Ariel Goodwin

I am pursuing a Ph.D. in Applied Mathematics at Cornell University, before which I completed my B.Sc. at McGill University in Joint Honours Mathematics and Computer Science. In 2020 I collaborated with Tim Hoheisel and Michael P. Friedlander on a research project about the variational analysis and efficient computation of epigraphical projections in nonsmooth optimization. In 2021 I continued working with Tim Hoheisel, Rustum Choksi, Yakov Vaisbourd, and Carola-Bibiane Schöenlieb on an information-theoretic approach for regularizing ill-posed inverse problems. Check out my Projects for more details.

I am interested in continuous optimization and variational analysis with an emphasis on geometry, as well as probability, algorithm design, and applications thereof to data science, scientific computing, machine learning, and finance.