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张仲荣，男，汉族，工学博士，教授。中国现场统计研究会大数据统计分会第二届常务委员、第一、第二届理事；中国优选法统筹法与经济数学研究会数据科学分会第二届理事；甘肃省人工智能学会入库专家；教育部学位中心硕、博士学位论文抽检评审专家；甘肃省社会科普研究会数据科学与人工智能科普特聘专家。在国内外重要学术期刊上发表论文70余篇，其中SCI论文26篇，EI论文7篇。个人H指数为9，论文总被数累计316次，在Journal of Hydrology、Urban Climate和Scientific Reports顶级期刊累计发表8次。 应用统计专业硕士点初创人，硕点主任。研究方向：基于数学、统计的人工智能算法设计及应用研究。聚焦于孪生数字底座的时空智能（孪生智能）算法及应用研究。研究组追踪元学习、量子计算、黎曼几何优化、字典学习、张量学习，人工智能算法不确定性分析、可解释性人工智能、模型选择等人工智能前沿算法与时空预测的结合.立足于时间序列、时空序列理论，考虑非线性特征、参数智能优化理论，建立组合时空模型、混合模型、集成模型、深度学习模型问题，提升模型精度、鲁棒性和自适应性的问题. 孪生智能是新质生产力、数字经济、低空经济的前沿热点，是数字孪生的智能化提升。2024年获得数转智改主题项目：“水利孪生数字底座时空预测预警”项目获甘肃省科技厅重点研发计划支持；依托甘肃省计算中心申报的“量超融合”算力服务平台关键技术研发与应用项目获中央引导地方科技发展资金支持。获得国网甘肃电力委托研发项目“基于全景监造数字底座的生产进度异常时空智能预测系统开发及响应激励机制研究”。 应用统计专业硕士点数据科学与时空智能预测预警方向学术带头人。2023年面对核验评估重任，二度出任硕士点主任，带头撰写了应用统计专业学 位研究生核验评估材料，硕士点最终赢得到教育指导委员会专家全票通过核验评估的结论。 已经培养毕业硕士生45人，在读研究生18人，联合培养3人，其中学术型硕士3人，专业型硕士15人。主要培养数学类学术型研究生和应用统计专业学位研究生。23级起，团队研究生深刻理解“人工智能就是统计”的科学论述，走出了读研“混文凭”认知。树立了读用“论文、实践、项目、专利、竞赛大奖”充实的、有内涵、有底气的研究生的理念。2025年来团队成果进入收获期，在读研究生人人SCI论文在手，论文成功发表的激情强化了团队的科研干劲，高质量的成果给同学们带来自信和高质量就业的底气，增强了团队凝聚力，团队科研进入的良性循环。主持和参与各类科研项目20余项，代表性项目有：[1]省级生态文明建设重点研发专项：24YFFA055，基于水利孪生数字底座的智能预测预警及典型应用研究，在研，主持。[2]中央引导地方科技发展资金项目“量超融合”算力服务平台关键技术研发与应用项目，25ZYJA039，在研，参与。[3]国网甘肃电力委托研发项目“基于全景监造数字底座的生产进度异常时空智能预测系统开发及响应激励机制研究”，在研，主持。[4]国家自然科学基金重点项目，41930101，面向全自动地图综合的空间相似关系理论，2020-01至2024-12，在研，参与。直接经费303万元，第二参与人（除主持人外是第一参与人）。[5]甘肃省科技计划资助（20CX9JA128)：甘肃干旱区农村饮水供水保障提升研究及产品开发，2020-01 至 2022-12，结题，主持.[6] 甘肃省自然科学基金，1610RJZA057，基于统计理论和人工智能的民勤绿洲地下水埋深时空预测研究，2016-07至2018-06，结题，主持。代表性论文： [1] Zhongrong Zhang*, Xuan Yang, Hao Li, Weide Li, Haowen Yan, Fei Shi. Application of a novel hybrid method for spatiotemporal data imputation: a case study of the Minqin County groundwater level[J]. Journal of Hydrology, 2017, 553: 384-397. DOI: 10.1016/j.jhydrol.2017.07.053.[2] Xingyu Yang, Zhongrong Zhang*. An attention-based domain spatial-temporal meta-learning (ADST-ML) approach for PM2.5 concentration dynamics prediction[J]. Urban Climate, 2023, 47: 101363. DOI: 10.1016/j.uclim.2022.101363.[3] Xingyu Yang, Zhongrong Zhang*. A CNN-LSTM model based on a meta-learning algorithm to predict groundwater level in the middle and lower reaches of the Heihe River, China[J]. Water, 2022, 14(15): 2377. DOI: 10.3390/w14152377.[4] Huiqin Xu†, Zhongrong Zhang†, Yin Gao, Haizhong Liu, Feng Xie, Jun Li*. Adaptive bilateral texture filter for image smoothing[J]. Frontiers in Neurorobotics, 2022, 16: 729924. DOI: 10.3389/fnbot.2022.729924.[5] Zhongrong Zhang, Yijia Liu, Haizhong Liu, Aihong Hao, Zhongwei Zhang. The impact of lockdown on nitrogen dioxide (NO2) over Central Asian countries during the COVID-19 pandemic[J]. Environmental Science and Pollution Research, 2022, 29(13): 18923-18931. DOI: 10.1007/s11356-021-17140-y.