I am a postoctoral researcher working on the formulation of hybrid thermodynamic models that combine physical knowledge with new methods from machine learning (ML). THe main focus hereby is are new fundamental equations of state (EOS) and transport property models for pure fluids and mixtures. As important part of this work, I’m engaged in the developement of thermodynamic open source libraries in the Julia language – including the new machine learning models (see Projects).
- Thermodynamics
- Machine Learning
- Julia Language
- Equations of State (EOS)
- Transport Properties
- Molecular Simulations
Postdoc and Group Leader “Machine Learning in Thermodynamics”, since 02/2025
Laboratory of Engineering Thermodynamics (LTD), RPTU Kaiserslautern, GermanyVisiting Researcher, 10/2025 – 12/2025
JuliaLab, CSAIL, Massachusetts Institute of Technology (MIT), USAScientific Associate, 06/2019 – 09/2019
Laboratory of Engineering Thermodynamics (LTD), RPTU Kaiserslautern, GermanyVisiting PhD Student, 06/2022 – 09/2022
IRTG 2057, UC Berkeley, USAVisiting Student, 10/2016 – 04/2017
Jianghan University, Wuhan, China
Ph.D. in Thermodynamics, 2024
RPTU University Kaiserslautern, GermanyThesis: Molecular Simulation and Entropy Scaling Modeling of Transport Properties
M.Sc. Computational Engineering, 2019
TU Kaiserslautern, GermanyB.Sc. in Mechanical Engineering, 2017
TU Kaiserslautern, Germany