王珏
王珏
硕士生导师
岗位:正高级工程师
职务:人工智能部副主任
所属部门:人工智能技术与应用发展部
学历:博士研究生
邮箱:wangjue@sccas.cn
通讯地址:
学科专业(学术型/专业型):计算机应用技术,计算机技术
招生方向:
人工智能算法与应用软件
承担科研项目等情况
先后承担了863子课题、国家重点研发计划课题、中国科学院战略性先导科技专项子课题、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。获得中核集团技术发明一等奖、国家电网公司科技进步三等奖等。
代表论著

[1] 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)

[2] 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)

[3] Cao, Haizhou, 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)

[4]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) 

[5] Yao, Tiechui, Jue Wang*, Meng Wan, Zhikuang Xin, Yangang Wang, Rongqiang Cao, Shigang Li, and Xuebin Chi. VenusAI: An artificial intelligence platform for scientific discovery on supercomputers. Journal of Systems Architecture (2022): 102550. JCR Q1. IF 5.836.

[6] 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, July. 2022, IF 8.31

[7] Tiechui Yao, Jue Wang*, Yangang Wang, et al. Very Short-term Forecasting of Distributed PV Power using GSTANN. CSEE Journal of Power and Energy Systems. 2022. JCR Q1, IF 6.014

[8] 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, Best Student Paper(3/498)

[9] Tiechui Yao, Jue Wang*, et al. A photovoltaic power output dataset: Multi-source photovoltaic power output dataset with Python toolkit[J]. Solar Energy, 2021, 230: 122-130. JCR Q2. IF 7.188

[10] Chen Li, Yulei Wu, Zhonghua Lu, Jue Wang, and Yonghong Hu, A Multi-Period Multi-Objective Portfolio Selection Model with Fuzzy Random Returns for Large Scale Securities Data, IEEE Transactions on Fuzzy System, Volume: 29, Issue: 1, Jan. 2021,JCR Q1, IF 12.029