NSF AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography

I lead the NSF AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography.  Changes in weather patterns, oceans, sea level rise, and disaster risk amplify the need for accelerated AI research in the environmental sciences. AI2ES is a convergent, multi-sector NSF Trustworthy AI institute led by the University of Oklahoma that brings together researchers in AI, atmospheric science, ocean science, and risk communication.

Dr McGovern’s Research

My research focuses on developing and applying machine learning and data mining methods for real-world applications with a special interest in high-impact weather. Much of my current work focuses on weather analytics or physical data science, where my students and I are developing physics-based trustworthy AI methods as well as explainable AI.  We apply these methods to high-impact weather phenomena including tornadoes, hail, severe wind events, flooding, drought, and aircraft turbulence.

To create a top science, technology, engineering, and mathmatics (STEM) workforce, we need a diverse and flexible workforce. Diversity will bring new ideas to the forefront and flexibility is required when technology changes rapidly. I’ve developed K-12 outreach projects to excite students about STEM careers and also actively work on diversity, equity, and inclusion.  

I also direct the Interaction, Discovery, Exploration and Adaptation (IDEA) lab. 

Education

• Ph.D. in Computer Science (May 2002), University of Massachusetts Amherst. Dissertation: Autonomous Discovery of Temporal Abstractions from Interaction with an Environment
  Committee: Andrew G. Barto (chair), J. Eliot B. Moss, Roderic Grupen, and Neil Berthier
• M.S. in Computer Science (1998), University of Massachusetts Amherst
• B.S. (Honors) in Math and Computer Science (minor: Spanish, 1996), Carnegie Mellon University