Kuo-Ching Ying | Metaheuristics | Best Researcher Award

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

National Taipei University of Technology, Taiwan

Author Profiles

orcid

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.

💼 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.

📚 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.

💡 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

Sogand Dehghan | social network analysis | Best Innovation Award

Ms. Sogand Dehghan | social network analysis | Best Innovation Award

Ms. Sogand Dehghan at K. N. Toosi University of Technology, Iran

👨‍🎓Professional Profiles

Orcid Profile

Google Scholar  Profile

👩‍💻 Summary

Ms. Sogand Dehghan an Information Technology specialist with expertise in data analysis and software development. My work primarily focuses on collecting, cleaning, and analyzing data from various sources to create actionable reports and dashboards for organizational decision-making. I am passionate about using data-driven strategies to help businesses achieve their goals, with a particular interest in social media analysis and its alignment with organizational objectives. Additionally, I enjoy developing data-driven software solutions that enhance operational efficiency.

🎓 Education

Ms. Sogand Dehghan earned my Master’s Degree in Information Technology from K.N. Toosi University of Technology (2019-2022) and my Bachelor’s Degree in Information Technology with a grade of 97% from Payame Noor University (2012-2016). My thesis, titled “Provision of an Efficient Model for Evaluation of Social Media Users Using Machine Learning Techniques,” focused on leveraging machine learning to assess social media engagement and user behavior.

💼 Professional Experience

Ms. Sogand Dehghan currently hold two key roles: as an Instructor at National Skills University, where I teach courses on Advanced Programming and Data Analysis (since Sep 2024), and as a Data Analyst at GAM Arak Industry, where I focus on data mining, machine learning, and visualizing data insights using tools like Power BI, Python, SQL Server, and SSRS (since Jan 2024). Additionally, I serve as a Software Developer at GAM Arak Industry, working with C#, ASP.NET Core, and SQL Server to build scalable software solutions (since Apr 2023). In my previous role at Kherad Sanat Arvand (Apr 2022 – Jun 2023), I honed my skills in data analysis and dashboard development.

📚 Academic Citations

My research has been published in prestigious journals. My paper, “The Credibility Assessment of Twitter Users Based on Organizational Objectives,” was published in Computers in Human Behavior (Sep 2024), where I developed a model for assessing the credibility of Twitter users by integrating profile data with academic sources like Google Scholar. Another notable publication, “The Evaluation of Social Media Users’ Credibility in Big Data Life Cycle,” appeared in the Journal of Information and Communication Technology (Sep 2023), in which I reviewed existing frameworks for evaluating social media user credibility.

🔧 Technical Skills

My technical skill set includes expertise in C#, ASP.NET, Python, and SQL Server for software development. I specialize in Data Visualization with Power BI, Data Mining, Machine Learning, and Social Network Analysis. Additionally, I have a solid foundation in Text Mining and Data Modeling, which enables me to provide comprehensive solutions for data-driven challenges in various organizational contexts.

👨‍🏫 Teaching Experience

As an Instructor at National Skills University, I teach Advanced Programming and Data Analysis. I focus on equipping students with the skills needed to thrive in the data-driven world of technology. My approach integrates real-world data problems with theoretical knowledge to help students apply their learning in practical scenarios.

🔍 Research Interests

My research interests lie in the intersection of Machine Learning and Social Network Analysis. I am particularly interested in developing models to evaluate social media user credibility, integrating heterogeneous data sources for organizational decision-making, and exploring the broader implications of big data in evaluating trust and influence within social networks.