二、科研项目
[1]国家自然科学基金项目,多模态教育认知大模型驱动的个性化学习研究,62507001,2026.01-2028.12,30万,主持
[2]北京市自然科学基金项目,融合多模态人机交互与大语言模型的自适应学习研究,4254091,2025.01-2026.12,20万,主持
[3]北京市研究型病房卓越临床研究计划项目课题,冠心病血瘀证中医四诊客观化研究,BRWEP2024Z014170101,2026.04-2027.10,30万,主持
[4]国家电网公司总部科技项目课题,面向电力系统的双飞翼垂直起降无人机新机型适航与高速巡航光电成像关键技术及示范应用,5500-202322539A-3-2-ZN,2023.10-2025.12,190万,主持
[5]北京市博士后科研项目,多模态融合的学习者认知过程建模研究,2023-ZZ-97,2023.05-2024.11,4万,主持
[6]软件开发环境国家重点实验室课题,面向员工的代码智能修复与编程能力评估方法研究,SKLSDE-2022KF-10,2022.11-2023.10,5万,主持
三、代表性研究成果
[1] Niu S, He J, Liang Y*, et al. CLMER: A framework for contrastive learning-based multimodal emotion recognition[J]. IEEE Transactions on Neural Networks and Learning Systems, 2026.(JCR Q1,CCF B类期刊)
[2]Peng T,Liang Y*, Wu W, et al. CLGT: A graph transformer for student performance prediction in collaborative learning[C]//Proceedings of the AAAI Conference on Artificial Intelligence, 2023, 37(13): 15947-15954.(CCF A类会议)
[3]Cao R, He J,Liang Y*, et al. CLDAE: A twostage EEG-based emotion recognition framework combining contrastive learning and dual-attention encoder[J]. IEEE Journal of Biomedical and Health Informatics, 2026,30(9):7523-7535.(JCR Q1,CCF C类期刊)
[4]Wang Z, He J,Liang Y*, et al. Milmer:Aframework for multiple instance learning based multimodal emotion recognition[J]. Neurocomputing, 2026, 699: 134368.(JCR Q1,CCF C类期刊)
[5]Liang Y, Zhang C, An S, et al. FetchEEG: A hybrid approach combining feature extraction and temporal-channel joint attention for EEG-based emotion classification[J]. Journal of Neural Engineering, 2024,21(3): 036011.
[6]Liang Y, Wang Y, Xie X, et al. Distribution bias embedding tuning of vision transformer for remote sensing object detection[J]. Scientific Reports, 2025,15(1): 45257.(JCR Q1)
[7]Liang Y, Peng T, Pu Y, et al. HELP-DKT: An interpretable cognitive model of how students learn programming based on deep knowledge tracing[J]. Scientific Reports, 2022,12(1): 4012.(JCR Q1)
[8]Liang Y, Yang L, Sun S, et al. YOLOv11-RAH: A recurrent attention-enhanced edge intelligence network for UAV-based power transmission line insulator inspection[J]. International Journal of Intelligent Networks, 2025, 6: 244-252.
[9]梁堉,马佳妍,胡晰远,等.基于大模型数据增强的多粒度特征融合谣言检测[J].计算机工程, 2026.(中文核心,CCF T2类期刊)
[10]胡晰远,李亚芳,梁堉主编.开源鸿蒙Python程序开发实战[M].电子工业出版社,2026.(数字教材)
全部论著详见:https://scholar.google.com/citations?user=Ky7Ekn0AAAAJ