(2020) Machine Learning Algorithms

The Wisconsin MRSEC has developed machine learning techniques that enable the design of new toxin sensors using liquid crystal droplets that respond to the presence of different bacterial toxins and at extremely low concentrations by changing shape and appearance. Machine learning enables computers to automatically analyze the droplet responses to measure toxin concentration and type automatically at high accuracy. More generally, these results demonstrate that the machine learning approach can quickly extract valuable information from complex datasets.

Social and Racial Justice and the Wisconsin MRSEC

The MRSEC Executive Committee has chosen to undertake the 21-Day Racial Equity Habit Building Challenge. The challenge is to take at least one action per day for twenty-one days to build equity and justice. What does that look like? The Challenge website provides a long list of resources, from articles and books to read, podcasts to listen to, and documentaries and interviews to watch, to organizations to connect with and activities to focus our attention on the racial context of the world around us. The Executive Committee commits to tracking our progress on the Challenge and to using it to help us form new habits of mind that will inform future decision making for the center.