Full Workshop Agenda, (PDF, 197 KB)
+ Thursday, 30 July 2020 Session 1: Overview Talks, Part 1
Time |
Title |
Speaker |
1:00 - 1:05 p.m. |
Information on the 2nd NOAA AI Workshop: Logistics, Timeline and Structure, (PPTX, 8.33 MB) |
Kevin Garrett (NOAA/NESDIS/STAR, Local Organizing Committee) |
1:05 - 1:15 p.m. |
Welcoming remarks and introduction of keynote speakers |
Harry Cikanek (NOAA/NESDIS, STAR Director) |
1:15 - 1:25 p.m. |
Keynote Address, NOAA AI: Realizing Transformational Advances in Mission Performance and Our Culture of Innovation |
RADM Timothy Gallaudet (NOAA, Deputy NOAA Administrator) |
1:25 - 1:35 p.m. |
Keynote Address |
Stephen Volz (NOAA, NESDIS Assistant Administrator) |
1:35 - 1:45 p.m. |
Keynote Address, (PDF, 2.49 MB) |
Nicole LeBoeuf (NOAA, NOS Acting Assistant Administrator) |
1:45 - 2:00 p.m. |
NOAA AI Implementation Plan, (PPTX, 40.97 MB) |
Bill Michaels (NOAA, NMFS) |
2:00 - 2:20 p.m. |
Efforts in NOAA to Leverage Modern AI techniques for Satellite Data Exploitation and NWP, (PPTX, 169.55 MB) |
Sid Boukabara (NOAA/NESDIS, STAR Principal Scientist) |
2:20 - 2:40 p.m. |
Machine Learning at ECMWF, (PPTX, 15.98 MB) |
Peter Dueben (ECMWF) |
2:40 - 3:00 p.m. |
Panel Discussion |
facilitated by H. Cikanek; Panelists: Dr. Volz, Dr. Jamese Sims, N. LeBoeuf, B. Michaels |
+ Thursday, 6 August 2020 Session 2: Fundamentals of AI, Part 1
Chairs: Dave Turner (NOAA. ESRL), Jebb Stewart (NOAA, ESRL)
+ Thursday, 13 August 2020 Session 3: Looking Ahead (Using AI for NOAA mission), Part 1
Chairs: Bill Michaels (NOAA, NMFS), John Ten Hoeve (Office of Organizational Excellence)
Time |
Title |
Speaker |
12:00 - 12:30 p.m. |
NOAA Center for AI (NCAI) Introduction, (PPTX, 60.95 MB) |
Bill Michaels (AI S&T Chair), Mary Wohlgemuth (NCEI Director),
Eric Kihn (NCEI CCOG Director), Rob Redmon (NCAI Acting Director, LCDP XI) |
12:30 - 1:00 p.m. |
NCAI Community of Practice (CoMP) |
Eric Kihn (NCEI CCOG Director), Rob Redmon (NCAI Acting Director, LCDP XI) |
1:00 - 1:30 p.m. |
NCAI CoMP Capabilities Discussion
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+ Thursday, 20 August 2020 Session 4: AI/ML for Post-Processing and Data dissemination, Part 1
Chairs: Greg Dusek (NOAA/NOS), Andre van der Westhuysen (IMSG at NWS/NCEP/EMC)
Time |
Title |
Speaker |
12:00 - 12:40 p.m. |
Artificial Intelligence for Advanced Earth Science Information Systems |
Jacqueline Le Moigne (NASA) |
12:40 - 1:10 p.m. |
Using Random Forests to Create Probabilistic Next-Day Severe Weather Guidance from NWP Ensembles, (PPTX, 112.77 MB) |
Eric Loken (OU CIMMS/OU) |
1:10 - 1:40 p.m. |
Modeling Clouds From Sub-grid to Global Scales with Deep Generative Models |
Tianle Yuan (NASA GSFC/UMBC JCET) |
1:40 - 2:00 p.m. |
Panel Discussion |
Panelists: Session Chairs & Speakers |
+ Thursday, 27 August 2020 Session 5: AI/ML for Environmental Data, Image, and Signal Processing, Part 1
Chairs: Imme Ebert-Uphoff (CIRA), Ryan Lagerquist (CIRA/NOAA-GSD)
+ Thursday, 3 September 2020 Session 6: AI/ML for Information Extraction from Data, Part 1
Chairs: Philippe Tissot (Texas A&M University, Corpus Christi), Jebb Stewart (NOAA, ESRL)
+ Thursday, 10 September 2020 Session 7: Fundamentals of AI, Part 2
