王珏
王珏
wangjue@sccas.cn
岗位:正高级工程师
专家类别:博士生导师
学历:博士研究生
计算机网络信息中心人工智能技术与应用发展部 副主任,中国科学院青年促进会会员,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到UIUC的Laxmikant V. Kale教授课题组访学。有近20年的计算机体系结构底层适配经验,包括性能模型、自动调优和人工智能相关工具、软件和应用的研发经历;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、AAAI、CPC、JSA、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80余篇;授权专利50余项;专著1部。
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