zhang, Huan Dai, Yue Yun, et. al. "Student knowledge diagnosis on response data via the model of sparse factor learning", International Conference on Educational Data Mining. 2019. (教育数据挖掘顶级会议，IF = Top4)[8] Bo Yang, Yupei Zhang, Shanmin Pang et. al. "Integrating multi-omic data with deep subspace fusion clustering for cancer subtype prediction", IEEE/ACM Transaction on Computational Biology and Bioinformatics, 2019.（机器学习、生物信息学，IF = 3.7）[7] Yupei Zhang, Shuhui Liu, Xuequn Shang, et. al. "Low-rank graph regularized sparse coding", PRICAI. 2018 (人工智能知名会议)[6] Yupei Zhang, Ming Xiang, and Bo Yang, "Hierarchical sparse coding from a Bayesian perspective", Neurocomputing, 2018.（统计学习、压缩感知，IF = 5.7）[5] Yupei Zhang, Ming Xiang, and Bo Yang, "Graph regularized nonnegative sparse coding using incoherent dictionary for approximate nearest neighbor search", Pattern Recognition, 2017.（统计学习、机器学习，IF = 7.7）[4] Yupei Zhang, Ming Xiang, and Bo Yang, "Low-rank preserving embedding", Pattern Recognition, 2017.（流形学习、拓扑计算，IF = 7.7）[3] Bo Yang, Ming Xiang, and Yupei Zhang, "Multi-manifold discriminant Isomap for visualization and classification", Pattern Recognition, 2016.（机器学习、流形学习，IF = 7.7）[2] Yupei Zhang, Ming Xiang, and Bo Yang, "Linear dimensionality reduction based on hybrid structure preserving projections", Neurocomputing, 2016. （机器学习、流形学习，IF = 5.7）[1] Bo Yang, Ming Xiang, and Yupei Zhang. "Learning discriminant isomap for dimensionality reduction", IJCNN, 2015. （机器学习、流形学习）

综合介绍

学术活动 Professional Activities >> >> 更新于2024-02-26+ 2024年2024-02-26：恭喜曲希然论文“Concept Prerequisite Relation Prediction by Using Permutation-Equivariant Directed Graph Neural Networks” 被AI4ED-AAAI评选为最佳论文！+ 2023年2023-12-14：恭喜曲希然论文“Concept Prerequisite Relation Prediction by Using Permutation-Equivariant Directed Graph Neural Networks” 被AI4ED录用！2023-12-12：于人工智能论坛做关于《智能教育中知识结构的构建、挖掘与发现》报告。2023-12-01：恭喜王亦菲论文“Federated Discriminative Representation Learning for Image Classification” 被《IEEE Transactions on Neural Networks and Learning Systems》录用！2023-11-27：恭喜刘梦飞论文“Course-association Discovery From Academic Performance Using Improved LassoNet” 被国际计算机教育大会录用！2023-10-13：恭喜本科生王景珩论文“Learning path design on knowledge graph by using reinforcement learning” 被CCF B会录用！2023-10-13：恭喜本科生孙丽倩论文“Semantic Concept Recognition in Learning Brain by Using Deep Convolutional Networks” 被CCF B会录用！2023-10-13：恭喜本科生张一平论文“Concept-level Recognition from Neuroimages for Understanding Learning in The Brain”被CCF B会录用！2023-10-13：恭喜李钰心论文“Learning-Disability Recognition by Using Sparse Spatio-Temporal Graph Neural Networks” 被BIBM2023录用！2023-07-09：恭喜雷野论文“Knowledge-Concept Diagnosis from fMRIs by using a Space-Time Embedding Graph Convolutional Network” 被WISA2023录用！2023-06-28：恭喜李钰心论文“Federated Learning-Outcome Prediction with Multi-layer Privacy Protection”被期刊《Frontiers of Computer Science》录用！