个人简介

教育经历： 09/2009–10/2013 香港城市大学 博士 09/2005–07/2009 北京林业大学 本科 工作经历： 03/2016–至今 深圳大学 助理教授、特聘副研究员 10/2013–01/2016 香港城市大学 Senior Research Associate 获得荣誉： 深圳市海外高层次人才“孔雀计划”C类人才 深圳大学2019年“荔园优青”培养对象 教学课程： 《模式识别》、《统计学习方法》、《算法设计与分析》、《操作系统》

研究领域

机器学习、模式识别、大数据分析 具体方向： 监督学习与半监督学习 多分类问题与主动学习 模糊系统及粗糙集理论 计算智能与演化计算 大数据及时间空间数据分析

科研项目： 04/2018–03/2020 多标记主动学习的关键问题：多目标优化、不确定性建模与多准则决策 (主持, 中国国家自然科学基金，面上项目61811530324，10万) 01/2018–12/2021 多标记问题的不确定性分析与主动学习方法研究 (主持, 中国国家自然科学基金，面上项目61772344，62万) 01/2018–12/2022 面向大数据机器学习的不确定性建模理论与方法 (参与, 中国国家自然科学基金，重点项目61732011，285万) 01/2018–12/2020 大数据下多实例与多标记机器学习算法与应用 (主持, 深圳大学高端人才科研启动项目，827-000230，270万) 06/2017–05/2019 多标记主动学习的理论建模与算法研究 (主持, 深圳大学青年教师科研启动项目2017060，6万) 01/2015–12/2017 基于分治融合与主动学习的极速学习机方法研究 (主持, 中国国家自然科学基金，青年基金项目61402460，24万)

