# Applied Math Research Scientist

Howard specializes in the construction and analysis of models and algorithms for machine learning problems. Specifically, he takes high-level problems from stakeholders and translates them into mathematical terms to develop software tools (in Python) in a way that is explainable, safe, scalable, data-driven and satisfies provided constraints (e.g. large systems of equations for physical systems). He has used these skills in several industries (e.g. medical imaging, e-commerce, animation), coordinating with both engineering and product stakeholders.

Howard writes and creates graphics for aspiring mathematicians. He created Typal Academy to publish academic research and teach introductory real analysis ("advanced calculus").

Howard completed his PhD at UCLA under the advisement of Wotao Yin and Stanley Osher. Below are his notes for qualifying exams in the math program at UCLA.

Applied Differential Equations Notes

Howard enjoys activities that require focus, especially running, powerlifting, and slacklining.