Philipp Fleck

Philipp Fleck is a researcher and PhD student at the University of Applied Sciences Upper Austria's Research Center Hagenberg, affiliated with the Center of Excellence for Smart Production and HEAL research group. His work focuses on digital transformation within ICT and production systems, leveraging optimization techniques for industrial applications.

His academic background includes:

• PhD in Computer Science (ongoing since 2021)
• Master of Science in Software Engineering (2013-2015)
• Bachelor of Science in Software Engineering (2010-2013)
• IT-HTL diploma (2005-2010)

Fleck specializes in dynamic optimization environments, genetic programming, and machine learning applications for production systems. His research develops adaptive algorithms for real-time decision-making in logistics and manufacturing, with emphasis on tree search methods, storage optimization, and evolutionary computation. Current work integrates machine learning with heuristic optimization for dynamic symbolic regression and transport-lot assignment problems.

His publication trends show concentrated focus on evolutionary computation applied to industrial challenges, particularly dynamic environments requiring real-time adaptation. Recent work bridges genetic programming with production logistics and machine learning update strategies, demonstrating strong interdisciplinary connections between computer science and operations research.

No scientific awards are documented in available sources.

Fleck has secured significant grant funding through Austrian research programs, including the Josef Ressel Center for Adaptive Optimization in Dynamic Environments (2019-2024), Fakultätsübergreifendes Institut für intelligente Produktion (2014-2019), and Josef Ressel Center for Heuristic Optimization (2008-2013). These projects address priority rules, distributed intelligence, and rapid prototyping in production systems.

He operates within the HEAL research ecosystem at Hagenberg's Center of Excellence for Smart Production, collaborating with interdisciplinary teams on digital transformation initiatives. His work integrates with the university's broader Strength Area ICT framework, focusing on practical implementations of optimization algorithms in production environments.