AI in Medicine

AI has many different and unique applications in medicine, from diagnosis to cell predictions, and this team investigates and guides students who are interested in becoming physicians about the potentially life saving impact machine learning can have on medicine.


This project teams focuses on the emerging field of quantitative finance and uses the free platform Quantopian to work on trading stocks algorithmically. Today, the majority of trades on the stock market are placed by computers via algorithms, which has drastically impacted the landscape of the market as there is now a greater emphasis on statistics, automation through machine learning, and a greater level of accessibility to the general public, in comparison to traditional trading. The quantitative finance team looks to research methods of trading stocks and uses Quantopian’s platform to ‘backtest’ these new algorithms. Analyzing large volumes of financial data can be extremely slow, and greater computational resources can provide the ability to advance our research.

Education through Competition (Kaggle)

This project team utilizes the website Kaggle to teach students about machine learning and data science. Kaggle offers competitions and datasets so that people can learn and compete with each other for prizes. These competitions teach students to work together to solve modern day data science problems and give students a taste of the current state of data science research, as well as experience with applying machine learning and other statistical techniques to solve difficult problems.