2018 Summer Intern: Runmeng Zhai


Runmeng Zhai
University of Virginia, Class of 2018

Project 1: Statistical analysis of tumor growth after focused ultrasound Sonodynamic Therapy

Runmeng smProject Goal & Overview
In this project, I used longitudinal analysis (a statistical method) to analyze tumor growth in mice over the seven days following focused ultrasound treatment and to identify the decreasing pattern of tumore volume and the probability of deceasing pattern occurring. The goal was to understand which sonodynamic therapy is better and whether the combination of sonodynamic therapy with drug would be effective. I also aimed to understand the pattern of tumor growth under certain conditions.

I determined that focused ultrasound methods are better than using just the drug, but focused ultrasound plus the drug is the best therapy.

Project 2: Microbubble visualization and brain tumor type classification

Project Goal & Overview
In this project, I used time series methods (ARIMA) models to understand the pattern of microbubbles, such as the peak time, how much time before the effect will be cleared, etc. I wanted to see if it is possible to classify the type of brain tumor using ARIMA methods and then use long short-term memory (LSTM) methods to improve the models.

I determined that microbubbles can help classify the brain tumor type, and there is no residual effect in the brain.

Why were you interested in working for the Foundation?
I wanted to learn some new technology, and I am curious about how to use statistics methods in biotech industry.

What was your most important learning experience as an intern?
Self-learning, because I was able to study some new methods and also learned how to apply them.