Best Project Presentation

Students will analyze images from optical microscopes that reveal features of materials and microstructures using machine learning techniques. These images have been collected by geologists, who use them to study the rock samples that they collect in the field and determine their properties and origins. We have a baseline system already implemented, and the goal is to improve it with new machine learning techniques, guided by the insights of our collaborating geologists.

Data science projects require knowledge of software that changes rapidly. As a result, scientists spend hours reading long documentations and manuals instead of advancing their scientific fields. In this project, we aim to automatically extract relevant aspects of scientific software (e.g., what does it do, how to install it, how to operate with it or how to cite it) from documentation and code using machine learning techniques. The students will build on an existing baseline of classifiers and try to improve the existing results.

SideEffects is a cancer patient’s resource to access treatment and side effects tailored to the patient’s treatment and disease history. The app sources content from clinical data, National Cancer Institute, social media, and user input from an app.