Jianjia Wang | Complex Networks | Best Researcher Award

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Assist Prof Dr. Jianjia Wang | Complex Networks | Best Researcher Award

Scopus Profile

Educational Details

Dr. Jianjia Wang holds a Ph.D. in Computer Science from the University of York, United Kingdom (2014-2018), where he specialized in computer vision and pattern recognition within the Department of Computer Science. Prior to his doctoral studies, he completed a Master of Science in Electronic Engineering from the Hong Kong University of Science and Technology (2011-2012), focusing on advanced electronic and computer engineering topics. He also earned a Bachelor of Engineering in Measuring & Control Technology and Instrumentation from Nanjing University of Posts and Telecommunications (2007-2011), where he built a strong foundation in automation and instrumentation technologies. His academic background integrates expertise in both electronics and computer science.

Employment

Dr. Jianjia Wang served as a Lecturer at the School of Computer Science and Engineering, Shanghai University, P.R. China, from 2018 to 2023. During this period, he was also an Adjunct Professor with the Council on International Educational Exchange (CIEE) at Rutgers, The State University of New Jersey, USA, from 2020 to 2022, where he contributed to the Department of Computer Science. Prior to these roles, he worked as a Project Engineer specializing in 3D Machine Vision at the Hong Kong Applied Science and Technology Research Institute (HK ASTRI) from 2013 to 2014, where he was involved in the Display Group and focused on 3D Machine Vision Systems. His professional experience encompasses a broad range of expertise in computer vision, engineering, and international academic collaboration.

Teaching Experience

Dr. Jianjia Wang has a diverse teaching portfolio that spans multiple institutions and disciplines. At Rutgers, The State University of New Jersey, he taught CS111 Introduction to Computer Science in Autumn 2020 and CS112 Data Structures and Algorithms in Spring 2021. During his tenure at Denison University, he delivered CS109 Introduction to Computer Programming in Spring 2021. At Shanghai University, Dr. Wang taught several courses, including CS08306145 Big Data: From Theory to Practice in Spring 2021, CS08696027 Signal Processing in Autumn 2020, and CS08695001 Blockchain and Cryptocurrency during the 2020-2021 academic year. Additionally, he has experience teaching a range of subjects at the University of York, including COM00001I-A Artificial Intelligence (ARIN), COM00005C-A Mathematical Foundations of Computer Science (MFCS), and COM00006C-A Numerical Analysis (NUMA), across various terms from 2015 to 2017. His teaching experience reflects a strong background in computer science and engineering, encompassing both theoretical and practical aspects of the field.

Grants

Dr. Jianjia Wang has been the Principal Investigator on several significant research projects. From January 2021 to December 2023, he led the Automatic Testing Aging System in New Energy project under the Innovative Entrepreneurial Program of Technique Leader in Fei-Feng Talent, Wuxi Science and Technology Bureau, with a funding of CNY 3,000,000. He also directed the Using Complex Networks to Analyze Urban Spatial Density and Population project funded by the Shanghai Pujiang Talent Program, receiving CNY 300,000 from October 2021 to September 2023. His research on Structural Properties in Complex Networks with Statistical Pattern Recognition was supported by the Oversea Visiting Fellowship Scheme of the Ministry of Science and Technology of P.R. China, with a grant of CNY 350,000 from January 2022 to December 2023. Additionally, Dr. Wang managed the Statistical Structural Pattern Recognition in Complex Networks project, funded by the Science and Technology Commission of Shanghai Municipality, with CNY 150,000 from January 2022 to January 2023. He also received Young Professor Funding from the Shanghai Municipal Education Commission for the project Young Professor Funding of Shanghai University, which was awarded CNY 40,000 from January 2021 to December 2022. Other notable projects include Analyzing the Spatial and Population in the City with Complex Networks and Signal Processing, funded by the Grant Joint Project of Shanghai University and the Key Course Project of Shanghai University, respectively.

In addition to his principal investigator roles, Dr. Wang has been a co-investigator in various collaborative projects. He contributed to the Epidemic Spread and Prediction Model in Complex Spatio-temporal Environment, funded by the Ministry of Science and Technology of China, with a budget of CNY 700,000 from October 2021 to October 2024. He also worked on the Active Learning Assists Diagnosis of Gastrointestinal Diseases project with the Science and Technology Commission of Shanghai Municipality, which received CNY 200,000 from April 2020 to June 2023, and the Multi-center Capsule Endoscopy Image Federation Active Learning project funded by the National Natural Science Foundation of China (NSFC), with a grant of CNY 700,000 from January 2022 to December 2025.

