Hi! I'm Winnie, a fourth year Ph.D. in Computer Science at Stanford.
In 2016, I graduated with a B.S. degree in Mathematics from Stanford.
In 2017, I obtained an M.S. in Computer Science from here as well.
I am currently being advised by Professor Ron Fedkiw, and have worked in Professor Leo Guibas' and Professor Silvio Savarese's labs. My academic interests mainly lie at the intersection of Applied Mathematics, Visual Arts, and Machine Learning; this includes but is not limited to Graphics, 3D Vision, and Computational Geometry.
In my free time, I like to cook, doodle, read fantasy/sci-fi, and belt (screech) out Taiwanese rock ballads while biking between my apartment and my research lab.
CS248:Interactive Graphics, 1st place game (2015)
Unity, Blender, and Photoshop. Worked with Herman Chau to produce this game. Implemented custom acceleration structures, created assets, and designed UI. Click here for more details.
Procedurally Generated Ice Cream
CS348B:Image Synthesis Techniques (2014)
C++ and pbrt. Procedurally modeled soft serve ice cream, via implementation of shape classes in pbrt.
CS448:Scientific Computing (2015)
Visualized with C++ and OpenGL, arranged in Adobe Illustrator. Rendering and simulation of paths of double pendulums.
CS148:Introductory Graphics (2013)
C++ and class raytracer. Worked with Adam Young to produce this image. Extended raytracer to create underwater lighting via implementation of procedurally generated waves and Snell's law.
Real-time Interactive Tree Animation
IEEE TVCG.2017.2661308 (2017)
Co-author. Augmented in-house raytracer for visualizations of simulation results, scripted cluster computing and scene generation routined, verified the mathematical soundness of some parts of the algorithm.
Autoencoders for Inverse Rendering
CS231N:Convolutional Neural Networks (2017)
Experimented with physics-based image feature extraction. Synthesized toy dataset of textures, depth, normals, and radiance by augmenting raytracers. Trained adversarial autoencoders for image generation.
Adaptive Samplers for Ray-Tracing
CS229:Machine Learning, best project in Vision (2015)
Implemented SVM-based hierarchical adaptive sampler in C++ and pbrt.
Body Pose from Optical Flow
CS231A:Computer Vision (2015)
Experimented with optical flow based methods and Kalman filters for joint tracking in videos.
Deformation Graphs for Meshes
Undergraduate Research in Computer Science (2014)
Summer internship project in Geometric Computation Group. Implemented constraint-based deformations for use in research framework.
Deterministic Growth Processes
MATH101:Math Discovery Lab (2015)
Group project of 3. Collaborated with Caroline Ellison and Mark Nishimura to explore the mathematical properties of a well-defined growth process.
Facetracking for AR/VR
I was a research intern in the People AI team at Facebook AR/VR, and I worked on designing, implementing, evaluating, benchmarking, and analyzing a variety of deep-learning based face-tracking methods, with the goal of productizing promising methods to be used on-device for AR/VR applications.
VFX Research and Development
Industrial Light and Magic 2018-2020
I was a research intern at Industrial Light and Magic in summer of 2018, and continued working as a part-time research engineer up until March 2020. I worked on researching, implementing, and evaluating traditional and modern computer vision algorithms, with the goal of improving animation pipelines through tracking, retargeting, and generation of 2D and 3D data. More specifically, I've had the privilege to design and develop some data-driven production tools for The Irishman (2019) and Terminator: Dark Fate (2019).
Stonehearth Game Development
Radiant Entertainment 2015, Riot Games 2016
I was an software engineering intern at Radiant Entertainment in 2015, and an intern again in 2016 after Radiant Entertainment's acquisition by Riot Games. My first summer I worked on the restructuring, implementation, and some asset design of their world generation code, as described here, and in the following summer I worked on the restructuring and implementation of in-game hydrology.
Stanford Computer Science
I have been teaching assistants for
- CS205L: Continuous Mathematical Methods with an Emphasis on Machine Learning during 2020.Winter (head TA), 2019.Winter (head TA),
- CS231N: Convolutional Neural Networks for Visual Recognition during 2019.Spring (head TA), 2018.Spring
- CS148: Introduction To Computer Graphics and Imaging during 2020.Fall, 2018.Fall, 2016.Fall,
- CS109: Introduction To Probability For Computer Scientists during 2017.Spring, 2016.Winter, 2016.Spring, 2015. Fall
High School Outreach
I wrote the curriculum, led development, and cotaught the graphics track for the Girls Teaching Girls To Code CodeCamp (2015,2016).
Curriculum was designed for high school girls with minimum coding experience.
Here is the handout and the source code for 2016, designed to teach students how to create a simple game in Unity.
I cotaught the GTGTC summer workshop (2014) on 3D printing,
and I have taught a few sessions on graphics and image processing at Stanford Splash (2014), a program for middle school and high school students.
Mathematics for Advanced High School Students
I was a teaching assistant for
Euler Circle in Abstract Algebra (2015) and Cryptography (2016),
and was a residential teaching assistant in Number Theory for Stanford University Mathematics Camp (2013).