白亮，民盟盟员，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。主要研究方向为机器学习与数据挖掘，其中包括图学习与聚类分析、机器学习基础理论与智慧医疗应用等，相关研究成果发表在AIJ、IEEE TPAMI、IEEE TKDE、DMKD、ICML、KDD、AAAI等国际权威学术期刊和会议等，博士论文获得了中国人工智能学会优秀博士论文奖。承担了国家自然科学基金“重点”/“优青”项目、科技部新一代人工智能重大项目课题等。2次作为主要完成人获得了山西省科学技术奖（自然科学类）一等奖奖励。
[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.
[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
