Kuo-Ching Ying | Metaheuristics | Best Researcher Award

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Prof Dr. Kuo-Ching Ying | Metaheuristics | Best Researcher Award

National Taipei University of Technology, Taiwan

Author Profiles

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Scopus

👨‍🏫 Current Position and Leadership Roles

Prof. Dr. Kuo-Ching Ying is currently a Distinguished Professor in the Department of Industrial Engineering and Management at National Taipei University of Technology, Taiwan. In addition to his role as a faculty member, he also serves as the Associate Dean of the College of Management and Vice Director of the EMBA Program at the university. His leadership positions reflect his deep commitment to advancing education and research in the fields of industrial engineering and management.

🎓 Early Academic Pursuits and Education

Prof. Ying’s academic journey began with a Master’s degree in Industrial Management from the National Taiwan University of Science and Technology in 1992. His academic pursuits culminated in a Ph.D. in Industrial Management from the same institution in 2003. His educational background provided the foundation for his current expertise in operations scheduling, combinatorial optimization, and various aspects of industrial management.

đź’Ľ Professional Endeavors and Editorial Contributions

Prof. Ying has significantly contributed to the academic community as an editor for several prestigious journals. He has been serving as an editor for Advances in Industrial Engineering and Management since December 2012 and has held editorial roles for other journals like IEEE Access (since 2018), Applied Sciences (since 2021), and American Journal of Operations Management and Information Systems (since 2020). His editorial work spans across more than 10 journals, underscoring his significant involvement in shaping the direction of research in industrial management and optimization fields.

🔬 Contributions and Research Focus

Prof. Ying’s primary research interests revolve around operations scheduling, combinatorial optimization, and industrial management. He has authored more than 130 academic papers in top-tier international journals such as IEEE Access, Computers and Operations Research, Applied Soft Computing, and European Journal of Operational Research. His research delves into innovative approaches to solving complex problems in industrial settings, particularly in operations management, manufacturing, and logistics.

🌍 Impact and Influence in Academia

Through his extensive research contributions and editorial roles, Prof. Ying has become a recognized figure in the fields of industrial engineering and management. His work has been cited numerous times in academic research, demonstrating his influence in advancing knowledge in operations scheduling and combinatorial optimization. His efforts have led to advancements in how industries manage production, operations, and logistics.

đź“š Academic Citations and Recognition

Prof. Ying’s scholarly output has earned him wide recognition within the academic community. His work has been cited extensively across numerous journals, reflecting the importance and impact of his research. The high citation rate of his publications is a testament to the relevance and applicability of his work in both academic and industrial contexts. He is widely regarded as a thought leader in industrial management research.

đź’ˇ Technical Skills and Expertise

Prof. Ying possesses strong technical skills in areas such as operations research, optimization algorithms, and industrial management. He is particularly skilled in developing models and techniques for solving complex optimization problems related to manufacturing, logistics, and scheduling. His expertise in artificial intelligence and computational techniques further enhances his ability to contribute to cutting-edge research in these fields.

👩‍🏫 Teaching Experience and Mentorship

Prof. Ying has been a mentor to numerous students in the Department of Industrial Engineering and Management at National Taipei University of Technology. As an educator, he has significantly shaped the careers of many professionals in industrial management. His teaching philosophy emphasizes the application of theory to real-world problems, preparing students to tackle challenges in operations management and optimization. His experience in teaching and mentoring plays a key role in nurturing the next generation of scholars and industry leaders.

🌱 Legacy and Future Contributions

Prof. Ying’s legacy is already well established through his substantial academic achievements, his leadership in educational programs, and his continued contributions to the field. Looking ahead, he is likely to continue shaping the future of industrial engineering research, particularly in optimizing industrial processes and the integration of new technologies. His future contributions will likely focus on further advancing operations research, combinatorial optimization, and artificial intelligence applications in industrial contexts.

