最终学历：研究生
研究方向：数据挖掘与机器学习
电子邮箱：bailiang@sxu.edu.cn
最终学位：博士
研究生导师：博士生导师
联系电话：0351-7010566
白亮，山西大学智能信息处理研究所所长，教授，博士生导师，国家优秀青年基金获得者。2009-2012年在山西大学计算机与信息技术学院攻读博士学位，2014年-2016年在中科院计算所网络数据科学与技术重点实验室进行博士后研究工作。主要研究方向为机器学习，重点关注无/自监督学习基础理论与方法以及在医疗场景中的应用，相关研究成果发表在AI、IEEE TPAMI、IEEE TKDE、ICML、KDD、AAAI等国际重要学术期刊和会议，主持了科技部新一代人工智能重大项目课题、国家自然科学基金优青、面上等项目，获得了包括中国人工智能学会优秀博士论文奖、山西省科学技术奖（自然科学类）一等奖等奖励。
1. 数据科学与大数据计算，国家优秀青年科学基金，2021-01至2023-12，主持
2. 医疗会诊智能体的自组织与自学习，科技部科技创新2030-“新一代人工智能”重大项目课题，2021-12至2024-11，主持
3. 自监督聚类基础理论与算法研究，国家自然科学基金面上项目, 2023-01至2026-12，主持
4. 带参照物的聚类集成方法研究，国家自然科学基金面上项目, 2018-01至2021-12，主持
5. 符号数据的聚类有效性分析与优化算法研究, 国家自然科学基金青年项目, 2014-01至2016-12，主持
[1] Liang Bai, Minxue Qi, Jiye Liang, Spectral clustering with robust self-learning constraints, Artificial Intelligence, 2023, 320: 103924
[2] Liang Bai, Jiye Liang, Yuxiao Zhao, Self-constrained Spectral Clustering, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023, 45(4): 5126-5138
[3] Liang Bai, Jiye Liang, K-relations-based consensus clustering with entropy-norm regularizers, IEEE Transactions on Neural Networks and Learning Systems, 2023
[4] Wentao Cui, Liang Bai, Contrastive learning with the feature reconstruction amplifier, In Proceedings of the 37th AAAI Conference on Artificial Intelligence, 2023
[5] Qing Yin, Linda Zhong, Yunya Song, Liang Bai, Zhihua Wang, Chen Li, Yida Xu, Xian Yang, A decision support system in precision medicine: contrastive multimodal learning for patient stratification, Annals of Operations Research, 2023
[6] Qin Yue, Jiye Liang, Junbiao Cui, Liang Bai, Dual bidirectional graph convolutional networks for zero-shot node classification, 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2022
[7] Liang Bai, Jiye Liang, Fuyuan Cao, Semi-supervised clustering with constraints of different types from multiple information sources, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021, 43(9): 3247-3258
[8] Liang Bai, Jiye Liang, Sparse subspace clustering with entropy-norm, Thirty-seventh International Conference on Machine Learning, 119:561-568, 2020
[9] Liang Bai, Jiye Liang, A three-level optimization model for nonlinearly separable clustering, In Proceedings of the 34th AAAI Conf. on Artificial Intelligence, 2020
[10] Liang Bai, Jiye Liang, Hangyuan Du, Yike Guo. An information-theoretical framework for cluster ensemble, IEEE Transactions on Knowledge and Data Engineering, 2019, 31(8):1464-1477.
[11] Liang Bai, Jiye Liang, Yike Guo. An ensemble clusterer of multiple fuzzy k-means clusterings to recognize arbitrarily shaped clusters, IEEE Transactions on Fuzzy Systems, 2018, 26(6): 3524-3533.
[12] Liang Bai, Xueqi Cheng, Jiye Liang, Huawei Shen. An optimization model for clustering categorical data streams with drifting concepts, IEEE Transactions on Knowledge and Data Engineering, 2016, 28(11):2871-2883.
[13] Liang Bai, Jiye Liang. Cluster validity functions for categorical data: a solution-space perspective, Data Mining and Knowledge Discovery, 2015, 29(6):1560-1597.
[14] Liang Bai, Jiye Liang, Chuangyin Dang, Fuyuan Cao. The impact of cluster representatives on the convergence of the K-Modes type clustering, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013, 35(6):1509-1522.
[15] Jiye Liang, Liang Bai, Chuangyin Dang, Fuyuan Cao. The k-means-type algorithms versus imbalanced data distributions, IEEE Transactions on Fuzzy Systems, 2012, 20(4):728-745.