Summary
Johannes Hendriks is a Staff Data Scientist with eight years' experience applying optimisation, control and probabilistic machine learning to real-world energy systems, currently focused on CNI battery optimisation at Hachiko. He blends a strong academic foundation—PhD work and postdoctoral research in Bayesian inference, Hamiltonian Monte Carlo and system identification—with hands-on product impact across startups like Evergen and consultancies such as GRIDSIGHT. Johannes excels at turning uncertainty-aware models into actionable control strategies that improve energy asset performance and grid integration. He is particularly drawn to problems at the intersection of control engineering, Bayesian statistics and ML, and has taught and developed practical courses on machine learning for engineers. Colleagues describe him as evidence-driven and outcome-focused, able to translate complex math into measurable operational gains. Based in Newcastle-Maitland, Australia, he brings both deep research rigor and pragmatic systems engineering experience to decarbonisation challenges.
8 years of coding experience
10 years of employment as a software developer
Doctor of Philosophy - PhD Mechatronics Robotics and Automation Engineering, Doctor of Philosophy - PhD Mechatronics Robotics and Automation Engineering at University of Newcastle
Doctor of Philosophy - PhD (Exchange) Machine learning, Doctor of Philosophy - PhD (Exchange) Machine learning at Uppsala University
English