Assoc Prof Dr. Izabela Rojek | Artificial Intelligence | Best Researcher Award

Assoc Prof Dr. Izabela Rojek, Kazimierz Wielki University, Poland

Dr. Izabela Rojek is a prominent academic and researcher serving as the Head of the Department of Data Processing Methods and Tools and the Dean of the Faculty of Computer Science at Kazimierz Wielki University in Bydgoszcz, Poland. She holds the qualifications of Ph.D., D.Sc.Eng., and Associate Professor. Dr. Rojek’s research is centered on engineering sciences, specifically in Technical Informatics, Telecommunications, and Mechanical Engineering. Her extensive scientific output includes five books, 190 articles and chapters in monographs, and over 6000 points in the Ministry of Science and Higher Education (MNiSW) ranking, with a Hirsch index of 18 (Web of Science and Scopus) and 20 (Google Scholar). She has been recognized with 15 national and international awards, including four UKW Rector’s Awards and three foreign medals for outstanding inventions. Dr. Rojek’s contributions extend to 20 grants and innovation projects, and she actively participates in the Manufacturing Engineering Committee of the Polish Academy of Sciences, where she chairs the Manufacturing Digitisation Section.

Professional Profile:

ORCID

Suitability for Best Researcher Award:

Izabela Rojek is an exemplary candidate for the Best Researcher Award due to her outstanding contributions to the field of engineering sciences, particularly in Technical Informatics and Telecommunications. Her extensive publication record, high citation metrics, and significant involvement in national and international research projects highlight her impact on the field. Her leadership roles and innovative research further demonstrate her exceptional qualifications for this award.

Education:

Ph.D. in Engineering Sciences from Kazimierz Wielki University
D.Sc.Eng. (Doctor of Science in Engineering)
Associate Professor (Assoc. Prof.)

Work Experience:

Kazimierz Wielki University, Bydgoszcz
- Head of the Department of Data Processing Methods and Tools
- Dean of the Faculty of Computer Science

Additional Roles and Experience:

Member of the Manufacturing Engineering Committee of the Polish Academy of Sciences
Chair of the Manufacturing Digitisation Section of this Committee
Participation in the implementation of the IFS Applications IT system, including solution design, data migration, and training material preparation

Research and Contributions:

Authored 5 books and over 190 articles and chapters in monographs
Achieved over 6000 points in MNiSW (Polish Ministry of Science and Higher Education) evaluation
Total Impact Factor (IF) above 120
Hirsch index: h=18 (573 citations, Web of Science), h=18 (717 citations, Scopus), h=20 (1097 citations, Google Scholar)
Involved in 20 grants and innovation projects and 10 research topics
Recipient of 15 national and international awards, including 4 UKW Rector’s Awards and 3 foreign medals for outstanding inventions

Publication top Notes:

Enhancing 3D Printing with Procedural Generation and STL Formatting Using Python

Green Energy Management in Manufacturing Based on Demand Prediction by Artificial Intelligence—A Review

Use of Machine Learning to Improve Additive Manufacturing Processes

Review of the 6G-Based Supply Chain Management within Industry 4.0/5.0 Paradigm

Utilizing Selected Machine Learning Methods for Conicity Prediction in the Process of Producing Radial Tires for Passenger Cars

Dr. Xianchao Zhu, School of Artificial Intelligence and Big Data/Henan University of Technology, China

Dr. Xianchao Zhu is a Lecturer at the School of Artificial Intelligence and Big Data at Henan University of Technology, a position he has held since 2022. He completed his Ph.D. in Physics at the Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, where his research focused on “Abstraction-based Reinforcement Learning Algorithms and its Quantization.” Prior to his doctoral studies, Dr. Zhu earned a Master of Science in Computer Architecture from the School of Computer, Central China Normal University, with a thesis on “Research on Dimensionality Reduction Visualization Method of High-Dimensional Biological Data Based on Gradient Descent and Adaptive Learning.” His academic interests span artificial intelligence, reinforcement learning, and high-dimensional data analysis.

Professional Profile:

Education

Ph.D. in Physics
Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China
2018 – 2022
Thesis Title: Abstraction-based Reinforcement Learning Algorithms and its Quantization.
M.Sc. in Computer Architecture
School of Computer, Central China Normal University
2015 – 2018
Thesis Title: Research on Dimensionality Reduction Visualization Method of High-Dimensional Biological Data Based on Gradient Descent and Adaptive Learning.

Employment History

Lecturer
School of Artificial Intelligence and Big Data, Henan University of Technology
2022 – Present