Image from William Putman/NASA Goddard Space Flight Center
I mainly use Python with the scientific stack of libraries.
I created an online course on High Performance Python.
It includes profiling, vectorisation with NumPy, compiling with Numba, parallelisation with Dask and Ray, and using GPUs with JAX and CUDA/Numba.
Numerical atmospheric models#
I taught and provided support for a complex air quality model, WRFChem (Bash and Fortran).
I used machine learning models to predict optimum emission reduction strategies to improve air quality and public health in China.
I created an online course on Introduction to Machine Learning.
It covers fundamentals, machine learning with scikit-learn, deep learning with TensorFlow / Keras and PyTorch / PyTorch Lightning, data pipelines, model tuning, transfer learning, and distributed training.
Useful learning resources#
Here are some great learning resources for topics in data science, software engineering, and machine learning that I’ve found helpful.