Mark W_

Developed a failure detection algorithms for industrial Designing and applying methods for extraction of information from sensor data. Developments of algorithms and test procedures using machine learning, deep learning, or other statistical techniques for integration as a Minimum Viable Product(MVPs). Wrote well-tested code to ensure software reliability and scalability. Managed and maintained services using Kubernetes, Docker, FastAPI, and Grafana for monitoring.

Designing and applying methods for extraction of information from sensor data. Developments of algorithms and test procedures using machine learning, deep learning, or other statistical techniques for integration as a Minimum Viable Product(MVPs).

>Under the system engineering department, I implemented, simulated wind turbines using a Lifting Line model which showed favorable results with a more computational costly model (CFD). >Analyzed and Visualized large datasets of wind turbine operational, 3D CFD simulation using computer-aided tools such as Python(Pandas, Numpy, etc ), TECplot, ParaView. >Explicitly defined technical and best practices of Lifting Line Free wake mode. >Performed optimization of workflow using scripting languages like Python.

Wind potential, Aerodynamics & Loading of wind turbines, electrical and control issues, certification. Wind Turbine design, wind farm study, offshore, Economics & Environmental issues

Photovoltaics, Solar Thermal, Biomass, hydro energy, Storage Technologies, Energy Meteorology, Energy Systems, socio-economics fundamentals

Statistical Physics, Solar Energy Techniques, Vibrations and Waves, Engineering Drawing, Mathematical Methods, Electromagnetic Fields