Format
The poster presenter will be designated a virtual breakout room/table where attendees will be able to join and speak with the presenter about the poster.

Content
We encourage posters that connect data science research to other applications and research topics to build up our data science community. This year we encourage submissions that fit our theme of Data Science for the Social Good, though posters are not required to fit under one of the three sub-themes.  

Below are ideas for inspiration (but are not requirements or endorsements):
1. Data Science for Racial Equity
    - [Example] Curating inclusive and diverse datasets for AI
    - [Example] Understanding bias in machine learning algorithms predicting recidivism
2. Data Science for Health and the Environment
    - [Example] Measuring the effectiveness of different masks in fighting COVID-19
    - [Example] Tracking and modeling Cyanobacteria blooms in Wisconsin lakes
3. Data Science for Cities
    - [Example] Tracking segregation in city neighborhoods
    - [Example] Helping food banks and policy makers analyze food insecurity
4. Other
    - [Example] Efficiency and use of machine learning algorithms
    - [Example] Large scale data processing for data science applications
    - [Example] Visualization and tools for data science communication

Your proposal will be evaluated based on how it addresses the following questions:
1. What is the historical context and significance behind the problem you are trying to solve?
2. What kind of resources, expertise, services do you bring to the campus community or potential collaborators?
3. If you are looking for collaborators, what kind of expertise are you looking for in them?
4. What methodological, logistic, and cultural challenges and successes do you foresee or have you faced?