POSITION/TITLE
Development Engineer
RESEARCH FIELD
Medical image analysis
huyujin@sribd.cn
EDUCATION BACKGROUND
Biomedical Engineering, School of biomedical engineering, south-central minzu university, bachelor
Biomedical Engineering, School of Biomedical Engineering, medical School, Shenzhen University, master
POSITION/TITLE
Medical Big Data Lab, Engineer
RESEARCH FIELD
Medical Image Processing, Computer Vision
huangshan@sribd.cn
EDUCATION BACKGROUND
School of Biomedical Engineering, Shenzhen University, Master
Biomedical Engineering, School of Electrical Engineering, Zhengzhou University,
POSITION/TITLE
Embedded Software Engineer
RESEARCH FIELD
Industrial Automation
zhuwenxin@sribd.cn
EDUCATION BACKGROUND
Bachelor of Engineering, Shanghai Jiao Tong University
BIOGRAPHY
Graduated in 2010 with a bachelor's degree and worked in the industrial automation industry for many years, with many years of experience in the implementation of industrial control system projects, and industrial control embedded system development
POSITION/TITLE
Embedded Software Engineer
RESEARCH FIELD
Industrial Automation
zhuwenxin@sribd.cn
EDUCATION BACKGROUND
Bachelor of Engineering, Shanghai Jiao Tong University
BIOGRAPHY
Graduated in 2010 with a bachelor's degree and worked in the industrial automation industry for many years, with many years of experience in the implementation of industrial control system projects, and industrial control embedded system development
POSITION/TITLE
Senior Engineer, Smart City/Transportation/Logistics Big Data Lab, SRIBD
RESEARCH FIELD
Operations Research of Supply Chain, deep learning and machine learning strategies in supply chain optimization, system architecture design
wangxin@sribd.cn
EDUCATION BACKGROUND
Bachelor, Northeastern University, Computer Science and Technology
Master, The Chinese University of HongKong(Shenzhen), EMSc Programme in Supply Chain and Logistics Management
BIOGRAPHY
WangXin currently serves as a senior engineer at the Smart City, Transportation, and Logistics Big Data Laboratory of the Shenzhen Research Institute of Big Data (SRIBD). Prior to joining the SRIBD, he has served as an artificial intelligence expert, system full stack architecture expert, and digital consulting expert in technology companies such as IBM. His fields of expertise include operations Research of supply chain, deep learning and machine learning strategies in supply chain optimization, system architecture design, and more. In recent years, he has leaded multiple major projects such as big data analysis, system architecture design, and supply chain operation in enterprises and institutions such as Tencent, Huawei, China General Nuclear Power Group, and China Southern Power Grid. He has nearly 20 years of rich project implementation experience. He has been invited for a long time to serve as an expert evaluation team member for the digital project in Shenzhen Futian District Development & Reform Bureau.
POSITION/TITLE
SRIBD Research Scientist
RESEARCH FIELD
Energy storage technology; Machine learning; Numerical modeling
harrywan@sribd.cn
EDUCATION BACKGROUND
PhD, The Hong Kong University of Science and Technology, Aug 2018 – Dec 2022
BEng, Harbin Institute of Technology, Sep 2014 – Jun 2018
BIOGRAPHY
Dr. Shuaibin Wan is currently a Research Scientist at Shenzhen Research Institute of Big Data (SRIBD). Before joining SRIBD, he obtained his BEng Degree in Material Science and Engineering from Harbin Institute of Technology and received his PhD Degree in Mechanical Engineering from The Hong Kong University of Science and Technology. His current research lies in the interdisciplinary area of mathematical modeling and energy storage systems. His research works have been published in top journals such as Energy & Environmental Science, and Applied Energy.
