AI2ES Talks

Talks to all of AI2ES, from both AI2ES speakers and outside speakers

2024

  • December 4: AI Numerical Weather Prediction at NSF NCAR – David John “DJ” Gagne, John Schreck (NCAR)
  • November 20: TBD
  • October 23: Exploring NWS Forecasters’ Assessment of AI Guidance Trustworthiness – Mariana Cains (NCAR)
  • September 25: WoFSCast: A Machine Learning Model For Watch-to-Warning Scales – Monte Flora, Corey Potvin (NOAA). Slides, Paper, Recording
  • September 11: Wildfire Occurrence Prediction for CONUS with the UNet3+ Deep Learning Model – Bethany Earnest (OU); Annual Review – Amy McGovern (OU). Recording
  • July 31: Evaluation of Flash Drought Identification with Machine Learning Techniques – Stuart Edris (OU). Recording
  • July 18: Stuart Edris PhD Defense. Recording
  • July 17: Measuring Sharpness of AI-Generated Meteorological Imagery – Imme Ebert-Uphoff (CSU/CIRA). Recording
  • July 17: Bethany Earnest PhD Defense. Recording
  • July 2: Amanda Burke PhD Defense. Recording
  • June 26: Code IT Camp – Del Mar College Team. Recording
  • June 5: DiffObs: Generative Diffusion for Global 
Forecasting of Satellite Observations – Jason Stock (CSU). Recording
  • May 22: Advancing Coastal Inundation Forecasting: A Multifaceted Machine Learning Approach – Marina Vicens-Miquel. Slides, Recording
  • May 8: AI Governance: A Status Report on Federal Agencies’ Policy Development – Cary Coglianese (UPenn Carey Law). Recording
  • April 24: An AI/ML Collaborative for Southeast Florida Coastal Environmental Data and Modeling Center – Jason Liu (FIU) and FIU ExpandAI team. Recording
  • April 24: Andrew Justin MS Defense. Recording
  • March 27: AI Foundation Models for Weather and Climate: Applications, Design, and Implementation – Campbell Watson, Karthik Mukkavilli (IBM). Recording
  • March 13: Expand AI2ES for 4D space-time organization of precipitation processes and extremes, visualization tools, and workforce development – Samuel Shen (SDSU). Recording
  • February 28: Dynamical Tests of a Deep-Learning Weather Prediction Model – Greg Hakim (UW). Recording
  • February 14: Research Agenda for the Evaluation of AI-Based Weather Forecasting Models – Imme Ebert-Uphoff (CSU). Recording
  • January 17: Machine-learned emulation of climate models – Chris Bretherton (Allen Institute for AI). Recording

2023

  • November 8: Pure AI-based weather forecasting models – Where are we and where should we go? – Jacob Radford (CIRA/CSU) / Unveiling Predictive Uncertainty: Evidential Deep Learning vs. Ensembles for P-Type Forecasting – John Schreck (NCAR). Recording, Slides (Radford), Sildes (Schreck)
  • October 25: Vaisala Internship “Applying XAI To ML Hail Nowcasting” – Jay Rothenberger (OU). Recording, Slides
  • October 11: Experience using the DMC AI2ES GeoAI curriculum and work at TAMUCC – Miranda Barrett (DMC/TAMU-CC). Recording
  • September 27: International Collaboration with University of Valencia – Marina Vicens-Miquel (TAMU-CC), Veronica Nieves, Cristina Radin, Javier Martinez Amaya (U. Valencia). Recording
  • September 13: Development and teaching of the Intro to AI course to undergrads – Phillip Davis (DMC). Recording
  • August 30: Recording
    • OceanNet and its applications on prediction Loop Current – Anna Lowe
    • Gulf Stream – Michael Gray
  • August 16: Exploring Physically-Informed Scaling for TC Intensity Prediction – Marie McGraw (CSU). Recording
  • July 26: TAMU-CC REU and Undergrad Research Associate lightning talks and Del Mar College CODE IT II Camp presentation. Recording
  • July 21: AI2ES Research Experiences for Undergraduates – final 12-minute presentations. Recording
  • July 18: Master’s Thesis Defense – Visibility Estimation from Camera Images Using Deep Learning – Mel Wilson Reyes (OU). Recording
  • July 11: Master’s Thesis Defense – Gridded Hail Nowcasting Using UNets, Lightning Observations, and the Warn-on-Forecast System – Tobias Schmidt (OU). Recording
  • June 26: AI2ES Research Experiences for Undergraduates and SIParCS Interns 5-minute talks. Recording
  • June 21: Recording
    • Using Mathematical Techniques to Leverage Domain Knowledge in Image Analysis for Earth Science – Lander Ver Hoef (CSU)
    • Training a CNN to Predict Tornadoes in Non-Supercellular MCS Storms – Amanda Murphy (OU)
  • June 7: Recording 
    • International collaboration with National Meteorological Satellite Center of Korea Meteorological Administration: U-Net based model to estimate composite radar reflectivity using GK2A AMI data – Yoonjin Lee (CSU)
    • Generative AI discussion
  • June 6: Brainstorming the Future of AI in Education – Franklin Hays, OU HSC. Recording
  • May 10: Friends Don’t Let Friends Deploy Black-Box Models: The Importance of Intelligibility in Machine Learning – Rich Caruana (Microsoft). Recording
  • April 26: Envisioning Cooperative Visualization Systems – Melanie Tory (Northeastern). Recording
  • April 12: Google Research and Forecasting for Africa – Jason Hickey (Google). Recording
  • March 29: Recording 
    • Grid-Based Hail Nowcasting using UNets and WoFS NWP – Tobias Schmidt (OU)
    • Using Deep Learning to Improve the NSSL’s Warn-On-Forecast System (WoFS) Forecast of Thunderstorm Location – Chad Wiley (OU)
  • March 1: Recording
    • Comparative Visibility Estimation from New York State Mesonet Camera Images Using Deep Learning – Mel Wilson Reyes (OU) Slides
    • Synthetic Benchmarks to Study the Influence of Correlated Values on XAI for Geoscience – Evan Krell (TAMU-CC) Slides
  • February 15: Recording
    • Machine learning estimation of storm updrafts – Randy Chase (OU) Slides
    • Detecting the Presence of Precipitation in New York State Mesonet Imagery at Night using Convolutional Neural Networks – Vanessa Przyblyo (UAlbany) Slides
  • February 1: AtmoRep: Large Scale Representation Learning of Atmospheric Dynamics – Christian Lessig (Otto von Guericke University Magdeburg). Slides, Recording
  • January 18: AI in NOAA from workforce proficiency and training to new applications for tropical cyclones – Chris Slocum (NOAA). Slides, Recording

