Julia Gong is a sophomore at Stanford University majoring in Mathematical and Computational Science and minoring in Linguistics. She started at SAS in the summer of 2016, when she created a skin cancer detection software at JMP using image analysis and statistical modeling techniques. In the summer of 2017, she used JMP Scripting Language to build an interactive custom R add-in builder for JMP. In the summer of 2018, she built an end-to-end, automated data pipeline for liver tumor segmentation in 3D CT scans using deep learning and computer vision for biomedical image analytics in SAS Viya and CAS. She has been recognized in international technology competitions, loves public speaking and puns, and enjoys seeking novel solutions in overlooked intersections of AI, machine learning, language, environmental conservation, medicine, service, and art. Julia hopes to pursue a career that unites her many interests in computer vision, artificial intelligence, medicine, natural language processing, social good, education, and sustainability.
This is the fifth and final post in my series of posts about the deep learning model I developed to detect tumors in 3D CT scans of livers. My last post talked about visualizing the results of the computer vision project. This post will cover model accuracy and the final
This is the fourth post in my series about a computer vision project I worked on to identify liver tumors in CT scans. In my previous post, I had taken a break from my deep learning model to work on data management and data labeling. Now, I’ll return to the
This is the third post describing a computer vision project I worked on at SAS to identify liver tumors in CT scans. In my previous post I talked about testing different models and hyperparameters for the models. Today, I’ll talk about data processing for image data. If you need to
This is the second post in my series about a computer vision project I worked on at SAS. In my previous post, I talked about my initial research and excitement for the project. In this post, I’ll talk about how I refined my goals and got started with the project
Recently, I was given an amazing opportunity to work on a project in biomedical image analytics in collaboration with a large university medical center. The goal of the project was to develop a computer vision system that identifies tumors in CT scans of livers. I have always loved applying technology
As a third-year intern here at SAS and rising sophomore in college, I’ve been fortunate enough to have completed a few projects in various corners of the tech space. Having gathered my third data point this summer, and in the spirit of SAS #analytics, I’ve started making some data-driven inferences
