CV

Basics

Name James W. Noeckel, PhD
Label Graphics Software Engineer
Email jamesn8@cs.washington.edu
Url jamesnoeckel.com
Summary I obtained my PhD from the GRAIL lab in the Paul G. Allen School of Computer Science and Engineering at the University of Washington, advised by Brian Curless and Adriana Schulz. My research has focused reverse engineering 3D designs of objects through the use of domain-specific geometry representations. In particular, I am fascinated by the ability of such representations to enable precise reconstruction with incomplete observations, especially alongside advances in deep learning techniques for 3D vision / shape modeling. I’ve published techniques to recover computer-aided design (CAD) models from measured data. During my undergraduate studies at Cornell University, I worked with Kavita Bala on photorealistic cloth rendering and Timur Dogan on large-scale light radiance simulation in urban environments. I also minored in physics; I have retained a particular interest in realtime graphics and physics simulation techniques thanks to my graphics / physics background, with various side projects exploring rendering, physics, and geometry techniques.

Work

  • 2025.02 - Present
    Graphics Software Engineer
    Apple
    Research and development on graphics algorithms for cutting-edge rendering techniques.
  • 2023.6 - 2023.9
    Research Scientist Intern
    Meta
    Developed an automated pipeline for synthesizing manufacturable parts of smart wearable devices tailored to individuals from their head scans. Employed geometry processing techniques to generate part geometry adhering to fitment parameters predicted from head measurements based on data analysis of prior user study data.
  • 2023.01 - 2023.06
    Teaching Assistant
    University of Washington
    Prepared course assignment codebase and other materials, conducted office hours, and graded assignments / projects in CSE 556: Computational Fabrication and CSE 599: Special Topics in Computational Design.
  • 2019.6 - 2019.9
    Software Engineering Intern
    NVIDIA
    Added features to a real-time volumetric renderer for medical visualization, such as better denoising capability, and computing optical flow maps to improve stability with temporal accumulation and to facilitate training an improved, special purpose AI denoiser.
  • 2018.6 - 2018.9
    Software Engineering Intern
    NVIDIA
    Developed 3D mapping/reconstruction pipeline for robotic navigation using deep stereo depth estimation and temporal probabilistic mixture models to improve the quality of fused geometry.
  • 2017.09 - 2024.12
    PhD Researcher
    University of Washington
    Working as part of GRAIL and CDG labs advised by Brian Curless and Adriana Schulz, conducting research on methods for editable scene reconstruction with a focus on reverse engineering designs of manufactured objects. Previously published work in fabrication-aware reconstruction of carpented objects and inferring the motion of CAD assemblies using physics and deep learning. Most recently submitted a paper on 3D reconstruction of engineering CAD models from partial scans using deep learning and geometry optimization.
  • 2016.5 - 2016.8
    SULI Intern
    Pacific Northwest National Laboratory
    Developed data analysis software for the fundamental particle physics group to improve particle reconstruction and energy calibration techniques for the ILC detector.
  • 2016.1 - 2016.5
    Undergraduate Research Assistant
    Cornell University
    Developed real-time implementation for a cloth rendering project under Prof. Kavita Bala (http://www.cs.cornell.edu/projects/ctcloth/), leading to publication.

Volunteer

  • 2022.12 - 2022.12

    Seattle, WA

    Presenter
    University of Washington CS Open House
    Presented my published work on predicting motion of mechanical CAD assemblies to undergraduates and high school students to spark interest in CS research.

Education

  • 2017.09 - 2024.12
    PhD
    University of Washington
    Computer Science
  • 2013.8 - 2017.5
    Bachelor
    Cornell University
    Computer Science

Awards

  • 2022.4
    UW Reality Lab Fundee
    University of Washington
    For the years of 2019 - 2022, I successfully pitched projects to the board of industry researchers (including Paul Debevec, Michael Cohen, Michael Abrash), securing research funding.
  • 2017.9
    Wissner-Slivka Endowed Fellowship
    University of Washington
    I was awarded a Computer Science & Engineering First-Year Fellowship upon admission to the UW PhD program.
  • 2017.2
    Phi Beta Kappa Society Membership
    Phi Beta Kappa Society
    I was recognized for my undergraduate academic achievement at Cornell and admitted into PBK.
  • 2016
    Dean's List
    Cornell University
    I was on the Dean's List for academic achievement from the years 2013 to 2016.

Publications

Skills

Computer Graphics
Rendering
Simulation
Geometry
Fabrication
Computer Vision
3D Reconstruction
Deep Learning
Classical Techniques
Programming
C++
Python
Java
C#
Lisp / Racket
Bash
GPU Programming
CUDA
OpenGL
GLSL
HLSL
Scientific Computing
Mathematica
Matlab
Julia
Scipy
Optimization
Numerical Analysis
Computational Physics
Deep Learning
Pytorch
Graph Learning
Computer Vision
Segmentation
Implicit Neural Representations
Generative Models
Robotics Mapping / Navigation
Art
3D Modeling
Drawing
Animation
Research
Technical Writing
Scientific Publication
Implementation / Engineering

Languages

English
Native speaker
German
Intermediate

Interests

Drawing
Traditional
Digital
Animation
Computer Graphics
Shader Programming
Procedural Animation
3D Modeling
Videogame Modding

References

Dan Zeng
My former manager at Meta.
Adriana Schulz
My PhD co-advisor at UW.
Brian Curless
My PhD advisor at UW.
Kavita Bala
My mentor and undergraduate research advisor at Cornell.