Johannes completed his B.E. (mechatronics) and Ph.D. (Mechanical engineering) at the University of Newcastle, Austraila, in 2015 and 2020, respectively. Since that time, Johannes has worked at the University of Newcastle as a research associate with the mechatronics department.
Johannes' research interests lie on the intersection of Engineering, Machine learning, and data science. His PhD involved developing novel three-dimensional strain tomography algorithms for studying residual stress caused by manufacturing processes. These algorithms are analogous to medical computed tomography, and they required tailoring machine learning methods to satisfy physical constraints.
As a research associate, Johannes' is focussed on applying recent statistical methods from data science, such as Hamiltonian Monte Carlo, to system identification problems. The developed tools will allow the design of autonomous control systems taking into account uncertainty in the data.
I am currently collaborating on projects with Carl Jidling and Professor Thomas Schön from Uppsala University in Sweden. I have also collaborated on experiments at the Japan Proton Accelerator Research Complex (JPARC) and Australia's Nuclear Science and Technology Organisation with Dr Vladimir Luzin (ANSTO), Dr Oliver Kirstein (ESS, Sweden), Dr Anton S. Tremsin (Berkeley), and Dr Takenao Shinohara (JPARC).
Johannes has taught into a variety of undergraduate courses at the University of Newcastle, Australia. Currently, he is developing ENG3300 (Machine Learning for Engineers), which covers regression and classification using logistic regression, linear regression, discriminant analysis, Random forests, bagging and boosting, deep neural networks, and convolutional neural networks. The course has a special focus on ensuring robust results and that engineering constraints are satisfied.