jinghua wu | Behavior science | Women Researcher Award

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Assoc Prof Dr. jinghua wu | Behavior science | Women Researcher Award

Assoc Prof Dr. jinghua wu, sichuan Agricultural University, China

Dr. Wu Jinghua is an associate professor at the College of Information Engineering, Sichuan Agricultural University, a key university under China’s “Project 211.” She holds a Ph.D. in Information Management System from South-West Financial University. With research interests in information management systems, e-commerce, and e-finance, she has authored numerous papers and publications. Previously, she worked at Leshan Gas Company and has undertaken significant roles in research projects focusing on digital agriculture and financial technologies. Dr. Wu is known for her analytical skills and dedication to advancing information technology applications. 📊

 

Publication profile

Scopus

Education Experience

Dr. Wu Jinghua holds a Ph.D. in Information Management System from South-West Financial University (2012), an M.S. in Computer Science from Southwest University (2005), and a B.S. in Computing Science from China West Normal University (1999).

 

Professional Experience

She has been an associate professor at Sichuan Agricultural University since 2012, teaching courses on E-commerce, Java Programming, and more.

Dr. Wu Jinghua’s research focuses on several key areas within information engineering and agricultural economics. Her work primarily centers around data mining, machine learning applications such as natural language processing and sentiment analysis, and the digital transformation of agriculture. She has contributed significantly to fields like e-commerce, e-finance, and digital agriculture, emphasizing innovations in information management systems and software engineering. Dr. Wu’s research also extends to agricultural price prediction models and the spatial-temporal factors influencing agricultural economics. Her interdisciplinary approach integrates technology with agricultural practices, aiming to enhance efficiency and decision-making processes in farming communities. 🌾💻

Research Focus

Dr. Wu Jinghua’s research focuses on several key areas within information engineering and agricultural economics. Her work primarily centers around data mining, machine learning applications such as natural language processing and sentiment analysis, and the digital transformation of agriculture. She has contributed significantly to fields like e-commerce, e-finance, and digital agriculture, emphasizing innovations in information management systems and software engineering. Dr. Wu’s research also extends to agricultural price prediction models and the spatial-temporal factors influencing agricultural economics. Her interdisciplinary approach integrates technology with agricultural practices, aiming to enhance efficiency and decision-making processes in farming communities. 🌾💻

 

Publication Top Notes

📄 Agricultural price prediction based on data mining and attention-based gated recurrent unit: a case study on China’s hog, Journal of Intelligent and Fuzzy Systems, 2024

📄 Exploring the Chinese public’s affective attitudes towards digital transformation in agriculture: A social media-based analysis, Applied Psychology: Health and Well-Being, 2024

📄 Agricultural price forecasting based on the spatial and temporal influences factors under spillover effects, Kybernetes, 2023 (cited by 1)

📄 Student classroom behavior recognition and evaluation system based on YOLOX, Proceedings of SPIE – The International Society for Optical Engineering, 2022 (cited by 1)

📄 A Comparative Study of Image Dehazing Based on Attention-Net and U-Net Atmospheric Light Estimation, 2020 IEEE 6th International Conference on Computer and Communications, 2020

📄 Image restoration of agricultural history based on neural patch synthesis, 2019 IEEE 11th International Conference on Communication Software and Networks, 2019

📄 Automatic classification and detection of oranges based on computer vision, 2018 IEEE 4th International Conference on Computer and Communications, 2018