ACADEMIC PUBLICATIONS
Shuaibin Wan, Haoran Jiang, Zixiao Guo, Changxiang He, Xiongwei Liang, Ned Djilali, and Tianshou Zhao. Machine learning-assisted design of flow fields for redox flow batteries. Energy & Environmental Science 15, 2874-2888 (2022). [JCR Q1, IF = 39.7]
Shuaibin Wan, Xiongwei Liang, Haoran Jiang, Jing Sun, Ned Djilali, and Tianshou Zhao. A coupled machine learning and genetic algorithm approach to the design of porous electrodes for redox flow batteries. Applied Energy 298, 117177 (2021). [JCR Q1, IF = 11.4]
Jiahui Xu, Shuaibin Wan, Yao Wang, Su Huang, Zhihao Yuan, Fanglin Chen, Yanxiang Zhang, and Tong Liu. Enhancing performance of molybdenum doped strontium ferrite electrode by surface modification through Ni infiltration. International Journal of Hydrogen Energy 46 (18), 10876-10891 (2021). [JCR Q1, IF = 7.2]
Guang Jiang, Fuyao Yan, Shuaibin Wan, Yanxiang Zhang, and Mufu Yan. Microstructure evolution and kinetics of B-site nanoparticle exsolution from an A-site-deficient perovskite surface: a phase-field modeling and simulation study. Physical Chemistry Chemical Physics 21 (21), 10902-10907 (2019). [JCR Q1, IF = 3.3]
Shuaibin Wan, Mufu Yan, and Yanxiang Zhang. A numerical study of infiltrated solid oxide fuel cell electrode with dual-phase backbone. International Journal of Energy Research 43 (7), 2562-2570 (2019). [JCR Q2, IF = 4.6]
POSITION/TITLE
SRIBD Research Scientist
RESEARCH FIELD
Energy storage technology; Machine learning; Numerical modeling
harrywan@sribd.cn
EDUCATION BACKGROUND
PhD, The Hong Kong University of Science and Technology, Aug 2018 – Dec 2022
BEng, Harbin Institute of Technology, Sep 2014 – Jun 2018
BIOGRAPHY
Dr. Shuaibin Wan is currently a Research Scientist at Shenzhen Research Institute of Big Data (SRIBD). Before joining SRIBD, he obtained his BEng Degree in Material Science and Engineering from Harbin Institute of Technology and received his PhD Degree in Mechanical Engineering from The Hong Kong University of Science and Technology. His current research lies in the interdisciplinary area of mathematical modeling and energy storage systems. His research works have been published in top journals such as Energy & Environmental Science, and Applied Energy.
ACADEMIC PUBLICATIONS
Shuaibin Wan, Haoran Jiang, Zixiao Guo, Changxiang He, Xiongwei Liang, Ned Djilali, and Tianshou Zhao. Machine learning-assisted design of flow fields for redox flow batteries. Energy & Environmental Science 15, 2874-2888 (2022). [JCR Q1, IF = 39.7]
Shuaibin Wan, Xiongwei Liang, Haoran Jiang, Jing Sun, Ned Djilali, and Tianshou Zhao. A coupled machine learning and genetic algorithm approach to the design of porous electrodes for redox flow batteries. Applied Energy 298, 117177 (2021). [JCR Q1, IF = 11.4]
Jiahui Xu, Shuaibin Wan, Yao Wang, Su Huang, Zhihao Yuan, Fanglin Chen, Yanxiang Zhang, and Tong Liu. Enhancing performance of molybdenum doped strontium ferrite electrode by surface modification through Ni infiltration. International Journal of Hydrogen Energy 46 (18), 10876-10891 (2021). [JCR Q1, IF = 7.2]
Guang Jiang, Fuyao Yan, Shuaibin Wan, Yanxiang Zhang, and Mufu Yan. Microstructure evolution and kinetics of B-site nanoparticle exsolution from an A-site-deficient perovskite surface: a phase-field modeling and simulation study. Physical Chemistry Chemical Physics 21 (21), 10902-10907 (2019). [JCR Q1, IF = 3.3]
Shuaibin Wan, Mufu Yan, and Yanxiang Zhang. A numerical study of infiltrated solid oxide fuel cell electrode with dual-phase backbone. International Journal of Energy Research 43 (7), 2562-2570 (2019). [JCR Q2, IF = 4.6]
TITLE/POSITION
Engineer
RESEARCH FIELD
Hardware, RF Circuitry
wanhuaying@sribd.cn
EDUCATION BACKGROUND
Bachelor of Electronic Information Engineering, Guangxi University
Master of Electronic and Communication Engineering, Harbin Institute of Technology
BIOGRAPHY
Previously worked with multiple companies specializing in RF and hardware circuit design and testing. Proficient in hardware and RF circuit design, with extensive experience in resolving interference and EMC issues.
