The National Science Foundation invited academics to answer the question "What should undergraduate STEM education look like in 2040 and beyond?." The Integrated Statistics Learning Environment (ISLE) is a browser-based educational platform that supports data analysis as well as report writing, presentations, lecture slides, videos and student-instructor interaction. More info, and Professor Nugent's video "Personalized Learning Environments for Student-Centric STEM" can be found here.

NeurIPS is one of the premier conferences on machine learning, and includes a wide audience of researchers and practitioners in academia, industry, and related fields. Four department PhD students had three first-authored Proposal Track papers accepted for the workshop Tackling Climate Change with Machine Learning, which will be held in December.

1) Trey McNeely and Nic Dalmasso with a Spotlight Talk (Proposal Track) on Structural Forecasting for Tropical Cyclone Intensity Prediction: Providing Insight with Deep Learning (joint work with Kim Wood and Ann Lee)

2) Lorenzo Tomaselli with a Spotlight Talk (Proposal Track) on Wildfire Smoke and Air Quality: How Machine Learning Can Guide Forest Management (joint work with Coty Jen and Ann Lee)

3) Nic Dalmasso and Galen Vincent with a Poster (Proposal Track) on HECT: High-Dimensional Ensemble Consistency Testing for Climate Models (joint work with Dorit Hammerling and Ann Lee)

The COVIDcast project is about building and providing an ecosystem for COVID-19 tracking and forecasting. Read the interview here.

One reason has received too little attention: scientists, and science journalists, too often exaggerate results. Watch his lecture “Exaggerated Claims Undermine Science by Ignoring the Scientific Method,” here.