I am working on developing novel optimization methods for non-convex problems where gradients are unavailable or uninformative.
My background is in machine learning (PhD, 2018) and software engineering (MSc, 2014). My main interests lie in solving real-world problems using machine learning and optimization.
In the past I have worked on FX portfolio optimization, interpretable deep learning for finance, image question answering, text analysis, movie and news recommender systems, and building complex city models from satellite images and census data.
Check out my up-to-date list of publications at Google Scholar.