Aditya Ganeshan
CS PhD Student
Brown University
Graphics / Vision / Machine Learning / Mathematics / Music
What is my research about?
My research focuses on Symbolic Geometry, i.e. structured representations that capture how visual data is constructed, organized, or related (typically in a programmatic manner). Such representations hold the promise of making geometry interpretable, editable, and reusable across domains, yet they remain difficult to design and apply in practice. I address this challenge across three fronts: Formulation, by developing symbolic languages tailored to diverse geometric domains; Acquisition, by building learning systems that recover symbolic structure from visual data; and Manipulation, by creating learning-driven interfaces that make symbolic geometry intuitive to explore and refine. Together, these efforts aim to lower the barrier to creating new symbolic representations, enabling a Cambrian explosion of geometry languages that expand how we model, communicate, and reason about visual data.
Short Bio
I am a 5th year Ph.D. candidate in Computer Science at Brown University, advised by Daniel Ritchie. I have spent time at Adobe Research and the University of Tokyo, and previously worked at Preferred Networks in Japan and the Video Analytics Lab at IISc, India. I earned my Integrated B. Sc. and M.Sc. in Applied Mathematics from IIT Roorkee.
I am actively looking for full-time opportunities starting in 2026.
Select Research
A. Ganeshan, Matheus Gadelha, Thibault Groueix, Zhiqin Chen, Siddhartha Chaudhuri, Vladimir Kim, Wang Yifan and Daniel Ritchie
ArXiv 2025
A. Ganeshan, Kurt Fleischer, Wenzel Jakob, Ariel Shamir, Daniel Ritchie, Takeo Igarashi and Maria Larsson
ACM Siggraph Asia 2025, Journal at Transactions on Graphics (TOG) 2025
A. Ganeshan, Thibault Groueix, Paul Guerrero, Radomír Měch, Matthew Fisher and Daniel Ritchie
IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR) 2025
A. Ganeshan, Ryan Y. Huang, Xianghao Xu, R. Kenny Jones and Daniel Ritchie
ACM Siggraph Asia 2024, Journal at Transactions on Graphics (TOG) 2024.
A. Ganeshan, R. Kenny Jones and Daniel Ritchie
Oral (1.8%) IEEE / CVF International Conference on Computer Vision (ICCV), 2023
Select Projects
Recent highlights and news:
- 8 December 2025 : SuperFit project page is live! A collaboration with Adobe Research on converting 3D shapes into compact, editable primitive assemblies.
- 8 December 2025 : Gave a guest lecture on SuperFit in Daniel’s CSCI1230 course at Brown.
- 20 November 2025 : Gave an oral presentation on SuperFit at NECV 2025 at UMass Amherst.
- 14 October 2025 : The project page for MiGumi: Making Tightly Coupled Integral Joints Millable and the corresponding arxiv submission are now live! Check out the project page and read the paper on arXiv.
- 9 August 2025 : Our paper titled MiGumi: Making Tightly Coupled Integral Joints Millable has been accepted to SIGGRAPH Asia 2025! Had a lot of fun crafting this paper with amazing coauthors: Kurt Fleischer, Wenzel Jakob, Ariel Shamir, Daniel Ritchie, Takeo Igarashi, and Maria Larsson.
- See all news ...
What I am doing now
I am contributing towards a few research directions: a) building scalable text2visualprogram approach for 3D data, b) Designing tool that helps design Millable Kigumi Joints and c) Building a representation and inference system for richer procedural abstractions of articulate objects.
Most recent update: December 9th 2025.