[6] Xiaoya Chang, Zhongrong Zhang*, Jianguo Sun, Kang Lin, Ping'an Song. Breast cancer image classification based on H&E staining using a causal attention graph neural network model[J]. Medical & Biological Engineering & Computing, 2025, 63(7): 1965-1979. DOI: 10.1007/s11517-025-03303-3.[7] Zhenghao Sui, Zhongrong Zhang*, Ruiqi Wang, Kang Li, Yuyuan Pan. Quantum-transformer integration in H2STGCN: a novel approach for spatiotemporal pattern modeling[J]. Applied Intelligence, 2025, 55(16): 1079. DOI: 10.1007/s10489-025-06976-3.[8] Zhongrong Zhang*, Junyan Sun, Yulin Shen*, et al. WD-HRNN-BiGRU: a novel spatiotemporal sequence multi-value prediction model[J]. Water Resources Management, 2026, 40(4): 169. DOI: 10.1007/s11269-026-04541-2.[9] Wen Yang, Zhongrong Zhang*, Yunyun Zhang, et al. LPT-Former: local-point transformer for 3D point cloud completion[J]. Journal of Visual Communication and Image Representation, 2026, 117: 104749. DOI: 10.1016/j.jvcir.2026.104749.[10] Yunyun Zhang, Zhongrong Zhang*, Yulin Shen, et al. High-fidelity point cloud generation via multi-scale attentive feature fusion with graphSAGE and transformer[J]. The Visual Computer, 2026, 42(4): 187. DOI: 10.1007/s00371-026-04389-y.[11] Jing Bai, Wen Nie*, Zhongrong Zhang, et al. An optimized deep learning model with error correction for forecasting particulate matter 2.5 concentrations near tailings ponds[J]. International Journal of Environmental Science and Technology, 2026, 23(4): 315. DOI: 10.1007/s13762-026-07067-7.[12] Ruiqi Wang, Zhongrong Zhang*, Yulin Shen*, et al. Hqsan: a hybrid quantum self-attention network for remote sensing image scene classification[J]. The Journal of Supercomputing, 2025, 81(15): 1422. DOI: 10.1007/s11227-025-07922-3.[13] Xiangxiang Zheng, Zhongrong Zhang*, Xiaona Zhang, Nengzhi Jin*, Yunyun Zhang. Ricci-GraphDTA: a graph neural network integrating discrete Ricci curvature for drug-target affinity prediction[J]. Journal of Molecular Graphics and Modelling, 2026, 142: 109170. DOI: 10.1016/j.jmgm.2025.109170.[14] Zeyu Duan, Zhongrong Zhang*, Jisheng Li*, et al. Spatiotemporal time series graph modeling method research based on the fusion of time-frequency domain analysis and deep learning: a case study of groundwater depth prediction in the Heihe River Basin, China[J]. Journal of Hydrology: Regional Studies, 2026, 64: 103217. DOI: 10.1016/j.ejrh.2026.103217.[15] Wenyu Zhang, Zhongrong Zhang*, Nengzhi Jin*, et al. A hybrid deep learning-based framework for rolling bearing fault diagnosis: multi-resolution feature extraction and enhanced adaptive nonlinear mapping[J]. Advances in Engineering Software, 2026, 218: 104184. DOI: 10.1016/j.advengsoft.2026.104184.[16] Yang Zhu, Hong Li, Zhenhao Wang, et al. Optimal evacuation route planning of urban personnel at different risk levels of flood disasters based on the improved 3D Dijkstra's algorithm[J]. Sustainability, 2022, 14(16): 10250. DOI: 10.3390/su141610250.