📖 Top Noted Publications 

Reinforcement Learning-based Alpha-list Iterated Greedy for Production Scheduling
  • Authors: Kuo-Ching Ying, Pourya Pourhejazy, Shih-Han Cheng
    Journal: Intelligent Systems with Applications
    Year: 2024
Minimizing makespan in two-stage assembly additive manufacturing: A reinforcement learning iterated greedy algorithm
  • Authors: Kuo-Ching Ying, Shih-Wei Lin
    Journal: Applied Soft Computing
    Year: 2023
Meta-Lamarckian-based iterated greedy for optimizing distributed two-stage assembly flowshops with mixed setups
  • Authors: Pourya Pourhejazy, Chen-Yang Cheng, Kuo-Ching Ying, Nguyen Hoai Nam
    Journal: Annals of Operations Research
    Year: 2023
Supply chain-oriented permutation flowshop scheduling considering flexible assembly and setup times
  • Authors: Kuo-Ching Ying, Pourya Pourhejazy, Chen-Yang Cheng, Ren-Siou Syu
    Journal: International Journal of Production Research
    Year: 2023
Adjusted Iterated Greedy for the optimization of additive manufacturing scheduling problems
  • Authors: Kuo-Ching Ying, Fruggiero, F., Pourhejazy, P., Lee, B.-Y.
    Journal: Expert Systems with Applications
    Year: 2022

Jing An | Artificial Intelligence | Best Researcher Award

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Dr. Jing An | Artificial Intelligence | Best Researcher Award

Yancheng Institute of Technology, China

👨‍🎓Professional Profile

Scopus Profile

👨‍🏫 Summary

Dr. Jing An is a distinguished professor and master tutor at Yancheng Institute of Technology, China. He specializes in intelligent manufacturing engineering, industrial big data fault diagnosis, and residual life prediction. With numerous patents and software copyrights, Dr. An has published over 20 SCI/EI indexed papers and contributed to key academic texts. His pioneering research in artificial intelligence-based fault diagnosis has earned him prestigious awards, including first-place recognition in the China Commerce Federation Science and Technology Award .

🎓 Education

Dr. An holds a Ph.D. in Computer Science from Hohai University (2021) and a Master’s degree in Computer Science from Harbin University of Science and Technology (2006). His academic foundation has strongly influenced his research in AI and fault diagnosis.

đź’Ľ Professional Experience

Having joined Yancheng Institute of Technology in 2006, Dr. An is also the Vice President of Science and Technology for Jiangsu Province’s “Double Innovation Plan.” He has led numerous provincial-level projects, and his expertise has extended to more than 10 industry partnerships 🚀.

đź“š Academic Citations

Dr. An has authored over 20 peer-reviewed papers in prestigious journals such as IEEE Access and Mathematical Problems in Engineering. His impactful research on AI-based fault diagnosis methods is frequently cited within the academic community .

🔧 Technical Skills

Dr. An is skilled in AI-based fault diagnosis, deep learning, machine learning, and industrial big data analytics. He has expertise in Convolutional Neural Networks (CNNs) and intelligent manufacturing systems, focusing on improving machinery reliability and efficiency .

🧑‍🏫 Teaching Experience

Dr. An has been recognized as an outstanding teacher twice at Yancheng Institute of Technology. He teaches courses in intelligent manufacturing engineering and industrial big data fault diagnosis, preparing students to advance in the field of AI and data science .

🔍 Research Interests

Dr. An’s research is focused on developing intelligent systems for fault diagnosis in rotating machinery, predictive maintenance, and the application of deep learning techniques in industrial big data. His work aims to enhance manufacturing processes and equipment reliability .

đź“–Top Noted Publications

Hybrid Mechanism and Data-Driven Approach for Predicting Fatigue Life of MEMS Devices by Physics-Informed Neural Networks

Authors: Cheng, J., Lu, J., Liu, B., An, J., Shen, A.

Journal: Fatigue and Fracture of Engineering Materials and Structures

Year: 2024

Bearing Intelligent Fault Diagnosis Based on Convolutional Neural Networks

Authors: An, J., An, P.

