Tomasz Kozłowski

Tomasz Kozłowski is a researcher at Wrocław University of Science and Technology, actively involved in the Team of Advanced Data Analysis Methods (Zespół Zaawansowanych Metod Analizy Danych - ZZMAD). His work bridges engineering and data science, with a strong emphasis on industrial applications, particularly in mining and mechanical systems diagnostics.

Research Interests:

• Non-invasive diagnostics of machinery using NDT techniques
• Modeling of conveyor belt systems in surface and underground mines using DEM
• Signal processing for industrial monitoring
• Development of optimization algorithms for multi-criteria and multi-level engineering problems

His research projects focus on evolutionary optimization methods, multi-objective classifier training, and application-aware network optimization, reflecting a deep integration of computational intelligence with real-world engineering challenges.

Scientific Awards:

• Rector's Award for Scientific Achievements (2017)
• Rector's Award for Scientific Achievements (2018)
• Recognition in the Mining Success of the Year competition, category Innovation (2018)

Tomasz Kozłowski is engaged in advanced research projects involving black-box optimization, gene-inspired search techniques, and multi-layered network optimization. He contributes to the academic community through research platforms such as ORCID, ResearchGate, and the DONA scientific output system of PWr.

Laboratory and Research Teams:

• Team of Advanced Data Analysis Methods (ZZMAD)
• Machine Learning Team
• Computer Networks Team
• Teaching Team
• Metaheuristics Team