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GeezerVison is showing dritchie.github.io — Daniel Ritchie
Contact Information
CIT, Room 445
115 Waterman Street
Providence, RI 02912
Office hours: Book a slot
Teaching
Spring 2026
CSCI 2240: Advanced Computer Graphics
Spring 2025
CSCI 2240: Advanced Computer Graphics
Talks & Videos
Synthesizing Abstractions for 3D Modeling
Talk given at the BeyondCAD Workshop at The University of Edinburgh, July 2026.
How Video Games Saved Math (for me)
Invited talk at Brown's Symposium for Undergraduates in the Mathematical Sciences (SUMS) 2026.
Deep Learning for 3D Geometry
SGP 2024 Summer School (with Zoë Marschner)
Learning to Represent Shapes with Programs
SGP 2022 Summer School
Neurosymbolic Generative Models for Structured 3D Content
3D Geometry and Vision (3DGV) Seminar
We Need a Deeper Network
Brown CSCI 1470/2470 Fall 2020 end-of-semester song
Probabilistic Programming for Computer Graphics
PROBPROG 2018 Resources
Deep Learning for 3D Geometry
My slides for the course that Zoë Marschner and I taught at SGP '24
The SIGGRAPH Logo Gallery
An interactive gallery of paper figures featuring the SIGGRAPH name and/or logo
Optimeet
A tool for coordinated scheduling of multiple meetings
REU Site: AI for Computational Creativity
Website for our NSF REU Site
exploreCSR: Socially-Reponsible AI for Computational Creativity
Website for our undergrad research experience program (in partnership with Google Research)
Learning to Generate 3D Shapes and Scenes
Website for our CVPR 2021 Workshop
Learning 3D Generative Models
Website for our CVPR 2020 Workshop
Learning Generative Models of 3D Structures
Slides from our Eurographics 2019 Tutorial
Three-phase Paper Writing
An algorithm for writing technical papers About
I am an Associate Professor of Computer Science at Brown University, where I co-lead the Brown Visual Computing group. My research sits at the intersection of computer graphics, artificial intelligence, and machine learning—especially how AI and ML tools can make the practice of visual creation easier, more accessible, and more fulfilling. I'm particularly interested in technologies for creating, manipulating, and analyzing 3D shapes and scenes, and these days I'm excited about neurosymbolic methods for doing so (combining the best aspects of procedural models and deep neural networks). My research has been funded by gifts from Adobe, Autodesk, Roblox, Pixar, and NVIDIA, as well as grants from DARPA and the National Science Foundation, including an NSF CAREER Award. I received my PhD from Stanford University, where I worked with Pat Hanrahan in the Graphics Lab and with Noah Goodman in the Computation and Cognition Lab. I received my undergraduate degree from the University of California, Berkeley. My Erdős number is 4 (Daniel Ritchie → Niloy Mitra → Leonidas Guibas → Boris Aronov → Paul Erdős). My Bacon number is 3, though only if you count all film credits, not just cast appearances (Daniel Ritchie → John Lasseter → Tom Hanks → Kevin Bacon). This (debatably) makes my Erdős-Bacon number 7. News
November 2026
Applications are open for our NSF summer REU site, Artificial Intelligence for Computational Creativity! The application deadline is February 3.
September 2026
Code for ShapeLib is now available on Github.
September 2026
Check out Maxim's new paper (to appear at SIGGRAPH Asia) to learn how a good DSL design + classic program synthesis techniques can beat frontier LLMs at generating game character behaviors.
August 2026
The ShapeLib paper is finally out in ACM ToG!
July 2026
A recording of my talk at the BeyondCAD Workshop is now available.
Publications
Aditya Ganeshan,
Mateus Gadelha,
Thibault Groueix,
Zhiqin Chen,
Siddhartha Chaudhuri,
Vladimir Kim,
Yifan Wang,
and
Daniel Ritchie
CVPR 2026
website
|
paper
|
arxiv
|
code
Oral Presentation
CVPR 2026 Workshop on AI for Content Creation
arxiv
CVPR 2026 Workshop on Synthetic Data for Computer Vision
paper
Daniel Ritchie,
Paul Guerrero,
R. Kenny Jones,
Niloy Mitra,
Adriana Schulz,
Karl D. D. Willis,
and
Jiajun Wu
Eurographics 2023 STAR
arXiv
|
paper
arXiv preprint
arXiv
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