TITLE/POSITION
Engineer
RESEARCH FIELD
Hardware, RF Circuitry
wanhuaying@sribd.cn
EDUCATION BACKGROUND
Bachelor of Electronic Information Engineering, Guangxi University
Master of Electronic and Communication Engineering, Harbin Institute of Technology
BIOGRAPHY
Previously worked with multiple companies specializing in RF and hardware circuit design and testing. Proficient in hardware and RF circuit design, with extensive experience in resolving interference and EMC issues.
POSITION/TITLE
Research Scientist
RESEARCH FIELD
Scientific and engineering computing, fluid-structure interaction, deep learning, computer vision
zhanglian@sribd.cn
EDUCATION BACKGROUND
BSc at Zhejiang University 2011-2015
Ph.D at Hong Kong University of Science and Technology 2015-2019
BIOGRAPHY
Lian Zhang graduated from Zhejiang University in 2015 and received his Ph.D degree at Hong Kong University of Science and Technology in 2019. From 2019 to 2020, he worked as a postdoc at Penn State University, and then worked at In-Chao Institute Ltd. He joined SRIBD in December 2022. His research interest covers scientific and engineering computing and deep learning, especially the fluid-structure interaction problem and image processing.
ACADEMIC PUBLICATIONS
- Juncai He, Jinchao Xu, Lian Zhang, Jianqing Zhu. An Interpretive Constrained Linear Model for ResNet and MgNet, Neural Networks, 162, 384-392 2023.
- Xiaofeng Xu, Lian Zhang, Yin Shi, Long-Qing Chen, Jinchao Xu. Integral Boundary Conditions in Phase Field Models, Computer and Mathematics with Application, 135, 1–5, 2023.
- Mingchao Cai, Mo Mu, Lian Zhang. Decoupling Techniques for Coupled PDE Models in Fluid Dynamics, Book chapter in The Essence of Large-Eddy Simulations, 10.5772/intechopen.105997, 2022.
- Jianhong Chen, Wenrui Hao, Pengtao Sun and Lian Zhang. Predict Blood Pressure by Photoplethysmogram with the Fluid-Structure Interaction Modeling, Communications in Computational Physics 31(4), 1114-1133, 2022.
- Wenrui Hao, Pengtao Sun, Jinchao Xu and Lian Zhang. An efficient computational approach for solving the fluid-structure interaction problem with an application in aneurysm, Journal of Computational Physics 433, 110181, 2021.
- Juncai He, Xiaodong Jia, Jinchao Xu, Lian Zhang, and Liang Zhao. Make l1 Regularization Effective in Training Sparse CNN, Computational Optimization and Applications 77, 163-182, 2020.
- Lian Zhang, Mingchao Cai and Mo Mu. A multirate approach for fluid-structure interaction computation with decoupled methods, Communications in Computational Physics 27, 1014-1031, 2020.
POSITION/TITLE
Algorithm Engineer
RESEARCH FIELD
Deep Learning, Network Optimization
maojingwei@sribd.cn
EDUCATION BACKGROUND
Master of the Chinese University of Hong Kong, Shenzhen
Bachelor of Xidian University
BIOGRAPHY
Mao Jingwei obtained a Bachelor's degree in Electronic Information Engineering from Xidian University in 2016. In 2019, he obtained a Master of Philosophy (MPhil) degree in Computer Information Engineering from The Chinese University of Hong Kong, Shenzhen. After graduating in 2019, he worked as an algorithm engineer at Ping An Insurance and Alibaba. In 2023, he joined the Shenzhen Big Data Research Institute as an algorithm engineer.