Chairs: Amy McGovern (OU), David Hall (NVIDIA)
+ Thursday, 17 September 2020 Session 8: Machine Learning Tools and Best Practices, Part 1
Chairs: Sue Haupt (NCAR), Jason Hickey (Google)
+ Tuesday, 22 September 2020 Session 9: Tutorial 1
Time |
Title |
Speaker |
12:00 - 2:00 p.m |
Tutorial on Video and Image Analytics for Marine Environments (VIAME), a Do-It-Yourself AI Toolkit |
Matt Dawkins, Anthony Hoogs (Kitware) |
+ Thursday, 24 September 2020 Session 10: AI/ML for Post-Processing and Data dissemination, Part 2
Chairs: Nikunj Oza (NASA), Allen Huang (UW-Madison)
Time |
Title |
Speaker |
12:00 - 12:20 p.m |
The role of machine learning in a seamless modeling approach from weather to climate time scales, (PDF, 13.06 MB) |
V. Balaji (NOAA/GFDL) |
12:20 - 12:40 p.m |
Elucidating Ecological Complexity: Unsupervised Learning determines global marine eco-provinces, (PDF, 51.24 MB) |
Maike Sonnewald (NOAA/GFDL) |
12:40 - 1:00 p.m. |
Accelerating Google's Flood Forecasting Initiative with Tensor Processing Units, (PDF, 4.26 MB) |
Vova Anisimov, Anudhyan Boral, Lily Hu, Sella Nevo, Damien Pierce, Yusef Shafi (Google Research) |
1:00 - 1:20 p.m. |
Predicting global cloud ceiling values with machine learning |
Mihai Alexe (Spire Global) |
1:20 - 1:45 p.m. |
Panel Discussion |
Panelists: Session Chairs & Speakers |
+ Tuesday, 29 September 2020 Session 11: Poster Session I
Chair: Kevin Garrett (NOAA/NESDIS/STAR)
Time |
Title |
Speaker |
12:00 - 2:00 p.m |
Modelling runoff from green roofs using Deep Neural Networks, (PDF, 1.02 MB) |
Elhadi Abdalla (NTNU) |
12:00 - 2:00 p.m |
Fine-Delineated Tropical Cyclone Detection from Geostationary Satellites and IBTrACS data using Advanced Neural Networks, (PDF, 26.2 MB) |
Ata Akbari Asanjan (Universities Space Research Association) |
12:00 - 2:00 p.m |
Pixel-wise Deep Sequence learning for wildfire spread prediction in Alberta, Canada, (PDF, 2.08 MB) |
Xinli Cai (University of Alberta) |
12:00 - 2:00 p.m |
Using deep super-resolution for high resolution precipitation images, (PDF, 5.76 MB) |
Xinli Cai (University of Alberta) |
12:00 - 2:00 p.m |
Lightning prediction in the Atlantic offshore region, (PDF, 1.01 MB) |
John Cintineo (University of Wisconsin -- Madison) |
12:00 - 2:00 p.m |
Connecting ocean physical and biogeochemical properties with the spatial distribution of mesopelagic fish abundance, (PDF, 3.85 MB) |
Donglai Gong (Virginia Institute of Marine Science - William & Mary) |
12:00 - 2:00 p.m |
Using Data Mining Decision Tree Method to Identify the Optimal Fire Detection Thresholds, (PDF, 876 KB) |
Yingxin Gu (IMSG at NOAA/NESDIS/STAR) |
12:00 - 2:00 p.m |
Application of Advanced Deep Learning Algorithms in Precipitation Estimation from Multiple Sources of Information, (PDF, 11.3 MB) |
Negin Hayatbini (University of California, Irvine) |
12:00 - 2:00 p.m |
Low Cloud Detection for the GOES ABI using a Random Forest Classifier, (PDF, 15.65 MB) |
John Haynes (CIRA / Colorado State University) |
12:00 - 2:00 p.m |
3D Convolutional Deep Learning for Coastal Fog Predictions, (PDF, 1.68 MB) |
Hamid Kamangir (Texas A&M University-Corpus Christi) |
12:00 - 2:00 p.m |
Verification of a Machine Learning Algorithm in the Prediction of Flash Flooding, (PDF, 2.61 MB) |
