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Prof. Jacek Kluska | Engineering | Excellence in Research

Professor at Rzeszow University of Technology, Poland.

Prof. Jacek Kluska is a distinguished academic and researcher specializing in computational intelligence, fuzzy control systems, and machine learning applications. He has made significant contributions to the fields of technical informatics and telecommunications through his extensive research, administrative leadership, and editorial roles. Currently, he serves as a professor at Rzeszów University of Technology and holds key positions in the Polish Academy of Sciences, influencing research policies and technological advancements. With a career spanning over four decades, Prof. Kluska has collaborated with top European universities, contributed to high-impact research journals, and played a crucial role in shaping intelligent systems research. His international exposure, leadership roles, and dedication to advancing automation, artificial intelligence, and fuzzy modeling make him a strong contender for prestigious research awards.

Professional Profile:

Education

Prof. Jacek Kluska completed his M.Sc. (Eng.) at Wroclaw University of Technology, Poland, in 1977, where he developed a strong foundation in technical cybernetics and computational methodologies. He pursued his Ph.D. in Technical Cybernetics from the same university in 1983, focusing on intelligent control systems and stability analysis. His academic journey reflects his deep commitment to mathematical modeling, automation, and artificial intelligence applications. Over the years, Prof. Kluska has continuously expanded his knowledge by collaborating with leading technical institutions across Europe, gaining insights into advanced computational techniques. His academic background in technical informatics, fuzzy modeling, and AI-driven diagnostics has been instrumental in shaping his research career. The rigorous training and research exposure he gained during his doctoral studies laid the foundation for his later contributions to intelligent systems and computational intelligence.

Professional Experience

Prof. Jacek Kluska has built an impressive academic career at Rzeszów University of Technology, where he has served in multiple leadership capacities. He became an associate professor in 1995 and was promoted to full professor in 2010. From 1996 to 2002, he served as Vice-Dean of the Faculty of Electrical Engineering and Computer Science, overseeing academic programs and research initiatives. Later, from 2005 to 2012, he was Vice-President for Research, leading university-wide research strategies and collaborations. Prof. Kluska has also contributed to international research networks, making short-term research visits to prestigious institutions such as the University of Birmingham, National Technical University of Athens, and the University of Florence. He is currently the Chairman of the Intelligent Systems Section at the Polish Academy of Sciences and Vice-Chairman of the Scientific Council of the Institute of Systems Research of PAS, playing a key role in shaping Poland’s AI and automation research policies. His professional career reflects his dedication to bridging academic research with technological advancements and fostering international collaborations in computational intelligence.

Research Interests

Prof. Jacek Kluska’s research interests lie at the intersection of fuzzy control systems, computational intelligence, machine learning, and AI-driven diagnostics. His work focuses on stability analysis of fuzzy systems, fuzzy Petri nets, and advanced modeling techniques in intelligent systems. He has significantly contributed to the development of AI-driven decision-making models, particularly in medical diagnostics and technical automation. His research explores intelligent algorithms that improve system efficiency, fault detection, and predictive analytics. By integrating mathematical models with real-world applications, Prof. Kluska has played a key role in enhancing automation processes in industrial, healthcare, and technical domains. His interests also include hybrid AI techniques, deep learning models for intelligent computing, and fuzzy logic applications. As the field of AI evolves, he continues to develop innovative methodologies for improving system robustness and decision-making in complex environments.

Research Skills

Prof. Jacek Kluska possesses expertise in computational modeling, machine learning algorithms, fuzzy logic, and artificial intelligence applications. His proficiency in stability analysis of intelligent systems, fuzzy control mechanisms, and pattern recognition has made him a leading figure in the field. He has a deep understanding of mathematical optimization, neural networks, deep learning frameworks, and AI-based diagnostics. His technical skills include algorithm development for intelligent automation, simulation of fuzzy control networks, and predictive modeling using computational intelligence techniques. Over the years, he has demonstrated exceptional problem-solving abilities, technical analysis expertise, and system design capabilities. His experience in collaborative research, interdisciplinary studies, and AI-based data processing has allowed him to contribute significantly to cutting-edge advancements in intelligent control systems and real-time automation applications.

Awards and Honors

Throughout his career, Prof. Jacek Kluska has received numerous recognitions for his contributions to computational intelligence, automation, and artificial intelligence research. As a senior academic, he holds esteemed positions within the Polish Academy of Sciences, including serving as Chairman of the Intelligent Systems Section. His leadership in scientific committees, editorial boards, and research councils has earned him accolades for his contributions to AI-driven decision-making models and fuzzy systems. He has been invited to international conferences, workshops, and symposiums, where he has delivered keynote lectures on AI applications in technical diagnostics and automation. His work has also influenced policy development in intelligent systems research, strengthening Poland’s presence in AI and machine learning innovations. His professional achievements and international collaborations highlight his outstanding contributions to the field of computational intelligence.

Conclusion

Prof. Jacek Kluska’s exceptional academic career, leadership roles, and pioneering research in computational intelligence make him a highly deserving candidate for the Best Researcher Award. His contributions to fuzzy control systems, AI-based diagnostics, and intelligent automation have had a profound impact on both academia and industry. His leadership at the Polish Academy of Sciences, extensive research collaborations, and editorial roles further reinforce his global influence in intelligent systems research. While his achievements in theoretical and applied AI research are outstanding, strengthening his publication impact, patents, and industrial collaborations could further solidify his standing. Overall, Prof. Kluska’s dedication to advancing artificial intelligence, machine learning, and computational methodologies makes him a strong contender for prestigious research awards and global recognition.

Publication Top Notes

  • Model reference adaptive controller with interpretable fuzzy rules for linear MIMO systems (Information Sciences, 2024) [DOI: 10.1016/j.ins.2024.121189]
  • CACP: Classification Algorithms Comparison Pipeline (SoftwareX, 2022) [DOI: 10.1016/j.softx.2022.101134]
  • Applications of Computational Intelligence Methods for Control and Diagnostics (Studies in Systems, Decision and Control, 2021) [DOI: 10.1007/978-3-030-48587-0_22]
  • Extremely simple classifier based on fuzzy logic and gene expression programming (Information Sciences, 2021) [DOI: 10.1016/j.ins.2021.05.041]
  • FPGA-Embedded Anomaly Detection System for Milling Process (IEEE Access, 2021) [DOI: 10.1109/ACCESS.2021.3110479]
  • Adaptive fuzzy control of state-feedback time-delay systems with uncertain parameters (Information Sciences, 2020) [DOI: 10.1016/j.ins.2020.06.015]
  • PID-Like adaptive fuzzy controller design based on absolute stability criterion (IEEE Transactions on Fuzzy Systems, 2020) [DOI: 10.1109/TFUZZ.2019.2908772]
  • Prediction of 10-year Overall Survival in Patients with Operable Cervical Cancer using a Probabilistic Neural Network (Journal of Cancer, 2019) [DOI: 10.7150/jca.33945]
  • Condition monitoring in Industry 4.0 production systems (Procedia CIRP, 2019) [DOI: 10.1016/j.procir.2019.02.012]
  • Prediction of 5-year overall survival in cervical cancer patients using computational intelligence methods (BMC Cancer, 2017) [DOI: 10.1186/s12885-017-3806-3]
Jacek Kluska | Engineering | Excellence in Research

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