The Symposium on Geometry Processing 2024 – A Recap

The Symposium on Geometry Processing (SGP) is an annual event highly awaited in the geometry community. Researchers, enthusiasts, and newcomers alike flew in all over the globe to attend and enjoy the experience put together by this year’s organizing committee. As an incoming Summer Geometry Initiative fellow, when the opportunity to receive a travel grant to attend SGP 2024 arose, I immediately applied. A few days later, I received an email stating that I was a recipient, and almost a month later, I landed in Boston to be among 150 fellow participants.

Like most years, this year, SGP took place in two-parts: the graduate school from June 22-23, 2024, and the technical symposium from June 24-26, 2024, in MIT’s CSAIL building in Cambridge, Massachusetts, USA.

As a novice into geometry processing, the graduate school was a particularly helpful and robust introduction into the field. It was packed with foundational material that focused on the intuitive understanding of how geometric data was represented and processed. The motivation and goals of geometry process were well-laid out. I particularly enjoyed the talks on equivariant neural networks, sketch processing, introduction to geometry processing research in Python, and Monte Carlo methods. The talks had a much-needed balance of introductory, interactive material and in-depth analysis of useful methods. During this time, I also met many other novices like myself as well as those who push the frontier of geometry.

Equipped with the basics, I felt more confident attending the main event—the symposium. My favorites, right-off-the-bat were the three keynote speakers. They accomplished the great feat of inspiring an audience mixed with experts and beginners, and bring them to the same page. Dr. Xin Tong, Dr. Alec Jacobson, and Dr. Josephine Carstensen each covered complementary avenues of research—the broader scope, future direction, and innovative applications. The remaining 15-16 papers presented at the symposium were impressive in their own rights. While the selected papers covered a range of material, they all had one admirable thing in common: the papers were obvious by-products of passionate research.

The social events at the event were also a unique experience. Speaking to the presenters, organizers, fellow student researchers, and industry folks in the historic scene of Boston Tea Party Ships and Museum and the innovative display of MIT’s science museum set this symposium apart from other math conferences that I previously attended. I enjoyed talking to the presenters and getting to know them during and after the symposium. I built meaningful connections with all credit going towards the conference organizers on facilitating such an interaction.

For me, the most interesting problem is how data is represented. As someone that worked in bioinformatics and Boeing’s Phantom Works Estimating, the quality of data is immensely important. A common thread is that data is computationally and financially expensive to acquire so current data is relied upon heavily. Dr. Tong’s talk emphasized the need for better data and the papers reinforced this idea when it came to future direction. I have always been interested in better data representation and optimization for pipeline processing, but now, I am equipped with better direction and motivation.

I am grateful to have been the recipient of the SGP 2024 Student Travel Grant. I believe that I exhausted its resources to the best of my ability. The five-day event left a mark of inspiration on me that I could not erase if I tried.