Mark Klein (NWS/Weather Prediction Center) |
12:00 - 2:00 p.m |
Utilizing CNN's to produce Quantitative Precipitation Estimates, (PDF, 2.09 MB) |
Micheal Simpson (University of Oklahoma) |
12:00 - 2:00 p.m |
Refining aerosol optical depth retrievals over land by constructing the relationship of spectral surface reflectances through deep learning: application to Himawari-8, (PDF, 4.6 MB) |
Tianning Su (UMD) |
+ Thursday, 1 October 2020 Session 12: AI/ML for Models Parameterization, Emulation, and Hybrid Model/AI Construct, Part 1
Chairs: Vladimir Krasnopolsky (NOAA/NCEP/EMC), Kayo Ide (UMD)
+ Thursday, 15 October 2020 Session 13: AI/ML for Data Fusion/Assimilation, Part 1
Chairs: Peter Jan van Leeuwen (CSU), Steve Penny (NOAA PSD/CIRES)
+ Tuesday, 20 October 2020 Session 14: Tutorial 2
Time |
Title |
Speaker |
12:00 - 2:00 p.m. |
Learning the Fundamentals of Machine Learning through Forecasting El Niño |
Karthik Kashinath, Ankur Mahesh (LBL, ClimateAI) |
+ Thursday, 22 October 2020 Session 15: AI for Innovation: New Ways to Exploit Environmental Data, Part 1
Chairs:Christina Kumler (CIRES/NOAA/GSL), Jeremy McGibbon (Vulcan)
+ Thursday, 29 October 2020 Session 16: AI/ML for Post-Processing and Data Dissemination, Part 3
Chairs: John K. Williams (The Weather Company, an IBM Business), Maike Sonnewald (NOAA/GFDL)
+ Thursday, 5 November 2020 Session 17: AI/ML for Post-Processing and Data dissemination, Part 4
Chairs: Andre van der Westhuysen (IMSG at NWS/NCEP/EMC), William Collins (LBNL, UC Berkeley)
+ Tuesday, 10 November 2020 Session 18: Tutorial 3
+ Thursday, 12 November 2020 Session 19: AI/ML for Environmental Data, Image, and Signal Processing, Part 2
Chairs: Imme Ebert-Uphoff (CIRA), Ryan Lagerquist (CIRA/NOAA-GSD)
+ Thursday, 19 November 2020 Session 20: Looking Ahead (Using AI for NOAA mission), Part 2
Chairs: Michael Pavolonis (NESDIS/STAR), Philippe Tissot (Texas A&M University, Corpus Christi)
+ Tuesday, 1 December 2020 Session 21: Tutorial 4
Time |
Title |
Speaker |
12:00 - 2:00 p.m. |
Traditional Machine Learning Pipeline Applied to NWP Model Data |
Amanda Burke (OU) |
+ Thursday, 3 December 2020 Session 22: AI/ML for Models Parameterization, Emulation, and Hybrid Model/AI Construct, Part 2
Chairs: Likun Wang (ESSIC, University of Maryland), Ashesh Chattopadhyay (Rice University)
+ Tuesday, 15 December 2020 Session 23: Poster Session II
Time |
Title |
Speaker |
12:00 - 2:00 p.m. |
Poster Session: Lightning Round / Overview |
Katherine Lukens - moderator; all poster presenters will contribute |
12:00 - 2:00 p.m. |
Breakout Rooms |
Click for details |
+ Thursday, 17 December 2020 Session 24: AI/ML for Environmental Data, Image, and Signal Processing, Part 3
Chairs: Harry Cikanek (NOAA/NESDIS, STAR Director), Xiaoming Liu (NOAA/NESDIS/STAR)
+ Thursday, 7 January 2021 Session 25: AI/ML for Data Fusion/Assimilation, Part 2
Chairs: Steve Penny (NOAA PSD/CIRES), Kayo Ide (UMD)
+ Thursday, 21 January 2021 Session 26: AI/ML for Information Extraction from Data, Part 2
Chairs: Shannon Rankin (Southwest Fisheries Science Center, NMFS), Matt Dornback (NOAA/OAR/OER)
+ Thursday, 28 January 2021 Session 27: AI/ML for Information Extraction from Data, Part 3
