Kun Marhadi

Background

About Kun Marhadi

Wind energy expert in the area of wind turbine reliability, condition monitoring, operation and maintenance. Developing AI algorithm for automatic detection and prognosis of wind turbine failures, where faults can be detected as early as one year before functional breakdown. Maximize wind turbine uptime. Condition monitoring specialist; doing research and development of condition monitoring system for wind turbines and other rotating machines. Specifying product requirements, and creating remote monitoring strategies for wind turbines (implemented in more than turbines) and other machines. Collaborate to create software solutions for machine vibration data acquisition unit and its back end remote monitoring. Experienced in automation, instrumentation, sensors, vibration, and testing. Have experience in using computation to solve problems in wide range of fields, such as geophysics, statistics, and aerospace engineering. PhD in reliability design optimization involving deterministic and stochastic methods, non-convex problems, as well as uncertainty quantification. Generally interested in using computation and machine learning to tackle problems in science and engineering. Specialties: Machine Learning, Machine vibration, condition monitoring, signal processing, optimization, non-deterministic approach in structural design, Bayesian inference, numerical methods, engineering mechanics. Programming Language: R, Python, Fortran, C, Matlab, MPI, OpenMP