Over 2000 years ago, Greek mathematician Euclid drastically influenced how we perceive shapes. Adding a modern facet to these ancient teachings, Justin Solomon is leveraging modern geometric methods to confront complex issues often unrelated to shapes. As an Associate Professor in the MIT Department of Electrical Engineering and Computer Science and a member of MIT’s Computer Science and Artificial Intelligence Laboratory, Solomon’s work encompasses comparing geometrical aspects of datasets for training in machine learning models to substantive realistic applications such as aligning 3D organ scans and aiding autonomous vehicles in identifying pedestrians.
His research is characterized by a deep-seated union between geometric theory and real-world applications, evolving from an early passion for computer graphics and practical experience gained through internships in relevant fields. During a summer internship at Pixar Animation Studios, he concentrated on the physical simulation of cloth and fluids to enhance the realism of animated films. He continued at Pixar throughout his time at Stanford University, where he pursued double majors in math and computer science, and throughout graduate school. This connection between real-world applications and theoretical understanding drove his academic pursuits, leading him to pursue a computer science PhD with a focus on optimal transport problems, predominantly in computer graphics.
During his doctoral studies, his focus broadened from computer graphics-related applications of optimal transport to more interdisciplinary areas and applications, setting the base for an inclusive approach in his research at MIT. Inspired by a dynamic environment, Solomon collaborates with talented students, postdocs, and colleagues on complex, practical problems crosscutting various disciplines. His research employs geometric data processing to tackle high-dimensional statistical problems such as constructing better generative AI models, which Solomon highlights as the crux of mapping the space of images.
Parallel to conducting research, accessibility to geometrical know-how emerges as a key initiative for Solomon, stressing the importance of introducing and tutoring underserved students on the subject. To further this goal, he inaugurated the Summer Geometry Initiative, a six-week paid undergraduate research program, primarily for students from underrepresented backgrounds. The initiative provides an immersive experience of geometry research, and since its inception, has positively reshaped the demographics of incoming PhD students across different institutions.
Looking forward, Solomon anticipates the application of geometric tools for enhancing unsupervised machine learning models. Synergizing geometric insight with intricate data inference can assist computers in understanding complex unlabeled 3D scenarios, thereby facilitating more effective learning. Beyond academics, he enjoys playing classical music on his piano and cello, associating it with the analytical nature of his research.