Academic Service

Dr. Jianjia Wang has been actively involved in various academic and professional roles. Since 2020, he has served as a Recruitment Ambassador for the University of York, UK, where he helps to attract and engage prospective students. Additionally, he has been an Associate Editor for the International Journal of Complexity, Pattern Recognition since 2018, contributing to the journal’s editorial board. Dr. Wang is also a reviewer for numerous prestigious journals and conferences, including Pattern Recognition, Pattern Recognition Letters, IEEE Intelligent Systems, IEEE Access, Scientific Reports, Information Systems, Applied Sciences, Journal of Complex Networks, and Expert Systems with Applications. His expertise extends to reviewing for major conferences such as the IEEE/CVF International Conference on Computer Vision and Pattern Recognition (CVPR), International Conference on Pattern Recognition (ICPR), Asian Conference on Computer Vision (ACCV), Winter Conference on Applications of Computer Vision (WACV), and the British Machine Vision Conference (BMVC). His extensive involvement in these roles reflects his significant contribution to the fields of computer vision and pattern recognition.

Research Interests

Dr. Jianjia Wang’s expertise spans several critical areas of computer science, including Data Science, Pattern Recognition, Artificial Intelligence (AI), and Complex Networks. His research in Data Science focuses on extracting meaningful insights from vast datasets, enabling advancements in fields such as urban planning, healthcare, and environmental management. Through Pattern Recognition, Dr. Wang has developed algorithms that identify patterns in data, contributing to innovations in image recognition, natural language processing, and predictive modeling. His work in AI harnesses machine learning and deep learning to solve complex problems, particularly in automating processes and enhancing decision-making systems. Additionally, his contributions to Complex Networks involve analyzing interconnected systems, such as urban networks and social structures, to improve efficiency and sustainability in community infrastructures. This broad expertise allows Dr. Wang to apply advanced computational techniques to address real-world challenges, creating a significant societal impact.

Top Notable Publications

The Ihara Zeta Function as a Partition Function for Network Structure Characterisation

Authors: Wang, J., Hancock, E.R.

Journal: Scientific Reports

Year: 2024

Volume: 14

Issue: 1

Article Number: 18386

Citations: 0

Exploring the Regional Development Trend in New York City

Authors: Yu, T., Zhu, H., Wu, X., Wang, J.

Journal: Proceedings of SPIE – The International Society for Optical Engineering

Year: 2024

Volume: 13018

Article Number: 130184P

Citations: 0

Exploring the Regional Function in Shanghai and New York City

Authors: Yu, T., Wu, X., Wang, J.

Journal: Proceedings of SPIE – The International Society for Optical Engineering

Year: 2024

Volume: 13018

Article Number: 130184O

Citations: 0

Construction of Gene Expression Patterns to Identify Critical Genes Under SARS-CoV-2 Infection Conditions

Authors: Yu, X., Li, W., Wang, J., Wu, X., Sheng, B.

Journal: IEEE/ACM Transactions on Computational Biology and Bioinformatics

Year: 2024

Volume: 21

Issue: 4

Pages: 607–618

Citations: 0

Multiple Detection Model Fusion Framework for Printed Circuit Board Defect Detection

Authors: Wu, X., Zhang, Q., Wang, J., Yao, J., Guo, Y.

Journal: Journal of Shanghai Jiaotong University (Science)

Year: 2023

Volume: 28

Issue: 6

Pages: 717–727

Citations: 0

Statistical Structural Inference from Edge Weights Using a Mixture of Gamma Distributions

Authors: Wang, J., Hancock, E.R.

Journal: Journal of Complex Networks

Year: 2023

Volume: 11

Issue: 5

Article Number: cnad038

Citations: 0

Space or Time for Video Classification Transformers

Authors: Wu, X., Tao, C., Zhang, J., Liu, Y., Guo, Y.

Journal: Applied Intelligence

Year: 2023

Volume: 53

Issue: 20

Pages: 23039–23048

Citations: 0