Summary
Caden Hewlett is a statistics graduate student and research assistant at the University of British Columbia with nine years of professional experience spanning statistics research, cloud software development, and teaching. He focuses on non-parametric methods, Bayesian statistics, and hybrid/gradient-free evolutionary algorithms, blending theoretical rigor with practical implementation. At UBC he has supported courses from elementary statistics to advanced Bayesian topics while driving data modernization work in industry. Caden brings a hands-on approach to experimental algorithm design and enjoys translating complex probabilistic ideas into reproducible code and teaching material. Based in British Columbia, he pairs academic curiosity with applied engineering experience, often exploring gradient-free optimizers that bridge research and production use cases.
8 years of coding experience
Master's degree, Statistics, Master's degree, Statistics at The University of British Columbia
Rockridge Secondary School