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• Ecological forecasting using machine learning

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

  Environment / Machine Learning

  Environment
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  How do trees respond to climate change?

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

  Environment

  Environment

• Understanding how bacterial communities assemble and function

  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.

  Biomedical Engineering / Chemistry

  Environment, Science & Technology

• Urbanization and climate justice in West Africa

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

  Environment

  Health & Biomedicine, Environment

• Investigating the spread of disease

  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.

  Biology

  Health & Biomedicine, Science & Technology

• Improving recruiting & mitigating bias

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

  Business & Economics
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  Seeking Insights into Autism

  Discover how researchers are using machine learning to develop personalized therapies for autism.

  Machine Learning

  Health & Biomedicine

• Using technology to address mental health

  Researchers study eHealth tools to offer low cost ways to help people cope

  Biology

• Teaching machines and humans to cooperate

  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.
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  Improving access to open science

  MSDS '18 students Jack Prominski and Pragati Shah, led by faculty advisor and DSI professor Rafael Alvarado, undertook a capstone project to improve an automated system that matches PLOS article manuscripts with appropriate editors.

  Science & Technology, Education