近期论文

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代表性论文： [24] Dasen Yan, Xinlei Zhou, Xizhao Wang, and Ran Wang*. An off-center technique: Learning a feature transformation to improve the performance of clustering and classification. Information Sciences, 359: 139–152 (2019). (中科院小类1区top) [23] Farhad Pourpanah, Ran Wang*, Chee Peng Lim, Xizhao Wang, Manjeevan Seera, and Choo Jun Tan. An improved fuzzy ARTMAP and Q-Learning agent model for pattern classification. Neurocomputing, 503: 635–651 (2019). (中科院大类2区) [22] Xi-Zhao Wang, Tianlun Zhang, and Ran Wang*. Noniterative deep learning: Incorporating restricted boltzmann machine into multilayer random weight neural networks. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 49(7): 1299—1308 (2019). (中科院大类2区) [21] Yan Lyu*, Chi-Yin Chow, Ran Wang, and Victor C.S. Lee. iMCRec: A multi-criteria framework for personalized point-of-interest recommendations. Information Sciences, 483:294–312 (2019). (中科院小类1区top) [20] Ran Wang*, Haoran Xie, Jiqiang Feng, Fu Lee Wang, and Chen Xu. Multi-criteria decision making based architecture selection for single-hidden layer feedforward neural networks. International Journal of Machine Learning and Cybernetics, 10(4): 65–666 (2019). (中科院大类3区) [19] Yuheng Jia, Sam Kwong*, Wenhui Wu, Ran Wang, and Wei Gao. Sparse bayesian learning based kernel poisson regression. IEEE Transactions on Cybernetics, 49(1): 56–68 (2019). (中科院大类1区top) [18] Zhiqi Huang, Ran Wang*, Hong Zhu, and Jie Zhu. Discovering the impact of hidden layer parameters on non-iterative training of feed-forward neural networks. Soft Computing, 22: 3495–3506 (2018). (中科院大类3区) [17] Ran Wang*, Chi-Yin Chow, Yan Lyu, Victor C. S. Lee, Sam Kwong, Yanhua Li, and JiaZeng. TaxiRec: Recommending road clusters to taxi drivers using ranking-based extreme learning machines. IEEE Transactions on Knowledge and Data Engineering, 30(3): 585—598 (2018). (中科院大类2区, CCF: A类) [16] Xi-Zhao Wang, Ran Wang*, and Chen Xu. Discovering the relationship between generalization and uncertainty by incorporating complexity of classification. IEEE Transaction son Cybernetics, 48(2): 703—715 (2018). (中科院大类1区top) [15] Ran Wang, Xi-Zhao Wang*, Sam Kwong, and Chen Xu. Incorporating diversity and informativeness in multiple-instance active learning. IEEE Transactions on Fuzzy Systems, 25(6): 1460—1475 (2017). (中科院大类1区top) [14] Ran Wang, Chi-Yin Chow, and Sam Kwong*. Ambiguity based multiclass active learning. IEEE Transactions on Fuzzy Systems, 24(1): 242—248 (2016). (中科院大类1区top) [13] Ran Wang, Sam Kwong*, Xi-Zhao Wang, and Qingshan Jiang. Segment based decision tree induction with continuous valued attributes. IEEE Transactions on Cybernetics, 45(7):1262–1275 (2015). (中科院大类1区top) [12] Ran Wang, Yu-Lin He*, Chi-Yin Chow, Fang-Fang Ou, and Jian Zhang. Learning ELM-tree from big data based on uncertainty reduction. Fuzzy Sets and Systems, 258: 79–100 (2015). (中科院大类1区top) [11] Ran Wang, and Sam Kwong*. Active learning with multi-criteria decision making systems. Pattern Recognition, 47(9): 3106–3119 (2014). (中科院大类2区) [10] Ran Wang, Degang Chen, and Sam Kwong*. Fuzzy rough set based active learning. IEEE Transactions on Fuzzy Systems, 22(6): 1699–1704 (2014). (中科院大类1区top) [9] Xi-Zhao Wang, Ran Wang*, Hui-Min Feng, and Hua-Chao Wang. A new approach to classifier fusion based on upper integral. IEEE Transactions on Cybernetics, 44(5):620–635 (2014). (中科院大类1区top) [8] Yu-Lin He*, Ran Wang, Sam Kwong, and Xi-Zhao Wang. Bayesian classifiers basedon probability density estimation and their applications to simultaneous fault diagnosis. Information Sciences, 259: 252–268 (2014). (中科院小类1区top) [7] Hao Gao, Sam Kwong*, Baojie Fan, and Ran Wang. A hybrid particle-swarm tabusearch algorithm for solving job shop scheduling problems. IEEE Transactions on Industrial Electronics, 10(4): 2044–2054 (2014). (中科院大类1区top) [6] Ke Li, Qingfu Zhang, Sam Kwong*, Miqing Li, and Ran Wang. Stable matching based selection in evolutionary multiobjective optimization. IEEE Transactions on Evolutionary Computation, 18(6): 909–923 (2014). (中科院大类1区top) [5] Ran Wang*, Sam Kwong, and Debby Dan Wang. An analysis of ELM approximate error based on random weight matrix. International Journal of Uncertainty, Fuzziness, and Knowledge-Based Systems, 21(suppl.2): 1–12 (2013). (中科院大类4区) [4] Ran Wang, Sam Kwong*, Degang Chen, and Jingjing Cao. A vector-valued support vector machine model for multiclass problem. Information Sciences, 235: 174–194 (2013). (中科院小类1区top) [3] Ke Li, Sam Kwong*, Ran Wang, Kit-Sang Tang, and Kim-Fung Man. Learning paradigm based on jumping genes: A general framework for enhancing exploration in evolutionary multiobjective optimization. Information Sciences, 226: 1–22 (2013). (中科院小类1区top) [2] Ran Wang*, Sam Kwong, and Xizhao Wang. A study on random weights between input and hidden layers in extreme learning machine. Soft Computing, 16(9): 1465–1475 (2012). (中科院大类3区) [1] Ran Wang, Sam Kwong*, and Degang Chen. Inconsistency-based active learning for support vector machines. Pattern Recognition, 45(10): 3751–3767 (2012). (中科院大类2区)