入选国家级高层次人才计划，CCF开源发展委员会执委委员，中国医疗保健国际交流促进会健康数据与数字医学分会委员。2018.6—2019.1公派到UIUC的Laxmikant V. Kale教授课题组访学。长期从事大模型、图计算和数值反应堆的国产适配等；近几年在智能优化领域的研究成果在能源、材料、气象等多个学科领域进行成果应用和落地。在国内外高水平期刊和会议IEEE TSE、IEEE FS、PPoPP、SC、DAC、AAAI、IJCAI、CPC、中国科学：信息科学、计算机学报和软件学报等发表学术论文100余篇；授权专利50余项；专著2部。获得SC 23（CCF A推荐）最佳论文和最佳学生论文双提名，KSEM 22最佳学生论文。获得北京市技术发明等多个省部级奖、中核集团技术发明一等奖（2次）和二等奖（1次）、国家电网有限公司科技进步三等奖等。

先后承担了自然科学基金、863子课题、国家重点研发计划课题、中国科学院战略性先导A科技专项课题、国家电网基础性/前瞻性项目（院士合作项目），国家电网公司总部科技项目等。

[1] Shunde Li, Zhijie Pan, Ningming Nie, Jue Wang*，He Bai, Genshen Chu, Yan Zeng, Xinfu He, Yangang Wang, Changjun Hu, Xuebin Chi, MISA-AKMC :Achieve Kinetic Monte Carlo Simulation of 20 Quadrillion Atoms on GPU Clusters, In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis; SC ’25,（CCF A 推荐）

[2] Haisha Zhao, San Li, Jiaheng Wang, Chunbao Zhou, Jue Wang*, Zhikuang Xin, Shunde Li, Zhiqiang Liang, Zhijie Pan, Fang Liu, Yan Zeng, Yangang Wang, Xuebin Chi, Acc-SpMM: Accelerating General-purpose Sparse Matrix-Matrix Multiplication with GPU Tensor Cores, In Proceedings of the 30th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming; PPoPP’ 25, (CCF A推荐)

[3] Junyu Gu, Shunde Li, Rongqiang Cao, Jue Wang*, Zijian Wang, Zhiqiang Liang, Fang Liu, Shigang Li, Chunbao Zhou, Yangang Wang, Xuebin Chi, ParGNN: A Scalable Graph Neural Network Training Framework on multi-GPUs, In Proceedings of the 62st ACM/IEEE Design Automation Conference; DAC’ 25, (CCF A推荐)

[4] Meng Wan, Rongqiang Cao, Yanghao Li, Jue Wang*, Zijian Wang, Qi Su, Lei Qiu, Peng Shi, Yangang Wang, and Chong Li. SEP: A General Lossless Compression Framework with Semantics Enhancement and Multi-Stream Pipelines, In Proceedings of the 24st International Joint Conference on Artificial Intelligence; IJCAI 25, (CCF A推荐)

[5] Meng Wan, Tiantian Liu, Yuxuan Bi, Jue Wang*, Hui Cui, Rongqiang Cao, Jiaxiang Wang, Peng Shi, Ningming Nie, and Yangang Wang. MCloudNet: An Ultra-Short-Term Photovoltaic Power Forecasting Framework With Multi-Layer Cloud Coverage, In Proceedings of the 24st International Joint Conference on Artificial Intelligence; IJCAI 25, (CCF A推荐)

[6] Shunde Li, Junyu Gu, Jue Wang*, Tiechui Yao, Zhiqiang Liang, Yumeng Shi, Shigang Li, Weiting Xi, Shushen Li, Chunbao Zhou, Yangang Wang, Xuebin Chi, POSTER: ParGNN: Efficient Training for Large-Scale Graph Neural Network on GPU Clusters, In Proceedings of the 29th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming; PPoPP’ 24, (CCF A推荐)

[7] Shunde li, Zongguo Wang, Lingkun Bu, Jue Wang*, Zhikuang Xin, Yangang Wang, Yangde Feng, Shigang Li, Peng Shi, Yun Hu, Xuebin Chi. ANT-MOC: Scalable Neutral Particle Transport Using 3D Method of Characteristics on Multi-GPU Systems. In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis; SC ’23,（CCF A 推荐, 最佳论文和最佳学生论文双提名）

[8] Yumeng Shi, Ningming Nie, Shunde Li, Jue Wang*, Kehao Lin, Chunbao Zhou,  Shigang Li, Kehan Yao, Yangde Feng, Yan Zeng, Fang Liu, Yangang Wang, Yue Gao. Large-Scale Simulation of Structural Dynamics Computing on GPU Clusters. In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis; SC ’23，（CCF A 推荐）

[9] Haizhou Cao, Zhenhao Huang, Tiechui Yao, Jue Wang*, Hui He, and Yangang Wang. InParformer: Evolutionary Decomposition Transformers with Interactive Parallel Attention for Long-Term Time Series Forecasting. In Proceedings of the AAAI Conference on Artificial Intelligence; AAAI’23 (CCF A推荐)

[10] Kehao Lin, Chunbao Zhou, Yan Zeng, Ningming Nie, Jue Wang*, Shigang Li, Yangde Feng, Yangang Wang, et al., A Scalable Hybrid TotalFETI Method for Massively Parallel FEM Simulations, ACM SIGPLAN Annual Symposium Principles and Practice of Parallel Programming; PPoPP’23, (CCF A推荐) 

[11] Jing Yang, Hui He, Xuemeng Zhao, Jue Wang*, Tiechui Yao, Haizhou Cao, Meng Wan, Day-ahead PV power forecasting model based on fine-grained temporal attention and cloud-coverage spatial attention, IEEE Transactions on Sustainable Energy,2023

[12] Tiechui Yao, Jue Wang*, Haoyan Wu, PeiZhang, Shigang Li, Ke Xu, Xiaoyan Liu, Xuebin Chi, Intra-hour Photovoltaic Generation Forecasting based on Multi-source Data and Deep Learning Methods, IEEE Transactions on Sustainable Energy,  2022

[13] Tiechui Yao, Jue Wang*, Haizhou Cao, et al. A Multi-level Attention-based LSTM Network for Ultra-short-term Solar Power Forecast using Meteorological Knowledge. In: The 15th International Conference on Knowledge Science, Engineering and Management. KSEM 2022. Lecture Notes in Computer Science, vol 13369. Springer, (CCF推荐), 最佳学生论文（3/498）