Jerzy Montusiewicz | Computer Science and Artificial Intelligence | Best Researcher Award

Mr Jerzy Montusiewicz, Lublin University of Technology, Department of Computer Science, Poland

Based on the research achievements of Prof. Jerzy Montusiewicz, he appears to be a strong candidate for the Best Researcher Award. Here’s a summary of his contributions and achievements:

Publication profile

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Research Summary for Best Researcher Award

1. K-medoids Clustering and Fuzzy Sets for Isolation Forest
Montusiewicz co-authored this 2021 IEEE International Conference on Fuzzy Systems paper on clustering and fuzzy sets, highlighting advanced methodologies in data analysis. This work is cited for its impact on clustering techniques in complex datasets.

2. Preparation of 3D Models of Cultural Heritage Objects to be Recognized by Touch by the Blind—Case Studies
In this 2022 Applied Sciences publication, Montusiewicz contributed to developing 3D models of cultural heritage objects accessible to the visually impaired, showcasing his commitment to inclusivity in digital heritage.

3. Comparative Analysis of Digital Models of Objects of Cultural Heritage Obtained by the “3D SLS” and “SfM” Methods
This 2021 study, published in Applied Sciences, explores the comparative effectiveness of different 3D scanning methods for cultural heritage preservation, reflecting Montusiewicz’s expertise in digital preservation techniques.

4. 3D Scanning and Visualization of Large Monuments of Timurid Architecture in Central Asia—A Methodical Approach
Montusiewicz’s 2020 Journal on Computing and Cultural Heritage article demonstrates innovative methods for scanning large historical monuments, emphasizing his contributions to preserving Central Asian architectural heritage.

5. Virtual and Interactive Museum of Archaeological Artefacts from Afrasiyab—An Ancient City on the Silk Road
This 2020 paper in Digital Applications in Archaeology and Cultural Heritage presents the creation of a virtual museum for archaeological artefacts, illustrating Montusiewicz’s role in advancing digital tools for archaeology.

6. A Decomposition Strategy for Multicriteria Optimization with Application to Machine Tool Design
Montusiewicz’s 1990 publication in Engineering Costs and Production Economics addresses optimization strategies in machine tool design, demonstrating his early contributions to engineering and optimization techniques.

7. Structured-Light 3D Scanning of Exhibited Historical Clothing—A First-Ever Methodical Trial and Its Results
This 2021 Heritage Science study, co-authored by Montusiewicz, represents a pioneering effort in 3D scanning of historical clothing, marking a significant advancement in the field of heritage science.

8. Documenting the Geometry of Large Architectural Monuments Using 3D Scanning—The Case of the Dome of the Golden Mosque of the Tillya-Kori Madrasah in Samarkand
Montusiewicz’s research, published in 2022, focuses on documenting the geometry of significant architectural monuments, highlighting his continued impact on architectural preservation through advanced scanning techniques.

Prof. Montusiewicz’s diverse research, spanning from advanced 3D scanning techniques to the preservation of cultural heritage, underscores his significant contributions to the fields of computer graphics and digital preservation. His innovative approaches and practical applications make him an exemplary candidate for the Best Researcher Award.

Research focus

Based on the provided publications, the research focus appears to be in digital heritage preservation and 3D scanning technologies. The work of J. Montusiewicz and collaborators emphasizes creating and analyzing 3D models of cultural heritage objects, including methods for blind accessibility and the application of scanning technologies for historical artifacts and architecture. This includes comparative studies of different scanning methods and their effectiveness, as well as the development of interactive digital museums. Their research contributes significantly to both the preservation of cultural heritage and the advancement of technological applications in archaeology. 🏛️🔍📏

Publication top notes

K-medoids clustering and fuzzy sets for isolation forest

Preparation of 3D models of cultural heritage objects to be recognised by touch by the blind—case studies

Comparative analysis of digital models of objects of cultural heritage obtained by the “3D SLS” and “SfM” methods

3D Scanning and Visualization of Large Monuments of Timurid Architecture in Central Asia–A Methodical Approach

Virtual and interactive museum of archaeological artefacts from Afrasiyab–an ancient city on the silk road

A decomposition strategy for multicriteria optimization with application to machine tool design

Structured-light 3D scanning of exhibited historical clothing—a first-ever methodical trial and its results

Publication profile

Educational Background 📚

Mr. Fatemi has a robust academic foundation with a Ph.D. in Industrial and Systems Engineering from Auburn University, where he has maintained a perfect GPA of 4.0. His ongoing M.Sc. in Data Science further complements his expertise, and he also holds an M.Sc. and B.Sc. in Industrial and Systems Engineering from Tarbiat Modares University and the University of Kurdistan, respectively. This diverse and interdisciplinary educational background supports his innovative research in healthcare and systems optimization.

Research Experience and Contributions 🔬

Mr. Fatemi’s research is both extensive and impactful. His recent work involves using machine learning and network analysis to address critical healthcare issues such as low birth weight prediction, racial disparities in maternal outcomes, and cardiovascular death among liver transplant recipients. These projects showcase his ability to apply advanced analytical methods to real-world problems, significantly contributing to the fields of healthcare and data science. His studies have utilized cutting-edge techniques such as Recursive Feature Elimination, SHapley Additive exPlanations (SHAP), and network feature analysis, highlighting his technical prowess and innovation.

Publications and Academic Output 📝

Mr. Fatemi has authored several peer-reviewed articles, contributing to reputable journals like Frontiers in Public Health and Journal of Multidisciplinary Healthcare. His research on the stress and compensation perceptions of frontline nurses during the COVID-19 pandemic, as well as his work on hospital smart notification systems, demonstrates his commitment to improving healthcare environments and outcomes. His publications reflect his ability to tackle diverse and pressing issues, making him a significant contributor to the academic community.

Technical and Academic Skills 🛠️

Mr. Fatemi’s technical skills are impressive, encompassing data analysis tools like Python, R, and SQL, and specialized software for simulation and optimization. His expertise in machine learning, statistical learning, and network analysis is evident in his research outputs, further establishing his credibility as an innovative researcher.

Conclusion

Mr. Yasin Fatemi’s strong educational background, extensive research experience, and impactful contributions to healthcare and data science make him an excellent candidate for a Best Researcher Award. His ability to apply complex analytical techniques to critical issues in healthcare and his consistent academic excellence underscore his suitability for this recognition.