Robert J. Webber
I am Ph.D. student advised by Jonathan Weare
at the Courant Institute of Mathematical Sciences.
You can reach me at rw2515 [AT] nyu [DOT] edu.
I research Monte Carlo algorithms that are used to estimate statistics of high-dimensional models.
My main approach is to analyze the variance of Monte Carlo algorithms and propose improvements to make these schemes more effective.
- I designed a Monte Carlo rare event sampling scheme that reduces the variance of extreme climate and weather statistics, including tropical cyclone statistics. 
- I helped design a Monte Carlo scheme for estimating the ground state wave function of the Schrödinger operator for fermion systems, which produced eficiency gains of up to a thousand compared to other leading methods. 
- In a manuscript currently in preparation, I derive asymptotic error expressions and central limit theorems to explain the error in sequential Monte Carlo and connect these theoretical results to optimal implementation in practice.