This project will seek to provide accurate ecological forecasts by using different approaches for predicting algal blooms.

In partnership with NASA, researchers study the impact of climate change on trees.

This project will investigate the growth dynamic of bacterial biofilm with lattice light-sheet microscopy (LLSM), which is able to resolve individual cells within thick 3D biofilms in a non-invasive manner.

This project aims to explore how colonial policies of urban planning and racial segregation contribute to current-day urban air pollution in Dakar, Senegal.

This project will focus on predicting the interaction sites of host-host proteins using deep learning, so that scientists can better understand how these proteins interact for cell development.

Using data analytics to improve the way organizations identify, attract, develop, and retain talent

Presidential Fellows in Data Science Miranda Beltzer and Mawulolo Ameko are investigating technology-based models to address mental health by evaluating emotion regulation strategies.

Presidential Fellows in Data Science Erfan Pakdamanian and Nauder Namaky aim to develop a system that optimally alerts drivers when an autonomous vehicle algorithm fails. They plan to develop a deep neural learning algorithm that considers external hazards in conjunction with drivers’ cognitive states.

Presidential Fellows in Data Science Mark Rucker and Derek Lam, sponsored by the Data Science Institute and the Office of Postdoctoral and Graduate Affairs, are designing an algorithm that acts paternalistically to help people make decisions that are not just reflective of their immediate desires, but are also based on what they value as good.

Soda, salty snacks, and processed foods are among the top groceries purchased by Americans – a diet far removed from the one consumed for most of human history. Now researchers, health professionals, and the public want to know: how has this change in diet affected us and what, if anything, should we do about it?