Presentations and Posters on AI2ES Topics


Non-peer-reviewed and invited presentations

2021

  • Betz, Dara (2021) Map Your Career with Geospatial Technology & Artificial Intelligence. West Oso High School Career Day. Slides here.
  • Dinh, Hue; Kamangir, Hamid; Collins, Waylon; King, Scott Alan; Tissot, Phillipe; Durham, Niall; Rizzo, James (2021) Deep Learning Predictions of Coastal Fog Using Autoencoders. AMS 101st Annual Meeting. AI student award, Honorable Mention. Recording here.
  • Hall, David (2021) Exploring the Frontiers of Deep Learning for Earth System Observation and Prediction. AMS 101st Annual Meeting. Recording here.
  • Kamangir, Hamid; Tissot, Philippe; Collins, Waylon; King, Scott. A.; Dinh, Hue; Durham, Niall; Rizzo, James (2021). FogNet: A Multiscale 3D CNN with an Attention Mechanism and a Dense Block for Fog Predictions. AMS 101st Annual Meeting. AI student award, Third Place. Recording here.
  • Lagerquist, Ryan; McGovern, Amy; Gagne, David John; Homeyer, Cameron (2021) Using Significance Tests and Physical Constraints to Interpret a Neural Network for Tornado Prediction. AMS 101st Annual Meeting. Recording here.
  • Lagerquist, Ryan; Stewart, Jebb; Kumler, Christina; Ebert-Uphoff, Imme (2021) Deep Learning for Short-Term Forecasting of Convective Initiation and Decay over Taiwan. AMS 101st Annual Meeting. Recording here.
  • Lagerquist, Ryan; Turner, David D.; Ebert-Uphoff, Imme; Hagerty, Venita; Kumler, Christina; Stewart, Jebb (2021) Deep Learning for Parameterization of Shortwave Radiative Transfer. AMS 101st Annual Meeting. Recording here.
  • McGovern, Amy (2021) NSF AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography. Keynote talk, AMS 101st Annual Meeting. Recording here.
  • Pashaei, Mohammad; Starek, Michael (2021) Raw Digitized Waveform versus Attributes Derived from Online Waveform Analysis for Point Cloud Classification. AMS 101st Annual Meeting. Recording here.
  • Starek, Michael; Pashaei, Mohammad (2021) Deep Learning-Based Super-Resolution to Enhance UAS Imagery for Coastal Mapping. AMS 101st Annual Meeting. Recording here.
  • Stock, J.,  J. Dandy, I. Ebert-Uphoff, C. Anderson, J. Dostalek, L. Grasso, J. Zeitler, and H. Weinman, Using Machine Learning to Improve Vertical Profiles of Temperature and Moisture for Severe Weather Nowcasting, AMS 101st Annual Meeting, 20th Conference on Artificial Intelligence for Environmental Science, Jan 10-15, 2021.
  • Ver Hoef, Lander; Lee, Yoonjin; Adams, Henry; King, Emily; Ebert-Uphoff, Imme (2021) Topological Data Analysis for Identifying Convection in GOES-R Imagery. AMS 101st Annual Meeting. Recording here

2020

  • Caruso, Korinne;  Nelson, John; Tissot, Philippe; and Davis, Phil (2020) Broadening the AI Workforce through a Community College Program. Presented at the 2020 Virtual ATE Conference.
  • Kummerow, Christian and Imme Ebert-Uphoff. Satellite Precipitation Algorithms and AI, AGU Fall Meeting, Dec 7-11, 2020.
  • Ebert-Uphoff , Imme and Kyle Hilburn, On the Interpretation of Neural Networks Trained for Meteorological Applications, ECMWF-ESA Workshop on Machine Learning for Earth System Observation and Prediction, Oct 2020.
  • Kamangir, H., Collins, W., Tissot, P., King, S.A., Dinh, H., Durham, N., and Rizzo, J. (2020) FogNet: A 3D Attention Convolutional Neural Network for Fog Prediction. Presentation at the 2020 YOUMARES 11 Conference, Deutsche Gesellschaft für Meeresforschung, Hamburg, Germany. 
  • McGovern, Amy. (2020) Building trustworthy AI for environmental science. Invited talk for the AIML@OU seminar.
  • McGovern, Amy. (2020) Building trustworthy AI for environmental science. Invited talk for the Georgia Tech Institute for Data Engineering and Science (Ideas) Machine Learning seminar.
  • McGovern, Amy. (2020) Building trustworthy AI for environmental science. Invited talk for the Machine Learning seminar series.  Recorded slides are talk are here.
  • McGovern, Amy (2020) Building trustworthy AI for environmental science. Invited talk for the NITRD Big Data and AI annual meeting.
  • McGovern, Amy (2020) Building trustworthy AI for environmental science. OU School of Meteorology Convective Seminar.
  • McGovern, Amy. (2020) Machine Learning for High-Impact Weather. Invited talk for Science Discussion Group at the Storm Prediction Center.
  • McGovern, Amy (2020) NSF AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography. Keynote talk to the 2020 ASR/ARM Topical Workshop on Machine Learning and Statistical Methods for Observations, Modeling, and Observational Constraints on Modeling.
  • McGovern, Amy. (2020) Trustworthy AI for High Impact Weather Prediction. Presented at the 2nd Workshop on Leveraging AI in Environmental Science. Recordings and slides are available here.
  • Vicens Miquel, Marina; Medrano, F. Antonio; Tissot, Philippe (2020) Wet/Dry Shoreline GeoDetection by Applying Deep Learning Analysis to UAV Imagery. To be presented at the Reasoning in GeoAI Workshop

Posters

2021

  • Coming soon!