Professor Peng Shi

Keywords:Big data technology

Contact:pshi@ustb.edu.cn

Researches

Dr. Peng Shi is the Project Manager of Data Sharing System of National Center for Materials Service Safety, China at the University of Science and Technology, Beijing (USTB). Dr. Shi graduated from Shandong University with the B.S. degree in 1999. He received his M.S. degree from Ocean University of China (Qingdao) in 2002. And he got Ph.D. degree from Institute of Computing Technology, Chinese Academy of Sciences in 2007.

Dr. Shi’s interests include big data technology, high-throughput experiment and data analysis, social network analysis, artificial intelligence and knowledge engineering.

l  Main Projects

- Project 1 :”National Key R&D Program of China (2017YFB0203703)”, “intelligent workflow management and remote visualization technology”, total fund 1,200,000 RMB, 2017-2020

- Project 2 :“National Grand Fundamental Research 973 Program of China (2013CB329605)”, “information diffusion and source location in social network”, total fund 2,600,000 RMB, 2013-2017

l  Main Contributions

- high-throughput experiment platform The platform mainly consists of high-throughput corrosion reaction facility, data acquisition system and data processing system. The corrosion reaction facility supports high-throughput materials corrosion reactions under various conditions. The data acquisition system is mainly responsible for capturing the images of samples’ surface, collecting electrochemical signals and storing them into the computer in real time. The data processing system treats the acquired data and evaluates the degree of materials corrosion in real time by program automatically. The platform not only reduces the occupation of the equipment, but also improves the efficiency of sample preparation and experiment occurrence.

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- Dynamic Detection and Tracking on Large-Scale Text StreamWith distributed processing mechanism and hadoop platform, our method obviously improves the efficiency of burst hotspots detection and tracking from large-scale text stream. The method will enhance the ability for real-time understanding of online social network.

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l  Publications (5-10 selected papers)

1.       Jianyi Huang, Jianjiang Li, Yingying Chen, Jiankun Sun, Peng Shi*, Burst Hotspots Dynamic Detection and Tracking on Large-Scale Text Stream, IEEE Access, 2019, Vol. 7, 30913-30924

2.       Thike Phyu Hnin, Zhou Xu, Yuan Cheng, Ying Jin, Peng Shi*, Materials Failure Analysis Utilizing Rule-case Based Hybrid Reasoning MethodEngineering Failure Analysis, 2019, Vol.95, 300-311

3.       Peng Shi, Bin Li, Phyu Hnin Thike, Lianhong Ding, A Knowledge-Embedded Lossless Image Compressing Method for High-Throughput Corrosion Experiment, International Journal of Distributed Sensor Networks, 2018, Vol. 14(1)

4.       Wenwen Xu, Peng Shi*, Jianyi Huang, Feng Liu, Understanding and Predicting the Peak Popularity of Bursting Hashtags, Journal of Computational Science, 2018, Vol.28, 328-335

5.       Lianhong Ding, Bin Sun, Peng Shi*, Chinese Microblog Topic Detection through POS-Based Semantic Expansion, Information, 2018, 9, 203; doi:10.3390/info9080203

6.       Peng Shi, Bin Li, Jindong Huo, Lei Wen, A Smart High-Throughput Experiment Platform for Materials Corrosion Study. Scientific Programming, 2016, Article ID 6876241

7.       Peng Shi, Jindong Huo, Qingmei Wang, Constructing Ontology for Knowledge Sharing of Materials Failure Analysis, Data Science Journal, 2014,Vol.12, p 181-190

l  Books

1.     Peng Shi, Qingmei Wang, Liwu Jiang, Mathematical Methods and Applications in Materials Science (in Chinese), Chemical Industry Press, 2017

2.     Lianhong Ding, Peng Shi, Case Study and Applications of Complex Network (in Chinese), China Machine Press, 2017.


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