个人简介

• 教育背景

  Computer Science, Hong Kong Polytechnic University, Ph. D

  Electrical and Computer Engineering, Duke University, Master

  Electronic Engineering, UESTC, Bachelor

  
  

  Looking for highly motivated students to work on topics including but not limited to medical information systems, Bayesian methods, reinforcement learning, deep learning, feature learning, and data analytics.

• 研究方向

  Machine Learning, Data Mining, Information Systems, Bayesian Learning

• 讲授课程

  机器学习与商业分析 Machine Learning and Business Analytics, for undergrads

  人工智能与机器学习 AI and Machine Learning, for postgrads

  商务智能案例讨论 Business Intelligence Case Discussion, for undergrad

  商务智能与决策 Business Intelligence and Decision Making, for MBA

• 研究成果

  项目：

  主持国家自然科学基金青年项目、省社科规划项目各一项

  
  

  论文：

  [1]Tian-Hao Li, Zhi-Shun Wang,Wei Lu*,Qian Zhang, Deng-Feng Li,"Electronic Health Records based Reinforcement Learning for Treatment Optimizing", Information Systems, 2022. (SCI, Rank A; Corresponding author. The first author is my co-supervised Ph.D. student)

  [2]Wei Luand Yan Hu, "Multi-type Feature Mining and Fusion Model for Temporal Prediction,"2020 International Joint Conference on Neural Networks (IJCNN), Glasgow, United Kingdom, 2020, pp. 1-6.

  [3]Jiang Wenhao, Ma Lin, &Wei Lu, "Recurrent Nested Model for Sequence Generation".Proceedings of the AAAI Conference on Artificial Intelligence,2020, 34(7): 11117-11124. (CCF A)

  [4]Shen, Xiao, Quanyu Dai, Fu-lai Chung,Wei Lu, and Kup-Sze Choi. 2020. “Adversarial Deep Network Embedding for Cross-Network Node Classification.”Proceedings of the AAAI Conference on Artificial Intelligence,2020, 34 (3): 2991–99.(CCF A)

  [5]Wei Lu, Fu-lai Chung, Wenhao Jiang, Martin Ester, Wei Liu, “A Deep Bayesian Tensor Based System for Video Recommendation”,ACM Transactions on Information Systems （TOIS）, 2019. (SCI, Rank A)

  [6]Wei Lu, Fu-lai Chung, “A Deep Graphical Model for Layered Knowledge Transfer”,International Conference on Pattern Recognition(ICPR), 2018.

  [7]Wei Lu, Fu-lai Chung, Kunfeng Lai, Liang Zhang,“Recommender system based on scarce information mining [J]. Neural Networks, the Official Journal of the International Neural Network Society, 2017. (SCI, JCR Q1)

  [8]Wei Lu, Fu-lai Chung, Kunfeng Lai, “Scarce Feature Topic Mining for Video Recommendation”,Proceedings of the 25th ACM International Conference on Information and Knowledge Management(CIKM), 2016. (CCF B)

  [9]Wei Lu, Fu-lai Chung, “Computational Creativity based Video Recommendation”,Proceedings of the 39^thInternational ACM SIGIR Conference on Research and Development in Information Retrieval, 2016. (CCF A)

  [10]Wei Lu, Fu-lai Chung,“Auxiliary Information based Hierarchical Topic Model: Mining Biased Short text”, submitted.

  [11]Xiaoqian Yi, Xiao Shen,Wei Lu, Tung Shan Chan, and Fu Lai Chung. “Persuasion Driven Influence Analysis in Online Social Networks”,International Joint Conference onNeuralNetworks (IJCNN), 2016.

  [12]Wei Lu, Fu-lai Chung, “Deep Bayesian Tensor for Recommender System”,Proceedings of the ECMLPKDD 2015 Doctoral Consortium, 2015.

  [13]Anna Tyler,Wei Lu, Justin Hendrick,etc., “CAPE: An R package for Combined Analysis of Pleiotropy and Epistasis”,PLoS Computational Biology9.10, 2013.

• 社会兼职及荣誉

  2022年研究生教学质量优秀奖

  2021年度学院教学新人奖

  2019研究生教学优绩奖

  2019年度学院研究新人奖

  2018年度学院研究新人提名奖

  2021 IEEE International Conference on Data Science and Systems, Program Vice Chair，outstanding leadership award

  担任IEEE Transactions on Cybernetics, AAAI, ICDM, SDM, ICPR等国际期刊审稿人和会议PC member