梁新彦
梁新彦 （副教授）
研究领域：机器学习、数据挖掘、信号处理及其在微波原子探测方面的应用
电子邮箱：liangxinyan@sxu.edu.cn
个人简介
博士，副教授，山西大学“文瀛青年学者”人才计划（首批）。 2022年6月博士毕业于山西大学计算机科学与技术专业，博士期间曾于2017-2018年赴香港大学从事研究助理的工作。2022年8月加入山西大学大数据科学与产业研究院。 研究方向：多模态机器学习、信号处理及其在微波原子探测方面的应用。 近年来在IEEE TPAMI、IEEE TEVC、IEEE TCSVT、PR、AAAI、IJCAI、ACM MM等国内外重要学术期刊、会议发表论文30余篇。 主持军科委JCJQ重点项目课题、基金委重大项目子课题、基金委青年项目、山西省重大项目课题等多项。 担任Nature Communications、IEEE TEVC、NeurIPS、ICML、ICLR、CVPR等多个国际期刊、会议的审稿人。。
学生培养：
[1] 傅品翰（2022级硕士生）：发表CCF A会议论文3篇，Trans 一区1篇（AAAI-24, IJCAI-24, ACMMM-24, IEEE TCSVT），
[2] 张成龙（2022级硕士生）：发表CCF A会议论文4篇，（AAAI-25*2, IJCAI-24, ACMMM-24），
[3] 姜璋琪（2019级本科生）：发表CCF A会议论文1篇（AAAI2024），保研国防科大
教育教学
《高级语言程序设计》、《离散数学》
招生信息
热忱欢迎同学们报考课题组硕士研究生。课题组科研氛围浓厚、软硬件支撑完备，
将根据每位同学实际情况制定对应的培养方案，从理论研究和工程实践两方面不断提升个人科研能力。
我希望你是这样的：1）有兴趣从事学术研究；2）踏实肯干，积极进取，勤动手脑。3）具备良好的编程能力，英语和数学基础。4）对深度学习，多媒体图像处理课题感兴趣。
有兴趣者可以发邮件垂询送至liangxinyan@sxu.edu.cn，也非常欢迎来山西大学大数据科学与产业研究院当面交流。
同时欢迎本科生加入课题组开展基础科研工作。
科学研究
主要研究方向：
1.多模态机器学习，如面向多模态数据的融合、分类、聚类；跨模态检索等关键技术研究
2.关联数据分析，如关联信息驱动的数据增强关键技术研究
3.多模态融合技术驱动的应用，如声纹增强、识别；图像识别、检索、增强等
科研项目
[1] 国家自然科学基金重大项目，智能原子微波探测理论与方法（T2495250），2025-01 至 2029-12，1500万，子课题负责人
[2] JKW项目，***增强，2024-08 至 2026-08，351万，主持
[3] 国家自然科学基金青年项目，特征关联语义下的多模态表征融合机理与方法研究（62306171），2024-01 至 2026-12，30万，主持
[4] 山西省科技厅, 山西省科技重大专项计划“揭榜挂帅”项目课题, 面向复杂电磁大数据的多模态知识挖掘技术, 2023-01 至 2026-01, 140万元, 在研, 主持
[5] 科技部科技创新2030——“新一代人工智能”重大项目，基于多智能体超图的自主决策、学习理论与动态调控策略研究，2022-01-01至2024-12-31，参与
发表论文：
会议
[1] Bingbing Jiang, Chenglong Zhang, Xinyan Liang, Peng Zhou, Jie Yang, Xingyu Wu, Junyi Guan, Weiping Ding, Weiguo Sheng. Collaborative similarity fusion and consistency recovery for incomplete multi-view clustering. In: Proceedings of the 39th AAAI Conference on Artificial Intelligence (AAAI-25),2025.(CCF A类会议)
[2] Zhongli Wang, Jie Yang, Junyi Guan, Chenglong Zhang, Xinyan Liang, Bingbing Jiang, Weiguo Sheng. Enhanced denesity peak clustering for high-dimensional data. In: Proceedings of the 39th AAAI Conference on Artificial Intelligence (AAAI-25), 2025. (CCF A类会议)
[3] Xinyan Liang, Pinhan Fu, Qian Guo, Keyin Zheng, Yuhua Qian. DC-NAS: Divide-and-Conquer Neural Architecture Search for Multi-Modal Classification. Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI-24), 2024,38(12):13754-13762. Vancouver, Canada, Feb. 20-27, 2024 (CCF A类会议)
[4] Zhangqi Jiang, Tingjin Luo, Xinyan Liang. Deep Incomplete Multi-View Learning Network with Insufficient Label Information. Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI-24), 2024,38(11): 12919-12927. Vancouver, Canada, Feb. 20-27, 2024 (CCF A类会议)
[5] Pinhan Fu, Xinyan Liang, Tingjin Luo, Qian Guo, Yayu Zhang, Yuhua Qian. Core-Structures-Guided Multi-Modal Classification Neural Architecture Search, The 33rd International Joint Conference on Artificial Intelligence (IJCAI-24) .
