CS472 Data science and AI for COVID-19
This project class investigates and models COVID-19 using tools from data science and machine learning. We will introduce the relevant background for the biology and epidemiology of the COVID-19 virus. Then we will critically examine current models that are used to predict infection rates in the population as well as models used to support various public health interventions (e.g. herd immunity and social distancing). The core of this class will be projects aimed to create tools that can assist in the ongoing global health efforts. Potential projects include data visualization and education platforms, improved modeling and predictions, social network and NLP analysis of the propagation of COVID-19 information, and tools to facilitate good health behavior, etc. The class is aimed toward students with experience in data science and AI, and will include guest lectures by biomedical experts.
Class participation (20%)
Course project (80%)
Background in machine learning and statistics (CS229, STATS216 or equivalent).
Some biological background is helpful but not required.
For all course and project related questions, please send to firstname.lastname@example.org
Prof. James Zou (jamesz at stanford)
TA: Irena Fischer-Hwang (ihwang at stanford)
TA: Weixin (Victor) Liang (wxliang at stanford)
TA: Zhenqin (Michael) Wu (zqwu at stanford)
TA: Jaime Roquero Gimenez (roquero at stanford)
Date Lecture Readings/notes
May 1 Project proposals
May 15 NLP analysis COVID-19 information on Twitter and FB [video] guest: Johannes Eichstaedt
May 29 COVID-19 genomic analysis guest: Julia Palacios [slides]
June 10 Final reports due