About Us
At Rafinex we have a passion to develop advanced algorithms for an engineer’s toughest design challenges.
Who we are
Rafinex is a company that is singularly dedicated to providing advanced numerical models for challenging engineering applications, ready to use and packaged as beautiful, intuitive cloud simulation apps with built-in expert know-how.
By combining best-in-class algorithms and AI-assistance when needed, we are striving to find and provide the world’s most advanced and most appropriate numerical methods for your challenging needs.
Rafinex goes beyond current market tools by accounting for real-life variability using uncertainty quantification methods and by considering manufacturability; allowing safe and profitable usage by everyone in engineering design.
The Team
Michal Habera, PhD
Michal Habera is an expert in Finite Element methods and their application in the context of non-linear material models. Over the past 6 years, he has made significant contributions to the development of leading open-source finite element toolchains. He holds a PhD in Civil Engineering from the University of Luxembourg, where he focused on developing a high-performance model for aging concrete structures.
Currently, Michal holds an Industrial Fellowship funded by the Luxembourg National Research Fund. In his role at Rafinex, he is responsible for integrating state-of-the-art optimization methods into the company’s portfolio.
André A. R. Wilmes, PhD
André Wilmes has developed numerical methods for simulating composite nano-materials at Imperial College London and has given guest seminars at leading research centers including NASA and TU Munich.
He has experience as an R&D project manager in the ceramics and manufacturing industries, where he developed new simulation methods and experimental prototype processes in a variety of material topics ranging from fracture mechanics to optics.
Johannes Neumann, Dr. rer. nat.
Johannes Neumann researched physical simulations with stochastic uncertainties and robust topology optimization at the Weierstrass Institute for Applied Analysis and Stochastics (WIAS) in Berlin.
His focus on accelerating the numerical calculation unlocked the practical applicability of stochastic methods in a business environment. He has a wide network of scientific contacts across Europe in the field of numerical mathematics.
Martin Řehoř, PhD
Martin Řehoř received his doctoral degree in mathematical and computer modelling from Charles University in Prague and Heidelberg University. Martin has researched diffuse interface models in the context of physical simulations of multiphase flow. He worked on the simulation of viscoelastic materials in a PostDoc program with the University of Luxembourg and Goodyear S.A.. Martin’s speciality is modelling, simulation and optimisation of complex fluids via advanced numerical methods.
Miguel Mattos, PhD
Miguel Matos is specialised in advanced simulation methods including non-linear FEA and topology optimisation. Miguel received his PhD in aeronautical engineering from Imperial College London, where he studied the multiscale and multiphysics response of nanocomposites. At Airbus UK, Miguel implemented composite failure criteria and damage propagation models for large scale models.
Other focus areas include data science and analysis where Miguel trained and deployed artificial neural networks for complex material modelling, as well as Monte-Carlo analyses.
Jesus Blanco
Jesus has more than two decades of experience in Finite Element Analysis and consulting engineering services across automotive, defence and consumer product applications. His knowledge, both in pragmatic industrial applications of tools, as well as the curiosity for the theoretical breakthroughs that power Rafinex’ solutions, represents an invaluable addition.
At Rafinex he leads all algorithm testing and application engineering for our customers. His wealth of simulation experience pushes the team to make our products meet fast workflows and short timelines for product delivery, as seen in everyday’s CAE production environments.