2023-06-20：恭喜安蕊论文“Deep Knowledge Tracing with Concept Trees”被国际会议ADMA2023录用！2023-05-20：课题组“教育数据挖掘" 项目受到西北工业大学支持，入选重点布局资助。2023-04-15：论文“Predicting and understanding student learning performance using multi-source sparse attention convolutional neural networks, IEEE Transactions on Big Data". 入选领域高被引论文，被ESI收录。2023-03-10：课题组于2023年国际数据挖掘会议（ICDM）承办第二届人工智能与教育大数据研讨会（AiBDE），任会议主席，信息主页：https://vpomelo.github.io/AIBDE2023/ ，将于中国上海召开，欢迎新老朋友投稿！2023-03-03：恭喜徐宇楠论文“Doubly contrastive representation learning for federated image recognition” 被期刊《Pattern Recognition》录用！2023-02-07：论文“An improved hierarchical variational autoencoder for cell–cell communication estimation using single-cell RNA-seq data” 被期刊《Briefings in Functional Genomics》录用！2023-02-02：论文“Landmark tracking in liver US images using cascade convolutional neural networks with long short-term memory” 被老牌期刊《Measurement Science and Technology》录用！2023-01-12：基金项目《基于多源异构大数据的智能导学系统研究》受到陕西省教育厅推荐，入选陕西省重点研发计划资助！+ 2022年2022-11-23：恭喜徐宇楠论文“Markov Guided Spatio-Temporal Networks for Brain Image Classification”被IEEE_BIBM 2022录用！2022-11-06：恭喜徐宇楠论文“Personalized Federated Contrastive Learning”被IEEE_BigData 2022录用！2022-11-06：恭喜刘树慧论文“GLassonet: Identifying Discriminative Gene Sets among Molecular Subtypes of Breast Cancer”被《IEEE/ACM Transactions on Computational Biology and Bioinformatics》录用！2022-11-04: 恭喜韦双双论文“A Personalized Federated Learning Framework Using Side Information for Heterogeneous Data Classification”被IEEE_BigData 2022录用！2022-09-28: 恭喜韦双双论文“Graph Regularized Federated Learning with Shareable Side Information”被《knowledge-based system》录用！2022-09-27: 恭喜张雯鑫论文“Online Deep Knowledge Tracing”被IEEE_ICDM2023录用！2022-09-16: 受邀发起并组织“人工智能在脑认知与教育的研究（AI in BCDE）”专题，已在《Frontiers in Computational Neuroscience》（SCI）、《Frontiers in Education》（ESCI）和《Frontiers in Psychology》（SSCI）三方上线，担任期刊客座编辑，点击主页地址 。2022-09-12: 受邀担任 International Conference on Learning Analytics & Knowledge (智能教育顶级会议，LAK 2023）程序委员.2022-09-08: 获批国家自然科学基金（面上项目）《基于多维网络表征的导学链接预测方法研究》的研究支持.2022-07-08: 恭喜刘树慧论文“Identifying non-math students from Brain MRIs with an ensemble classifier based on subspace-enhanced contrastive learning”被《Brain Sciences》（IF=3.3）录用！2022-07-04: 恭喜云岳论文“Interpretable Educational Recommendation: An Open Freamework Based on Bayesian Principal Component Analysis”被IEEE_SMC2022录用！2022-06-29: 恭喜本科生李钰心获得2022届西北工业大学“优秀毕业论文”奖励！2022-06-10: 恭喜本科生陈昊琦、李钰心获得2022届西北工业大学“优秀本科毕业生”称号！2022-06-08: 受邀参加“第六届全国高等教育监测学术大会”，并就“大数据与智慧教育”为题做邀请报告！2022-06-07: 恭喜本科生曲希然参与证明的论文“Multi-instance Discriminative Contrastive Learning for Brain Image Representation”被《Neural Computing and Applications》（IF=5.8）录用！2022-05-28: 恭喜刘树慧的论文“Functional Analysis of Molecular Subtypes with Deep Similarity Learning Model based on Multi-omics Data”被ICIC2022（第18届国际智能计算大会）录用！