Aboue me

I am a first-year PhD student at Purdue University, advised by Prof. Daniel Aliaga. My research interests are computer graphics, 3D computer vision, and deep learning.

Previously, I earned my Master’s degree from Brown University, where I had the privilege of working with Prof. Daniel Ritchie and Prof. Srinath Sridhar on procedural modeling and 3D generative models. I received my bachelor’s degree from Tufts University, with three majors in computer science, applied mathematics, and economics. During my undergraduate years, I have been fortunate to work with Prof. Michael Hughes on generalized category discovery and Prof. Liping Liu on graph neural networks.

Last Update: 10/8/2025

Publications

ProcTex: Consistent and Interactive Text-to-texture Synthesis for Part-based Procedural Models
Ruiqi Xu*, Zihan Zhu*, Ben Ahlbrand, Srinath Sridhar, Daniel Ritchie. In Submission
[paper]

Specializing Small Language Models towards Complex Style Transfer via Latent Attribute Pre-Training
Ruiqi Xu*, Yongfeng Huang*, Xin Chen, Lin Zhang. In Proceedings of ECAI 2023
[paper] [code]

Implementations

Every now and then, we come across papers without code. Here is a record of codeless papers I implemented for personal interest / research needs. Hopefully you can notice how my coding skills grow over time from these repos:)

1. On Distillation of Guided Diffusion Models [paper] [code]
2. Nuvo: Neural UV Mapping for Unruly 3D Representations [paper] [code]