Professor at Guangxi University, Chinađź“–
Jianxin Deng is a professor and Ph.D. candidate supervisor in Mechanical Engineering at Guangxi University and serves as the vice director of the Guangxi Key Laboratory of Manufacturing Systems and Advanced Manufacturing Technology. He has an extensive academic and professional background, contributing to advancements in intelligent manufacturing, manufacturing systems, informatics, and squeeze-casting technology. With over 60 published academic papers and 15 national invention patents, along with one U.S. patent, his innovative work continues to impact the field significantly.
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Education Background🎓
Jianxin Deng earned his master’s degree in Industrial Engineering from Chongqing University, China, followed by a Ph.D. in Mechanical Engineering from South China University of Technology, China. His academic foundation laid the groundwork for his multidisciplinary research in manufacturing and data engineering.
Professional Experience🌱
Currently, Jianxin Deng holds a pivotal academic position as a professor at Guangxi University, where he mentors Ph.D. candidates and leads critical research initiatives. His collaborative work includes partnerships with renowned institutions such as Georgia Institute of Technology and South China University of Technology, focusing on integrated process models and data-driven design methods. As an editor for the journal Equipment Manufacturing Technology and a senior member of the Chinese Mechanical Engineering Society, he actively shapes the future of his field.
Jianxin Deng’s research spans intelligent manufacturing, industrial engineering, manufacturing systems, and data-driven solutions. His recent work on the efficient extraction method EMbTTBF highlights his expertise in developing innovative approaches to address data augmentation and literature analysis challenges. His ongoing projects focus on creating adaptable and efficient methodologies for modern manufacturing and data engineering.
Author Metrics
Publications Top Notes đź“„
1. Resource Coordination Scheduling Optimisation of Logistics Information Sharing Platform Considering Decision Response and Competition
- Authors: Deng, J., Chen, X., Wei, W., Liang, J.
- Journal: Computers and Industrial Engineering
- Year: 2023
- Volume: 176
- Article Number: 108892
- Citations: 7
- Abstract: This paper presents a novel optimization framework for logistics information sharing platforms that integrates decision-making response times and competitive factors. The study employs advanced coordination models to enhance resource scheduling efficiency, ensuring balanced competition among stakeholders and improved logistics operations.
2. Review of Design of Process Parameters for Squeeze Casting
- Authors: Deng, J., Xie, B., You, D., Huang, H.
- Journal: Chinese Journal of Mechanical Engineering (English Edition)
- Year: 2023
- Volume: 36
- Issue: 1
- Article Number: 146
- Citations: 3
- Abstract: This review provides a comprehensive analysis of squeeze casting process parameters, highlighting key advancements and challenges. It outlines methodologies for optimizing casting performance and introduces new perspectives for the design and control of process variables.
3. Intelligent Optimization Design of Squeeze Casting Process Parameters Based on Neural Network and Improved Sparrow Search Algorithm
- Authors: Deng, J., Liu, G., Wang, L., Wu, X.
- Journal: Journal of Industrial Information Integration
- Year: 2024
- Volume: 39
- Article Number: 100600
- Citations: 1
- Abstract: This paper introduces an intelligent framework leveraging neural networks and an improved sparrow search algorithm to optimize squeeze casting process parameters. The proposed approach achieves enhanced precision and efficiency, reducing production defects and material waste.
4. The Parameter Identification of Metro Rail Corrugation Based on Effective Signal Extraction and Inertial Reference Method
- Authors: Sun, H., He, D., Ma, H., Wen, Z., Deng, J.
- Journal: Engineering Failure Analysis
- Year: 2024
- Volume: 158
- Article Number: 108043
- Citations: 7
- Abstract: This study develops a novel methodology for identifying metro rail corrugation parameters using signal extraction and inertial reference techniques. The findings contribute to more effective rail maintenance strategies, enhancing safety and operational performance.
5. Blockchain-Based Security Access Control System for Sharing Squeeze Casting Process Database
- Authors: Deng, J., Liu, G., Zeng, X.
- Journal: Integrating Materials and Manufacturing Innovation
- Year: 2024
- Volume: 13
- Issue: 1
- Pages: 92–104
- Citations: 1
- Abstract: This research proposes a blockchain-based access control system for securely sharing squeeze casting process databases. The system enhances data integrity and accessibility, enabling collaborative innovation in manufacturing processes.
Conclusion
Prof. Jianxin Deng is an outstanding candidate for the Best Researcher Award. His innovative contributions to intelligent manufacturing, logistics optimization, and data-driven methodologies are highly impactful, and his patents underscore the practical relevance of his work. Although there are opportunities to diversify his application areas and enhance outreach, his achievements firmly position him as a leading figure in mechanical engineering and manufacturing research.
Recommendation:
Prof. Deng’s remarkable accomplishments and continued dedication to advancing his field make him a strong contender deserving of the award.