PAPER
1. Li Wenye, Mao J., Zhang Y., Cui S. (2018) Fast Similarity Search via Optimal Sparse Lifting. In Advances in Neural Information Processing Systems 31 (NeurIPS’2018).
PATENT
1. Method, Apparatus, Computer Equipment, and Medium for Answer Generation Based on Artificial Intelligence.
2. A Semi-Supervised Method and Mobile Terminal without Consistency Constraints.
POSITION/TITLE
Algorithm Engineer
RESEARCH FIELD
Deep Learning, Network Optimization
maojingwei@sribd.cn
EDUCATION BACKGROUND
Master of the Chinese University of Hong Kong, Shenzhen
Bachelor of Xidian University
BIOGRAPHY
Mao Jingwei obtained a Bachelor's degree in Electronic Information Engineering from Xidian University in 2016. In 2019, he obtained a Master of Philosophy (MPhil) degree in Computer Information Engineering from The Chinese University of Hong Kong, Shenzhen. After graduating in 2019, he worked as an algorithm engineer at Ping An Insurance and Alibaba. In 2023, he joined the Shenzhen Big Data Research Institute as an algorithm engineer.
PAPER
1. Li Wenye, Mao J., Zhang Y., Cui S. (2018) Fast Similarity Search via Optimal Sparse Lifting. In Advances in Neural Information Processing Systems 31 (NeurIPS’2018).
PATENT
1. Method, Apparatus, Computer Equipment, and Medium for Answer Generation Based on Artificial Intelligence.
2. A Semi-Supervised Method and Mobile Terminal without Consistency Constraints.
POSITION/TITLE
Algorithm Engineer of Data-driven Intelligent Information System Laboratory
RESEARCH FIELD
Research and development of computer vision, speech, Natural language processing AI algorithms
zhouweicong@sribd.cn
EDUCATION BACKGROUND
Master, Imperial College London, UK
Bachelor, Northwest A & F University, China
AWARDS
Principle Scholarship, Northwest A&F University, 2013
Professional Scholarship, Northwest A&F University, 2010, 2011, 2012, 2013
BIOGRAPHY
I graduated from ICL with master degree in 2015. Then, I’ve been focusing on AI algorithm research and development for many years. I worked at TOSHIBA， Zhuiyi and Tencent as a senior algorithm engineer. I joined in SRIBD at September, 2023.
ACADEMIC PUBLICATIONS
Framewise Supervised Training towards End-to-End Speech Recognition Models: First Results, Mohan Li, Yuanjiang Cao, Weicong Zhou, Min Liu, INTERSPEECH, 2019
PATENTS
A method, device, computer device and storage medium to recognize overlapping speech CN111145782A
A method, system and devices to process speech CN110335621A
POSITION/TITLE
Engineer
RESEARCH FIELD
Industrial Network Protocols
zhoufuqiang@sribd.cn
EDUCATION BACKGROUND
Jilin University
BIOGRAPHY
Engineer Zhou Fuqiang primarily engages in research on industrial network protocols and software development. He graduated from Jilin University with a major in Electronic Information Science and Technology in 2018. He has worked successively at Ganjiang Group and Industrial Bank, where he has conducted in-depth research on software development and industrial network protocols. He has participated in one national key R&D project, applied for multiple national patents related to time-sensitive networks, and obtained one authorized software copyright.
POSITION/TITLE
Engineer
RESEARCH FIELD
Industrial Network Protocols
zhoufuqiang@sribd.cn
EDUCATION BACKGROUND
Jilin University
BIOGRAPHY
Engineer Zhou Fuqiang primarily engages in research on industrial network protocols and software development. He graduated from Jilin University with a major in Electronic Information Science and Technology in 2018. He has worked successively at Ganjiang Group and Industrial Bank, where he has conducted in-depth research on software development and industrial network protocols. He has participated in one national key R&D project, applied for multiple national patents related to time-sensitive networks, and obtained one authorized software copyright.
