During a summer internship at Oregon State University I created a simple ray tracer using C++. I implemented and tested methods for improving image rendering speed and making rendered images more realistic.
The image shown to the right is an output from an early version of my program that used simple methods such as antialiasing and reflection.
The bottom image is an output that used more advanced techniques, such as Monte Carlo path tracing, to create more realistic lighting.
For more information and more images, the poster for my final project, which I presented at the University of Portland, can be viewed here.
Explainable Neural Networks
During summer of 2019 I worked on a project at Oregon State University on explainable neural networks. This project aimed to explain the decision-making of deep neural nets for image recognition in terms of human concepts.
The program was trained to recognize and identify images of birds and then analyzed to see whether it focused on semantically meaningful concepts, such as "Eye" or "Crown" as in the image shown here.
Over the course of 2016 and early 2017 I helped develop a project that used deep convolutional neural nets to analyze MRI scans and attempt to diagnose various stages of dementia. My motivation for this project comes from my family's history of Alzheimer's.
By developing a technique that allowed the 3D MRI scans to each be split into hundreds of 2D "slices" as seen in the image, I was able to substantially improve the accuracy of the program.
The project was submitted to the 2017 Central Western Oregon Science Expo and the subsequent Intel Northwest Science Expo. The presentation poster can be seen here.
Aside from this website, I've developed other websites and concepts for websites. One example is airinchina.github.io, which I created as an informative supplement for a high school project on air pollution in China.
A test website I created as a structure for the final project for Web Development (CS290) at OSU can be viewed here. Try the search bar!