Hello there!

I am a final-year Ph.D. Candidate in Computer Science at Columbia University, advised by Prof. Eitan Grinspun and Prof. Changxi Zheng. My research interests include Physics-based Simulation, Machine Learning, and Computational Fabrication.

I am on the job market this year. If you are interested, please contact me!

Currently, I am interested in merging simulation techniques with machine learning, hoping to trade-off bottlenecks and inaccuracies with data-driven techniques. Machine-learning and model-reduction methods benefit from large demonstrative datasets; the more data present, the easier it becomes to converge on a solution. Aggregating and formatting data is not easy however, examples are not always readily available and the collected samples must be labeled or tagged appropriately. Fortunately, accurate simulations allow for the generation of limitless data under controlled scenarios. With every variable accounted for, the overhead of gathering and preparing the data dissapears. Coming full circle, this data can then be used to train stable and efficient alternatives to physics simulations that can improve time-bound applications or even produce differentiable simulations that can be tuned to achieve specific dynamics.

In the past, I have worked on tagging physical hyperlinks onto intricate everyday objects, as well as exploring side-channel exploits of neural architechtures running on modern GPUs. I also love to tinker, build, and hack. I've been known to augment 3D printers and design award winning robots.

Outside of research you can find me playing ⚽ or 🏐. I also love to cook and explore the food scene around me, feel free to reach out to me for recommendations!

I am originally from São Paulo, Brasil but have spent the last few years living in (and photographing) New York City.

For more information about me, see my resume or contact me.