Optimization Engineer
Howard specializes in optimization algorithms for big data problems, particularly the creation, training, and evaluation of models that are data-driven and require hard constraints be satisfied (e.g. large systems of equations for physical systems).
Recent Explainable AI work, published in Nature's Scientific Reports
Howard writes and creates graphics for aspiring mathematicians.
A friendly introduction to real analysis
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.
