About Me

I am a 4th year PhD student at the Department of Statistics & Data Science at UCLA working with Guido Montufar on the mathematics of deep learning.

Recent News:

• I attended the wonderful SIAM AG25 conference at UW Madison in July, SIAM Conference on Applied Algebraic Geometry, and presented my results on the application of algebraic tools to understanding the geometry of the space of value functions in reinforcement learning problems.
• I attended the wonderful workshop given by IPAM at UCLA, Theory and Practice of Deep Learning.
• I attended workshops as part of the IMSI’s long program “Algebraic Statistics and Our Changing World” at the University of Chicago.
• I was accepted to be part of the G-RIPS program given by the IPAM, an NSF institute at UCLA. G-RIPS took place at the Zuse Institute Berlin, located at the Freie Universität Berlin. My work with Stefan Zachow’s group and an industry sponsor, 1000Shapes GmbH, concerned properties of statistical shape models and new approaches via neural networks including the variational autoencoder architecture introduced by Tamaz Amiranashvili.