My primary research interests are in physics simulations for computer graphics. I develop numerical simulations to synthesize sound for computer animations.
I was formerly a full-time software engineer at Microsoft, where I worked on the Office Graphics (PowerPoint, Word, Excel) team. I graduated in 2015 with an AB in Physics from Princeton University, where I was advised by Jason Fleischer. I have also worked on research projects at Columbia University, the Priceton Plasma Physics Lab, and Adobe Research.
Outside of work, I also enjoy board games, bridge, hiking, and food.
We propose a physically based, multi-scale reduced simulation method to synthesize nonlinear thin-shell sounds. We first split nonlinear vibrations into two scales, with a small low-frequency part simulated in a fully nonlinear way, and a high-frequency part containing many more modes approximated through time-varying linearization. This allows us to capture interesting nonlinearities in the shells’ deformation, tens of times faster than previous approaches. Furthermore, we propose a method that enriches simulated sounds with wave turbulent sound details through a phenomenological diffusion model in the frequency domain, and thereby sidestep the expensive simulation of chaotic high-frequency dynamics. We show several examples of our simulations, illustrating the efficiency and realism of our model.
Our algorithm performs a decomposition of the image into basis functions and searches for the coefficients that yield the flattest output intensity pattern. This algorithm takes advantage of the fact that a relatively small number of basis elements can store the majority of the information in the image. Popular phase retrieval methods such as the Gerchberg–Saxton algorithm can only converge to the phase image under light that is sufficiently coherent. From our simulations, we find that our method consistently produces correlations of over 99% with the original phase image, using either incoherent or coherent light and only 10% as many basis elements as the number of pixels in the image. We believe this result is a strong indication that this method will be able to reliably retrieve a direct phase image in the laboratory.