Justin Solomon, an associate professor at the MIT Department of Electrical Engineering and Computer Science and a member of the Computer Science and Artificial Intelligence Laboratory (CSAIL), is using modern geometric techniques to solve complex problems that often don’t initially seem related to shapes. For example, geometric structure in high-dimensional space can be used to compare datasets, bringing insight into issues such as the performance of machine-learning models.
The Geometric Data Processing Group, which Solomon leads, works on a wide range of problems, from aligning 3D organ scans to enabling autonomous vehicles to identify pedestrians. Another project involves using geometrical tools to develop better generative AI models. Solomon’s journey to MIT began with an early interest in computer graphics. At Stanford University, he interned at Pixar Animation Studios, where he researched physical simulations and rendering techniques. Throughout his academic career, Solomon has worked on a problem called optimal transport, which seeks to find the most efficient way to move a distribution of items to another distribution. Solomon is passionate about making geometric research accessible to underrepresented students, launching the Summer Geometry Initiative to provide a hands-on introduction to geometry research for undergraduates. He is also looking forward to improving unsupervised machine learning models with tools from geometry. In his spare time, Solomon enjoys playing classical music on the piano and cello, reinforcing the mutually beneficial relationship between research and artistic practice.