Journal: International Journal of Circuits, Systems and Signal Processing

Year: 2022

Deep Clustering Bearing Fault Diagnosis Method Based on Local Manifold Learning of an Autoencoded Embedding

Authors: An, J., Ai, P., Liu, C., Xu, S., Liu, D.

Journal: IEEE Access

Year: 2021

Deep Domain Adaptation Model for Bearing Fault Diagnosis with Riemann Metric Correlation Alignment

Authors: An, J., Ai, P.

Journal: Mathematical Problems in Engineering

Year: 2020

Deep Domain Adaptation Model for Bearing Fault Diagnosis with Domain Alignment and Discriminative Feature Learning

Authors: An, J., Ai, P., Liu, D.

Journal: Shock and Vibration

Year: 2020

Chengjie Sun – Natural Lanauage processing – Best Researcher Award 

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Assoc Prof Dr Chengjie Sun - Natural Lanauage processing - Best Researcher Award 

Harbin Institute of Technology - China

Author Profile:

Early Academic Pursuits

Assoc Prof Dr Chengjie Sun began his academic journey at Yantai University, where he pursued a Bachelor's degree in Computer Science and Technology from 1998 to 2002. Subsequently, he continued his education at Harbin Institute of Technology, achieving a Master's degree in Computer Science and Technology from 2002 to 2004. Later, he furthered his academic pursuits at the same institute, obtaining his Doctorate in Computer Application Technology from 2004 to 2008.

Professional Endeavors

After completing his doctoral studies, Assoc Prof Dr Chengjie Sun embarked on an illustrious professional journey. He joined the Harbin Institute of Technology's School of Computer Science and Technology as a Lecturer from January 2009 to December 2014. In 2013, he expanded his academic horizons by serving as a Visiting Scholar at the Massachusetts Institute of Technology's Computer Science and Artificial Intelligence Laboratory (CSAIL). Since January 2015, he has held the position of Associate Professor at the Harbin Institute of Technology.

Additionally, Assoc Prof Dr Chengjie Sun enriched his professional experience by collaborating with renowned institutions and organizations. He served as a Visiting Scholar at Microsoft Research Asia's Natural Language Computing Group from September 2011 to July 2012.

Contributions and Research Focus

Assoc Prof Dr Chengjie Sun's research interests primarily revolve around natural language processing technologies and their applications, recommender systems, and machine learning. His scholarly contributions encompass a wide range of topics, including offensive message identification, explainable dialogue systems, fake news detection, response generation, user modeling, and named entity recognition, among others. Through his extensive peer-reviewed publications in reputable journals and conferences, Chengjie Sun has significantly advanced the field of computer science and technology.

Accolades and Recognition

Assoc Prof Dr Chengjie Sun's exemplary contributions to academia have earned him prestigious accolades and recognition. In 2011, he received the First Prize of the Heilongjiang Science and Technology Award for his work on Sentence Level Pinyin Input Method in a Network Environment. His research endeavors and innovative approaches have consistently garnered acknowledgment from peers and experts in the field.

Impact and Influence

Assoc Prof Dr Chengjie Sun's research and teaching endeavors have had a profound impact on the academic community and industry alike. His publications in leading journals and conferences have contributed to the advancement of natural language processing, machine learning, and recommender systems. Furthermore, his collaborative efforts with esteemed institutions and professional memberships have facilitated knowledge exchange and interdisciplinary collaborations, fostering innovation and growth in the field.

Legacy and Future Contributions

As an Associate Professor at the Harbin Institute of Technology, Chengjie Sun continues to inspire and mentor future generations of computer scientists and researchers. His dedication to advancing knowledge and fostering excellence in research and teaching serves as a testament to his commitment to the academic community. Moving forward, Chengjie Sun's ongoing research endeavors and contributions are poised to shape the future of natural language processing technologies, recommender systems, and machine learning, leaving a lasting legacy in the field.

Citations

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