Chairs:Guangming Zheng (NOAA/NESDIS/STAR), Mark Veillette (MIT-LL)
+ Thursday, 4 February 2021 Session 28: Machine Learning Tools and Best Practices, Part 2
Chairs: Sanjay Purushotham (UMBC) , Mu-Chieh Ko (NOAA/AOML/HRD)
+ Thursday, 11 February 2021 Session 29: AI/ML for Environmental Data, Image, and Signal Processing, Part 4
Chairs: Chris Slocum (NOAA/NESDIS/STAR) and Jitendra Kumar (Oak Ridge National Laboratory)
+ Thursday, 18 February 2021 Session 30: AI/ML for Environmental Data, Image, and Signal Processing, Part 5
Chairs: Manil Maskey (NASA), George Cutter (NOAA Fisheries)
Time |
Title |
Speaker |
12:00 - 12:20 p.m. |
Mapping Arctic Vegetation using Hyperspectral Airborne Remote Sensing Data, (PDF, 21.74 MB) |
Venkata S. Konduri - Northeastern University & Oak Ridge National Laboratory |
12:20 - 12:40 p.m. |
Deep learning-based precipitation retrieval using passive microwave observations, (PDF, 4.17 MB) |
Yeji Choi - SI Analytics |
12:40 - 1:00 p.m. |
A spatiotemporal quantification of the relative importance of indicator inputs for drought estimation, (PDF, 2.26 MB) |
Soni Yatheendradas - UMD/ESSIC & NASA/GSFC |
1:00 - 1:20 p.m. |
Development of a Machine Learning-Based Radiometric Bias Correction for NOAA's Microwave Integrated Retrieval System (MiRS), (PPTX, 12.85 MB) |
Yan Zhou - UMD/ESSIC/CISESS |
1:20 - 1:40 p.m. |
Radar Reflectivity Surface Rainfall Retrieval with cGAN Algorithm: An Idealized Study, (PPTX, 9.54 MB) |
Shujia Zhou - NASA GSFC |
1:40 - 2:00 p.m. |
Panel Discussion |
Panelists: Session Chairs & Speakers |
+ Tuesday, 23 February 2021 Session 31: Tutorial 5
+ Wednesday, 24 February 2021 Session 32: Tutorial 6
+ Thursday, 25 February 2021 Session 33: AI for Innovation: New Ways to Exploit Environmental Data, Part 2
Chairs: Forrest M. Hoffman (Oak Ridge National Laboratory), Soni Yatheendradas (UMD/ESSIC & NASA/GSFC)
Time |
Title |
Speaker |
12:00 - 12:20 p.m. |
Energy efficiency and security aspects of Smart Homes, (PPTX, 37.35 MB) |
Olivera Kotevska - Oak Ridge National Laboratory |
12:20 - 12:40 p.m. |
Benefits of modeling interdependent environmental variables, streamflow and stream temperature, with deep learning |
Negin Hayatbini - Scripps/CW3E/UCSD |
12:40 - 1:00 p.m. |
Benefits of modeling interdependent environmental variables, streamflow and stream temperature, with deep learning, (PDF, 1.93 MB) |
Jeffrey Sadler - USGS |
1:00 - 1:30 p.m. |
Panel Discussion |
Panelists: Session Chairs & Speakers |
1:30 - 2:15 p.m. |
Workshop Science Committee Panel:
Achieving Efficiency and Added Value in Environmental Science Through AI:
The power of Govt/Academia/Private Partnership, (PDF, 5.28 MB) |
Science Committee Panelists: Sid Boukabara (NOAA/NESDIS/STAR) Chair; Vladimir Krasnopolsky (NOAA/NWS/NCEP) Co-Chair; Jebb Stewart (NOAA/OAR/ESRL); Nikunj Oza (NASA/Ames and NASA/ESTO) ; Greg Dusek (NOS); Amy McGovern (Univ. Of Oklahoma, AMS AI Committee Member); Allen Huang (Univ. Of Wisconsin); Phillip Tissot (Texas A&M-Corpus Christi, AMS AI Committee Member); Sue E. Haupt (NCAR); Jason Hickey (Google Inc.) John Williams (The Weather Company, an IBM Business) David Hall (NVIDIA) |
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