2022-05-28: 恭喜本科生Md Shahedual Islam Khan的毕设论文“An Effective Chinese Text Classification Method with Contextualized Weak Supervision for Review Autograding”被ICIC2022（第18届国际智能计算大会）录用！2022-04-26: 恭喜代欢论文“Contrastive Deep Knowledge Tracing”被AIED2022录用！2022-04-26: 受邀担任 International Conference on Education and E-Learning (ICEEL 2022)组委会成员.2022-04-14: 访问科大讯飞丝路总部并就“机器学习与智能教育”作研究报告并研讨产学研合作.2022-04-05: 受邀于The 22nd IEEE International Conference on Data Mining 组织以“Data Mining in Learning Science”为主题的研讨会并担任会议主席.2022-03-29: 恭喜周娅娅论文“WeStcoin: Weakly-Supervised Contextualized Text Classification with Imbalance and Noisy Labels”被ICPR2022_IAPR录用！2022-03-22: 受邀担任 International Conference on Intelligent Computing (ICIC2022) PC Member.2022-03-20: 恭喜张雯鑫获批西北工业大学教育教学改革项目一项！2022-02-14: 受邀担任 International Conference on Modern Educational Technology (ICMET2022_ACM)组委会成员.2022-01-15: 受邀于鹏城实验室就“联邦学习系统与大数据科学分析”做学术报告.2022-01-06: 邀请华东师范大学陆雪松副研究员就“水杉学习系统”做学术报告. + 2021年2021-12-24: 课题组获批西北工业大高等教育研究基金（重点项目）一项！2021-12-01: 恭喜崔嘉琪论文“Identifying Key Features in Student Grade Prediction”被IEEE PIC_2021录用！2021-11-23: 受邀担任 International Conference on E-society E-Learning and E-Technologies (ICSLT2022, Rome, Italy) 组委会成员.2021-11-11: 恭喜周娅娅论文“Comment Text Grading for Chinese Graduate Academic Dissertation Using Attention Convolutional Neural Networks”被IEEE ICSAI 2021录用！2021-11-02: 恭喜云岳、安蕊，等课题组成员协作论文“Educational Data Mining Techniques for Student Performance Prediction: Method Review and Comparison Analysis”被《Frontiers in Psychology》录用！2021-11-02: 受邀担任 International Conference on SEE Internet of Things (SEEIoT2021_GSRA) 组委会成员.2021-11-01: 恭喜安蕊论文“Predicting and Understanding Student Learning Performance Using Multi-source Sparse Attention Convolutional Neural Networks”被《IEEE Transactions on Big Data》录用！2021-10-28: 恭喜代欢论文“VarSKD: A Variational Student Knowledge Diagnosis for Efficiently Representing Student Latent Knowledge Space”被IEEE BigData 2021录用！2021-10-25: 受邀担任 IEEE International Conference on Progress in Informatics and Computing（PIC2021_IEEE）程序委员（PC member）.2021-10-22: 组织并担任“教育大数据高端国际研讨会2021”程序委员主席. http://www.nwpu-bioinformatics.com/AIBDE/index.html 2021-10-15: 恭喜云岳论文“个性化学习路径推荐”被《软件学报》录用！2021-08-09: 恭喜代欢论文“An improved deep model for knolwledge tracing and question-difficulty discovery”被PRICAI2021录用！2021-06-17: 受邀担任 International Conference on Big Data and Education (ICBDE2022_ACM) 组委会成员.2021-04-05: 恭喜云岳论文“Self-paced Graph Memory Network for Student GPA Prediction and Abnormal Student Detection”被AIED2021录用！2021-02-22: 受邀担任 International Conference on Modern Educational Technology (ICMET2021_ACM) 智能教育分会主席.2021-01-13: 恭喜安蕊论文“Undergraduate Grade Prediction in Chinese Higher Education Using Convolutional Neural Networks”被LAK21录用！更多学术活动：https://yupei-zhang.github.io/activities.html