Roland Platz

Roland Platz

Contact

  • Assistant Professor, Mechanical and Aerospace Engineering
  • PhD (Dr.-Ing.), Technical University of Darmstadt
  • MS (Dipl.-Ing.), Technical University of Berlin

Biography

Dr. Roland Platz’s research interests include state control, health and condition monitoring, and uncertainty quantification (UQ) in structural mechanical dynamic systems, such as trusses and their members, suspension legs, machines, and their supports in architectural, manufacturing, automotive, and aerospace engineering. His work includes mathematical modeling, numerical simulation, and experimental testing. He likes to expand his research activities by developing adequate model-form decision-making approaches based on physical axioms, empirical data, and machine learning algorithms, or a combination in hybrid approaches, such as physics-informed neural networks (PINN).

Before joining Michigan Technological University in August 2025, Dr. Platz worked as a research associate professor in Motion Dynamics and Design at Deggendorf Institute of Technology, and as the head of the Technology Center Weissenburg in Germany since March 2021. Prior to that, he worked on vibration isolation problems at Penn State University as a visiting scholar at the Architectural Engineering Department from October 2019 to February 2021.

Dr. Platz was a scientific group manager at the Fraunhofer Institute for Durability and System Reliability (LBF) in Darmstadt between 2017 and 2019. He was responsible for structural and reliability testing of high-voltage batteries. From 2008, he coordinated the process to establish and foster the 12-year-lasting Collaborative Research Center (SFB 805) “Controlling Uncertainty in Load-Carrying Structures in Mechanical Engineering”, funded by the German Research Foundation (DFG), at the LBF in cooperation with the Technical University of Darmstadt. In 2016, he was an Adjunct Professor at the College of Engineering and Science at Clemson University.

Links of Interest

Research Interests

  • Active Stability Control
  • Active and Semi-Active Vibration Control
  • Semi-Active Load Path Redistribution Control
  • Active Crack Propagation Reduction
  • Condition Monitoring
  • Model-Form Uncertainty
  • Physics-Informed Neural Networks (PINN)

Areas of Expertise

  • Structural Mechanics and Dynamics
  • Machine Dynamics
  • Rotor Dynamics
  • Fracture Mechanics
  • Mathematical Modeling, Numerical Simulation, and Experimental Testing
  • Vibration Testing
  • Active State Control for Structural Systems
  • Model-Based Health and Fault Identification
  • Uncertainty Quantification
  • Reliability Analysis