Konrad Wojdan

Konrad Wojdan is a Lecturer at the Institute of Heat Engineering within the Faculty of Power and Aeronautical Engineering at Warsaw University of Technology. His research spans interdisciplinary applications of artificial intelligence, with particular expertise in optimization algorithms for energy systems and medical diagnostics. He maintains an active research program with publications extending into 2025, demonstrating ongoing scholarly contributions in both engineering and medical fields.

Dr. Wojdan's research interests focus on developing and applying Artificial Intelligence and optimization algorithms in energy, heating and gas sectors, with significant contributions to district heating network optimization and combustion process control. His work also extends to medical applications, particularly in analyzing neurological conditions like tuberous sclerosis complex using advanced data science methods. This unique interdisciplinary approach bridges engineering and medical research, creating novel methodologies applicable across domains.

Analysis of his recent publications reveals a consistent pattern of applying immune-inspired optimization techniques to complex engineering problems, while simultaneously developing AI-based diagnostic tools for medical applications. His work on district heating networks demonstrates practical implementation of AI for energy efficiency, while his medical research contributes to early diagnosis and intervention strategies for neurological conditions in infants.

• Active researcher with publications through 2025
• Interdisciplinary work spanning energy engineering and medical diagnostics
• Specialized in immune-inspired optimization algorithms
• Develops practical AI applications for district heating systems

Dr. Wojdan supervises diploma theses focused on Data Science methods in energy, heating and gas industries, requiring students to develop programming skills in Python, R, or Julia. His teaching emphasizes the practical application of computational methods to real-world engineering challenges, preparing students for careers at the intersection of traditional engineering and modern computational techniques.