Big Theta is back with a renewed focus on presenting complex ideas at the frontiers of research in an easily digestible way.
With nearly a year separating our last article and this post’s time of writing, I believed it prudent to approach Big Theta with a renewed clarity and purpose that could sustain its momentum for months and years to come. After unforeseen circumstances separated our team in terms of location, Carlos has been focused largely on personal research projects in areas ranging from algorithmic information theory and computability theory to non-Euclidean geometry. My recent focus has been on time series prediction models using recurrent neural networks, in addition to continued work on reinforcement learning for robotics, language design for real-time Lagrangian simulations, and a budding interest in computational geometry and fluid dynamics for the optimization of wind turbine designs (you can see my website for more information about a few of these).
Across the Columbia community, I have had the chance to engage with some fantastically intelligent individuals working to push the boundaries of statistical machine learning, computer vision, and quantitative financial modeling. I hope to bring a few outside perspectives to this blog in the near future either through guest writing, or by means of adapting presentations given at our weekly machine learning discussion group.
Again with a hello world post “slightly” missing the beginning of the new year, we wish everyone a productive and educational 2017!
— Lucas Schuermann
Edited by Carlos Martin