Cornell Covid ResponseDates: Aug. 2020 - May. 2022 GitHub: cornell-covid-modeling Associated Projects:
- simpar | A Python package for analyzing pandemic response measures
- cotat | A Python package used to generate interactive contact tracing visualizations
In March 2020, I was sent home from Cornell amidst the Covid-19 pandemic. I eagerly awaited the university’s decision for returning to campus in the fall. In June, it was announced that Cornell would return to campus for a hybrid semester. This decision to return was a result of the Cornell Modeling Team’s work led by Peter Frazier. This Forbes article details how the team discovered returning to campus was the safer option. Given this decision, the university had a challenging obstacle ahead: creating a class schedule for Fall 2020.
The first hurdle in creating the class schedule was determining new room capacities subject to the six foot social distancing requirement. This posed an interesting optimization problem which an ORIE team led by Jody Zhu tackled. More information on that effort can be found in this article. In August of 2020, I was asked to join the Cornell Course Roster Scheduling team led by David Shmoys, Oktay Gunluk, David Williamson, and Brenda Dietrich. I aided in collecting course information and preferences from over 80 academic departments to be fed in to an optimization model designed by ORIE PhD student, Conner Lawless. Afterwards, I led the effort to manage department requests for changes to the fall course roster, and developed the room assignment model for exams. More about these efforts can be found in this article. The hard work of these teams led to Cornell’s ability to provide an in-person education for the Fall 2020 semester. This Bloomberg article summarizes the victory.
In Fall 2021, I was asked to join a team of Cornell ORIE faculty and PhD students to advise Cornell leadership on the university’s Covid-19 policies. I developed the cotat Python package to visualize Cornell contact tracing data. In December 2021, Cornell was the first university to see Omicron cases on campus. See this CNN article. Visualizations created by this tool were used in an internal report prepared by Jaylen C. Perkins, MPH providing insight into spread during this surge. In January of 2022, I led the development of simpar, a Python package used to simulate the spread of Covid-19 through a heterogeneous population. This tool was central in generating predictions which directly informed Cornell’s Spring 2022 policies and were used to advise administration throughout the spring semester.