本科、碩士畢業于南京大學計算機科學與技術專業，博士畢業于bet356手机版唯一官网登录計算機應用技術專業，曾先後在香港大學電子商務研究所、美國佐治亞州立大學訪問進修、工作。現任bet356手机版唯一官网登录教授，中國計算機學會大數據專家委員會委員，江蘇省大數據專家委員會副主任，江蘇省生物信息學會委員。主要研究興趣包括數據密集型計算、數據挖掘和機器學習、生物信息學等。本人長期從事數據分析與挖掘工作，近年來在面向大數據的網絡表示學習與挖掘，大數據下的深度學習及推薦，大數據下的數據倉庫建模及複雜查詢分析等方面進行了較深入的研究，積累了大量經驗和成果，并發表相關多篇論文。
大數據技術、數據挖掘和機器學習、生物信息學等
l 中藥分子标識大數據智能挖掘研究及其在中藥示範中的應用，國家重點研發計劃課題
l 立法公衆意見綜合分析及法律條文智能審查技術研究，國家重點開發計劃項目
l 面向立法的高質量智能輔助體系構建，國家重點研發計劃課題
l 面向複雜生物網絡的多特征大模體識别方法研究，江蘇省自然科學基金面上項目
l 基于移動數據庫系統的企業移動管理技術研究與開發，國家863
l 面向蛋白質結構預測的智能可理解性技術的研究，江蘇省自然科學基金面上項目
l 基于語義網格的信息集成平台技術的研究，江蘇省“十五”高科技項目
l [1]Jiacong Mi, Yi Zu, Zhuoyuan Wang, Jieyue He，ACDNet: Attention-guided Collaborative Decision Network for effective medication recommendation，Journal of Biomedical Informatics，Volume 149, January 2024.
l [2]Hua Pu, Jiacong Mi, Shan Lu, Jieyue He,RoKEPG: RoBERTa and Knowledge Enhancement for Prescription Generation of Traditional Chinese Medicine,BIBM 2023,12.
l [3]Yi Zu, Jiacong Mi, Lingning Song, Shan Lu and Jieyue He,Finformer: A Static-dynamic Spatiotemporal Framework for Stock Trend Prediction,IEEE BigData,2023,12.
l [4] Zhang, N., Wang, J. & He, J. HARPA: hierarchical attention with relation paths for knowledge graph embedding adversarial learning. Data Min Knowl Disc 37, 521–551 (2023).
l [5]Yu Wu, Xin Xi, Jieyue He, AFGSL: Automatic Feature Generation based on Graph Structure Learning, Knowledge-Based Systems, Volume 238, 2022, 107835, ISSN 0950-7051.
l [6]Jieyue He, Wang J. & Yu Z. Attention based adversarially regularized learning for network embedding, Data Min Knowledge, 2021.10.
l [7]S. Li, W. Wang and J. He, KGAPG: Knowledge-Aware Neural Group Representation Learning for Attentive Prescription Generation of Traditional Chinese Medicine, 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Houston, TX, USA.
l [8]Jieyue He; Xinxing Yang; Zhuo Gong; Ibrahim Zamit. Hybrid Attentional Memory Network for Computational drug repositioning. BMC Bioinformatics 21, 566 (2020)
l [9]Xinxing Yang, lbrahim Zamit, Yu Liu, Jieyue He： Additional Neural Matrix Factorization model for computational drug repositioning, BMC Bioinformatics,20 (1), 2019.
l [10]W. Wu, Z. Yu and J. He, A semi-supervised deep network embedding approach based on the neighborhood structure, Big Data Mining and Analytics, vol. 2, no. 3, pp. 205-216, September 2019.
l [11]Y. Liu, S. Wang,MS Khan,J. He: A novel deep hybrid recommender system based on auto-encoder with neural collaborative filtering. Big Data Mining & Analytics, 2018 , 1 (3) :211-221.
l [12]Bin Shen, Muwei Zhao, Wei Zhong, and Jieyue He: An Improved Method for Completely Uncertain Biological Network Alignment, BioMed Research International, vol. 2015, Article ID 253854, 11 pages, 2015.
l [13]Jieyue He, Chunyan Wang, Kunpu Qiu1 and Wei Zhong: An novel frequent probability pattern mining algorithm based on circuit simulation method in uncertain biological networks. BMC Systems Biology 2014.
l [14]Muwei Zhao，Wei Zhong，Jieyue He* :PBNA: An Improved Probabilistic Biological Network Alignment Method. Tsinghua Science and Technology, 6,2014.
l [15]Jieyue He,Chaojun Li, Baoliu Ye, Wei Zhong:Efficient and accurate greedy search methods for mining functional modules in protein interaction networks. BMC Bioinformatics 2012, 13(Suppl 10):S19.
