Welcome to Michelle Dai’s website!

Hello everyone! I am Michelle Dai, a 2nd year Ph.D student at Johns Hopkins University in the Applied Math and Statistics Department. I’ve loved numbers since I was young, but I was in high school when I began to consider the power data has to contribute to the betterment of society. At the North Carolina School of Science and Math (NCSSM), I am grateful to have received various research opportunities that exposed me to statistical applications in a diverse range of fields, such as monitoring cardiac arrhythmia, measuring air pollution, and viral epidemiology.

I attended Princeton University for my undergraduate studies, during which I focused my statistical interests on machine learning. To attain my B.S.E. in Operations Research and Financial Engineering and a minor in Finance, I completed an undergraduate thesis under the guidance of Dr. Jianqing Fan on using feedforward neural networks to predict American options prices. I earned a minor in Statistics and Machine Learning with a machine learning project about using convolutional neural networks (CNNs) in autonomous driving. After graduation, I worked at the World Bank Treasury in Washington, DC, having been inspired by its goals to eradicate poverty and promote shared prosperity worldwide.

Now at Johns Hopkins University, I seek to take advantage of its robust medical resources and the opportunity to collaborate with brilliant advisors and peers to continue pursuing what has always motivated me; harnessing technological tools for the betterment of mankind.