[17] Yang Zhu, Yijun Gao, Zhenhao Wang, Guansen Cao, Renjie Wang, Song Lu, Wei Li, Wen Nie*, Zhongrong Zhang*. A tailings dam long-term deformation prediction method based on empirical mode decomposition and LSTM model combined with attention mechanism[J]. Water, 2022, 14(8): 1229. DOI: 10.3390/w14081229.[18] Zhongrong Zhang, Yiliao Song, Feng Liu, Jinpeng Liu. Daily average wind power interval forecasts based on an optimal adaptive-network-based fuzzy inference system and singular spectrum analysis[J]. Sustainability, 2016, 8(2): 125. DOI: 10.3390/su8020125.[19] Feiyu Tong, Zhongrong Zhang*, Nengzhi Jin*, Haobo Liang, Kehan Zhu. From destination image to regional embeddings: a multi-scale framework for cross-city tourism recommendation[J]. Current Issues in Tourism, 2026, published online 24 June 2026. DOI: 10.1080/13683500.2026.2689449.[20] Yubin Qian, Zhongrong Zhang*, Qiang Bie*, Jinjun Li, Kang Lin. Landslide identification method based on enhanced DeepLabv3+ architecture: joint optimization of bottleneck attention and dual-module graph convolution[J]. Applied Intelligence, 2026, 56(13): 385. DOI: 10.1007/s10489-026-07432-6.[21] Zhongrong Zhang*, Yubin Qian†, Qiang Bie*. HMA-YOLO: hypergraph-guided multi-scale feature interaction for remote sensing object detection[J]. Digital Signal Processing, 2026, 185: 106549. DOI: 10.1016/j.dsp.2026.106549.[22] Zhongrong Zhang*, Yunyun Zhang†, Nengzhi Jin*, et al. Topology-aware point cloud generation via graph-induced simplicial diffusion and multi-scale GraphSAGE decoding[J]. Applied Intelligence, 2026, online first.[23] Jing Bai, Mudassir Mehmood, Zhongrong Zhang, Wen Nie*, Zhuangen Qin, Yixian Yao. Landslide risk early warning in open-pit mines: an integrated framework combining fuzzy comprehensive evaluation and intelligent prediction[J]. International Journal of Environmental Research, 2026, 20(6): 304. DOI: 10.1007/s41742-026-01221-2.[24] Junyan Sun, Zhongrong Zhang*, Yulin Shen, Kang Lin, Zeyu Duan, Jisheng Li. STA-HRNN-BiGRU: a spatiotemporal sequence multivariate forecasting model integrating spatiotemporal information[J]. Applied Intelligence, 2026, 56(8): 305. DOI: 10.1007/s10489-026-07325-8.[25] 张仲荣,王亚领,闫浩文. 一种时空混合插值算法及其应用[J]. 测绘科学, 2016, 41(12): 265-269, 306.代表性论著：[1] 张仲荣,闫浩文. 基于混合模型的地下水埋深时空预测研究---以民勤绿洲为例[M].北京，科学出版社， 2019年5月.[2] 常迎香,栗永安,李秦,刘海忠,张仲荣,刘旭. 高等数学（共上、下两册）[M].北京，科学出版社, 2009年8月.代表性计算机软件著作权登记证书：1.物种生态适宜区智能预测系统V1.0.2025SR0790300.2025年05月15日.2.信息技术服务咨询管理系统V1.0.2022SR1440890.2022年11月01日.3.地质灾害治理一站式服务系统V1.0.2022SR1440872.2022年11月01日.4.量子计算信息获取处理系统V1.0.2023SR0961516.2023年08月21日.5.智能化预测克里金插值计算软件V1.0.2023SR1807339.2023年12月29日.6.黎曼残差图神经网络动态预计系统V1.0.2024SR1128489.2024年08月06日.7.神经网络数值运算系统V1.0.2024SR1236063.2024年08月23日.8.基于机器学习的物种分布多情景预测软件V1.0.2025SR0795968.2025年05月15日.9.长短时记忆神经网络交通流量预测软件V1.0.2025SR0845929.2025年05月22日.10.基于数字孪生的流域供水优化配置系统V1.0.2025SR1028473.2025年06月17日.校园网教师个人主页： http://faculty.lzjtu.edu.cn/zhangzhongrong/zh_CN/index.htm联系电话：zzr1969（微信）。