SEAS and Cooperative Institute for Great Lakes Research (CIGLR) faculty received three of the 17 Propelling Original Data Science (PODS) grants awarded by the Michigan Institute for Data Science (MIDAS) in 2021.

“MIDAS is a University of Michigan (U-M)-wide institute with 420 affiliated faculty from 60 departments,” explained Bill Currie, Associate Dean for Research and Engagement and professor of Geospatial Data Sciences at SEAS. “The majority of the MIDAS affiliates are from engineering and computer science, with SEAS researchers being a minority. But in 2021, SEAS researchers were well represented among those receiving the PODS awards.”

The PODS grant awardees, announced in May 2021, will present “lightning talks” on their research at the PODS Awards Showcase on March 23, 12 - 3 p.m. at Weiser Hall on the U-M Ann Arbor campus. Attendees are requested to RSVP.

The PODS funding strongly encourages works that transform research domains through data science and Artificial Intelligence (AI), works that improve the reproducibility of research, and works that promise major impact and potential for significant expansion. “The diverse range of research that MIDAS is able to fund demonstrates the strength of data science and AI research at U-M,” said Dr. H. V. Jagadish, MIDAS Director. “These projects will strengthen the data science and AI community at U-M, play a transformative role in a wide range of disciplines, and will have immediate and significant impact on our society.”

The SEAS/CIGLR Principal Investigators (PIs) and the Co-PIs (including Currie) of the PODS-funded projects are: 

Assistant Research Scientist Ayumi Fujisaki-Manome (Geospatial Data Sciences, CIGLR, Climate and Space Sciences and Engineering) 
“Supporting Decision-making for a Vital Waterway in the Great Lakes by Machine Learning Model-based Lake Ice Forecasting"
Co-PI: Christiane Jablonowski (Climate and Space Sciences and Engineering)
 
"The project fills a gap of existing forecast models in river ice systems using a machine-learning technique,” said Fujisaki-Manome.

Associate Professor Joshua Newell (Sustainable Systems)
“Using Geospatial Data Science to Identify Vulnerable Communities to Climate Change”
Co-PIs: Marie O’Neill (Environmental Health Sciences); Carina Gronlund (Survey Research Center)
 
"This grant is enabling my research group to collaborate with colleagues from Public Health to map climate change risk due to heat, flooding, and what we are calling ‘knowledge vulnerability,’” said Newell. “For the latter, we have been using Twitter data to map climate change denialism at the zip code scale. Our overall objective is to identify communities particularly at risk due to climate change and we are using large-scale spatial data sets and modeling to do so."

Assistant Professor Runzi Wang (Landscape Architecture)
“Data Science Approach towards a Socio-ecological Framework for the Investigation of Continental Urban Stream Water Quality Pattern” 
Co-PIs: Yang Chen (Statistics); Bill Currie (Geospatial Data Sciences)

“In this research, new methods are being developed to use existing stream water quality datasets for streams that pass through U.S. urban areas and link those to specific subwatersheds to connect stream water quality to land use and urban form,” said Currie and Wang.     

Previous MIDAS grants have made it possible for the research teams to form many new collaborations, formulate groundbreaking ideas, and bring to U-M more than $75 million of external funding. 

Learn more about the 2021 MIDAS PODS grants.