2022

  • December 7: A universal mechanism for long-term instabilities in deep learning-based digital twins for geophysical turbulence: Building seamless data-driven climate models – Ashesh Chattopadhyay (PARC). Recording
  • November 9: Human-Centered AI: Ensuring Human Control, Enhancing Human Performance – Ben Shneiderman (University of Maryland). Slides, Recording
  • October 26: Maximizing the Utility of High-Resolution Ensembles for Heavy Snowfall Forecasts – Jacob Radford (NOAA/CIRA). Recording
  • September 28: AI2ES Year 2 Research Highlights and Review summary – Amy McGovern (OU), Elizabeth Barnes (CSU), Philippe Tissot (TAMU-CC), Christopher Wirz (NCAR), Ruoying He (NCSU), Kara Sulia (UAlbany), Mariana Cains (NCAR), Phillip Davis (DMC). Recording
  • September 14: Trust and Perception of an AI System – Brian Stanton (NIST). Recording
  • August 31: Explainable Wildfire Risk Model – Gabrielle Nyirjesy (IBM intern). Recording
  • August 3: ML-ready Data – Douglas Rao (NOAA). Slides, Recording
  • July 21: David Harrison PhD Defense. Recording
  • July 20: TAMU-CC REU student presentations. Recording
    • Introduction to Coding Camp – Dara Betz and Korinne Caruso (DMC)
    • VAE predictions of coastal fog – Brian Colburn (TAMU-CC). Slides
    • Comparison of AI methods for cold stunning predictions – Christian Duff (TAMU-CC) and Jarrett Woodall (Heidelberg University). Slides
    • Comparison of AI methods for water level predictions – Ashley Marines (DMC/TAMU-CC) and Dante Ramirez (Texas Tech). Slides
    • Internship at NRL Monterrey – Beto Estrada (TAMU-CC). Recording
  • June 22: OU REU and NCAR SIParCS 5-minute talks. Recording
    • Vincent Ferrera, OU REU Slides; Justin Willson, NCAR SIParCS Slides; Alex Nozka, OU REU Slides; Chris Cepin, OU REU Slides; Kayla Hoffman, OU REU Slides; Eliot Kim, NCAR SIParCS Slides; Noah Lang, OU REU, Slides
  • June 8: Relational trust in human-agent teaming – Erin Chiou, Arizona State University. Recording
  • May 25: Prerequisites, Causes, and Goals of Human Trust in AI – Ana Marasović, Allen Institute for AI. FAccT2020 paper. Recording
  • May 11: AI2ES Postdoc Research Review (2 of 2). Recording
    • Insights and progress across the development loop – Mariana Cains, NCAR. Slides
    • Highlighting ‘depth’ of risk comm work – Christopher Wirz, NCAR. Slides
    • SpatioTemporal Modeling from Multispectral Satellite Data using Deep Learning – Akansha Singh Bansal, CIRA/CSU. Slides
    • Assessing the fidelity of eXplainable Artificial Intelligence (XAI) methods using benchmark datasets – Antonios Mamalakis, CSU. Slides
    • Ocean reanalysis data-driven machine learning prediction of Loop Current eddy movements in the Gulf of Mexico – Anna Lowe, NCSU. Slides
    • Self Introduction – Vanessa Przybylo, UAlbany. Slides
  • April 27: Defining Core Concepts & Key Terms for AI2ES – Monte Flora, NOAA; Ann Bostrom, UW; Dimitris Diochnos and  Amy McGovern, OU; Mariana Cains, NCAR. Recording; Slides
  • April 13: AI2ES Postdoc Research Review (1 of 2). Recording
    • Chase AI2ES Research Activities – Randy Chase, OU. Slides
    • AI2ES Postdoc Research Reviews – Lauriana Gaudet, UAlbany. Slides
    • Severe Weather, Explainability, and Python – Monte Flora, NOAA. Slides
    • AI2ES Postdoc Introduction – Marie McGraw, CSU. Slides
  • March 30: Trustworthy Machine Learning – Kush Varshney, IBM Research. Recording
  • March 2: Considerations in Designing and Evaluation of ‘Intelligent’ Decision Aids – Emilie Roth, Roth Cognitive Engineering. Recording 
  • February 16: Probabilistic Assessment and Decisions – John Williams, IBM; Philippe Tissot, TAMU-CC; Brian Colburn, TAMU-CC. Recording
  • February 2: Climate Research at PARC – Kalai Ramea, PARC; Recording (the primary presentation starts at the 14 minute mark)
  • January 19: Introduction to Collaborative Coding – David John Gagne and Charlie Becker, NCAR; Antonio Medrano, TAMU-CC; Kevin Tyle, UAlbany. Presentation Slides; Recording

2021

2020