[6] Chenglong Zhang, Yang Fang, Xinyan Liang, Han Zhang, Peng Zhou, Xingyu Wu, Jie Yang, Bingbing Jiang, Weiguo Sheng. Efficient Multi-view Unsupervised Feature Selection with Adaptive Structure Learning and Inference. The 33rd International Joint Conference on Artificial Intelligence (IJCAI-24).
[7] Qian Guo, Xinyan Liang, Yuhua Qian, Zhihua Cui, Jie Wen. A progressive skip reasoning fusion method for multi-modal classification. The 32nd ACM MULTIMEDIA 2024 (ACM MM-24), 2024. Melbourne, Australia, 28 October-1 November, 2024. (CCF A类会议, Oral 录用率3.97%)
[8] Pinhan Fu, Xinyan Liang, Yuhua Qian, Qian Guo, Zhifang Wei, Wen Li. CoMO-NAS: Core-structures-guided multi-objective neural architecture search for multi-modal classification. The 32nd ACM MULTIMEDIA 2024 (ACM MM-24), 2024. Melbourne, Australia, 28 October-1 November, 2024. (CCF A类会议)
[9] Chenglong Zhang, Xinyan Liang, Peng Zhou, Zhaolong Ling, Yingwei Zhang, Xingyu Wu, Weiguo Sheng, Bingbing Jiang. Scalable multi-view unsupervised feature selection with structure learning and fusion. The 32nd ACM MULTIMEDIA 2024 (ACM MM-24), 2024. Melbourne, Australia, 28 October-1 November, 2024. (CCF A类会议)
期刊
[1] Xinyan Liang, Yuhua Qian, Qian Guo, Honghong Cheng, Jiye Liang. AF: An association-based fusion method for multi-modal classification. IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI) , 2022,44(12): 9236-9254. （CCF-A 类, SCI-1区Top）
[2] Xinyan Liang, Qian Guo, Yuhua Qian, Weiping Ding, Qingfu Zhang. Evolutionary deep fusion method and its application in chemical structure recognition. IEEE Transactions on Evolutionary Computation (IEEE TEVC) , 2021,25(5):883-893. （SCI-1区Top）
[3] Pinhan Fu, Xinyan Liang, Yuhua Qian, Qian Guo, Yayu Zhang, Qin Huang. Multi-scale features are effective for multi-modal classification: An architecture search viewpoint. IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2024, DOI: 10.1109/TCSVT.2024.3470996（SCI-1区Top）.
[4] Xinyan Liang, Yuhua Qian, Qian Guo, Keyin Zheng. A Data Representation Method Using Distance Correlation. Frontiers of Computer Science, 2025,19(1):191303. （CCF-B 类）
[5] Yayu Zhang, Yuhua Qian, Guoshuai Ma, Xinyan Liang, Guoqing Liu, Qingfu Zhang, Ke Tang. ESSR: Evolving sparse sharing representation for multi-task learning. IEEE Transactions on Evolutionary Computation (IEEE TEVC) , 2024,28(3):748-762. （SCI-1区Top）.
