Mackenzie S
- Research Program Mentor
PhD at Stanford University
Expertise
probability, statistics, data science, machine learning in medicine
Bio
I am a mathematician excited to apply math to medicine. My first love was probability -- the idea of understanding randomness is thrilling! Lately I'm excited to explore how machine learning and automation can improve clinical care and health outcomes. When I'm not studying or teaching, I love to be outside as much as possible. My favorite way to spend a free afternoon is a walk through the park trying to find cute dogs to pet.Project ideas
Machine Learning Methods in Breast Cancer Diagnosis
Machine learning (ML) can be applied to nearly every field of medicine. New and exciting research is being made every day, but there is still ways to go before ML is used in real clinical settings. For this project, the student can pick a focused area of medicine that interests them -- e.g. radiology for breast cancer, laboratory tests in pathology -- and research the state-of-the-art methods for applying ML to that area. The student can write a review paper outlying the key developments and the possibilities/ideas for how machine learning can be implemented in the future.
Law of Large Numbers Through Simulations
Probability is a foundational subject important for modeling processes in every field. The law of large numbers is a result about how the average of random variables converges to the theoretical average. For this project, the student will learn probability and coding skills to simulate different random variables and processes. The student can pick their favorite random variable, or one inspired by a real-life scenario, and then write simulations to investigate how the random variable follows the law of large numbers. The result would be a research paper or presentation containing figures from the simulations and mathematical results.