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Aditya Ganeshan

Researcher
Apple
Computer Vision / Computer Graphics / Machine Learning
What is my research about?

My research lies at the intersection of computer vision, computer graphics, and machine learning. I build systems that turn visual and geometric data into structured models by making parts, parameters, and constraints explicit. The goal is geometry that people and machines can edit, fabricate, and reason with.

Short Bio

I am a Researcher at Apple. I earned my Ph.D. in Computer Science from Brown University, where I was 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. My work has appeared at CVPR, ICCV, SIGGRAPH Asia, and NeurIPS, with papers selected for oral presentations and one named a CVPR Award Candidate.

Select Research
Residual Primitive Fitting of 3D Shapes with SuperFrusta
Residual Primitive Fitting of 3D Shapes with SuperFrusta

A. Ganeshan, Matheus Gadelha, Thibault Groueix, Zhiqin Chen, Siddhartha Chaudhuri, Vladimir G. Kim, Wang Yifan and Daniel Ritchie

Oral & Award Candidate (1.8%) IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR) 2026

MiGumi - Making Tightly Coupled Integral Joints Millable
MiGumi - Making Tightly Coupled Integral Joints Millable

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

Pattern Analogies - Learning to Perform Programmatic Image Edits by Analogy
Pattern Analogies - Learning to Perform Programmatic Image Edits by Analogy

A. Ganeshan, Thibault Groueix, Paul Guerrero, Radomír Měch, Matthew Fisher and Daniel Ritchie

IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR) 2025

ParSEL - Parameterized Shape Editing with Language
ParSEL - Parameterized Shape Editing with Language

A. Ganeshan, Ryan Y. Huang, Xianghao Xu, R. Kenny Jones and Daniel Ritchie

ACM Siggraph Asia 2024, Journal at Transactions on Graphics (TOG) 2024.

Improving Unsupervised Visual Program Inference with Code Rewriting Families
Improving Unsupervised Visual Program Inference with Code Rewriting Families

A. Ganeshan, R. Kenny Jones and Daniel Ritchie

Oral (9.03%) IEEE / CVF International Conference on Computer Vision (ICCV), 2023

Recent Talks
Recent highlights and news:
  • 27 July 2026 : I joined Apple as a 3D Generative AI / Computer Vision Researcher! I’m excited to work with David Jacob and the team on challenging new problems.
  • 20 July 2026 : Reviewed four papers for NeurIPS 2026 and four papers for SIGGRAPH Asia 2026.
  • 26 June 2026 : I successfully defended my PhD! Many thanks to my committee members: Daniel Ritchie, Adriana Schulz, and Takeo Igarashi.
  • 20 May 2026 : Our paper titled Residual Primitive Fitting of 3D Shapes with SuperFrusta has been selected as an Award Candidate at CVPR 2026! It is one of 74 award candidates out of 4,072 submitted papers.
  • 10 May 2026 : Gave a talk at Dartmouth’s Visual Computing Seminar with the same title, From Measurements to Structure, Annotation free acquisition of Symbolic Geometry. Thanks to Dhawal Sirikonda and Adithya Pediredla for inviting me!
  • See all news ...

Most recent update: August 5, 2026.