[6] Yuhua Qian, Xinyan Liang, Qi Wang, Jiye Liang, Bing Liu, Andrzej Skowron, Yiyu Yao, Jianmin Ma, Chuangyin Dang. Local rough set: A solution to rough data analysis in big data. International Journal of Approximate Reasoning (IJAR) , 2018,97:38-63.（CCF-B 类, SCI-2区，共同一作）
[7] Yuhua Qian, Xinyan Liang, Guoping Lin, Qian Guo, Jiye Liang. Local multigranulation decision-theoretic rough sets. International Journal of Approximate Reasoning(IJAR), 2017,82:119-137. （CCF-B 类, SCI-2区）
[8] Qi Wang, Yuhua Qian, Xinyan Liang, Qian Guo, Jiye Liang. Local neighborhood rough set. Knowledge-Based Systems(KBS), 2018,153:53-64. （CCF-C 类, SCI-1区）
[9] Qian Guo, Yuhua Qian, Xinyan Liang. GLRM: Logical pattern mining in the case of inconsistent data distribution based on multigranulation strategy. International Journal of Approximate Reasoning(IJAR), 2022,143:78-101. (CCF-B 类, SCI-2区)
[10] Qian Guo, Yuhua Qian, Xinyan Liang, Yanhong She, Deyu Li, Jiye Liang. Logic could be learned from images. International Journal of Machine Learning and Cybernetics(JMLC), 2021,12:3397–3414. （SCI-2区）
[11] Qian Guo, Yuhua Qian, Xinyan Liang, Junyu Chen, Honghong Cheng. Multi-granulation multi-scale relation network for abstract reasoning. International Journal of Machine Learning and Cybernetics(JMLC), 2022,13:1751–1762. （SCI-2区）
[12] Yan Chen, Qian Guo, Xinyan Liang, Jiang Wang, Yuhua Qian. Environmental sound classification with dilated convolutions. Applied Acoustics, 2019,148:123-132.（SCI-2区）
[13] Bassoma Diallo, Jie Hu, Tianrui Li, Ghufran Ahmad Khan, Xinyan Liang, Hongjun Wang. Auto-attention Mechanism for Multi-view Deep Embedding Clustering. Pattern Recognition (PR), 2023(143):109764.
[14] Qian Liu, Xia Zhang, Xinyan Liang, Yuhua Qian, Shanshan Yao，AWLloss: Speaker Verification Based on the Quality and Difficulty of Speech. IEEE Signal Processing Letters (SPL),2023(30):1337-1341.
[15] 梁新彦, 钱宇华, 郭倩, 黄琴. 多粒度融合驱动的超多视图分类方法. 计算机研究与发展, 2022, 59(8):1653-1667. (CCF-A 类)
[16] 张璐，曹峰，梁新彦, 钱宇华. 基于关联特征传播的跨模态检索. 计算机研究与发展, 2022, 59(9):1993-2002. (CCF-A 类)
专利：
[1] 梁新彦，郭倩，钱宇华，朱哲清，彭甫镕. 一种基于演化计算多视图融合的分子结构图检索方法. 国家发明专利，授权号：ZL202010666319.3，授权时间：2022.5.31
[2] 郭倩，钱宇华，梁新彦. 一种基于逻辑学习的多图检索方法. 国家发明专利，授权号：ZL202110337481.5，授权时间：2022.11.11
社会服务：
Program Committee Member:
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2025
International Conference on Machine Learning (ICML) 2025
International Conference on Learning Representations (ICLR) 2025
Conference on Neural Information Processing Systems (NeurIPS) 2024
AAAI Conference on Artificial Intelligence (AAAI) 2024-2025
ACM International Conference on Multimedia (ACM MM) 2024
International Joint Conference on Artificial Intelligence (IJCAI) 2024
Selected Journal Reviewer:
Nature Communications
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
IEEE Transactions on Image Processing (TIP)
IEEE Transactions on Evolutionary Computation (TEVC)
IEEE Transactions on Neural Networks and Learning Systems (TNNLS)