Talks and Presentations

  1. Tutorial lead - Neural Networks in Tensorflow in Intro to AI-driven Science on Supercomputers: A Student Training Series , October 4, 22.
  2. Tutorial lead - Deep Learning Methods (talk/hands-on) at an Argonne training program on extreme-scale computing (ATPESC) on August 12, 2022.
  3. Contributed talk - Jointly presented our work on programmatic labeling and weak supervised learning approaches for extracting climate change impacts and geography-specific adaptation strategies from a large corpus of scientific literature on the future of data-centric AI by Snorkel, 2nd August 2022.
  4. Tutorial lead - Transfer learning in the hyperparameter search session and hands-on in the Deephyper workshop, July 15, 2022.
  5. Talk - Accelerating graph convolution based deep learning framework for large scale highway traffic forecasting with sambanova, Usecase presentation in SambaNova training workshop, June 16, 2021.
  6. Talk - Spatiotemporal learning for climate modeling using graph neural network, Climate and Energy Action Initiative Town Hall on Advancing Predictive Climate Science, June 8, 2021.
  7. Talk - Accelerating graph convolution based deep learning framework for large scale highway traffic forecasting with sambanova, Usecase presentation in SambaNova training workshop, June 16, 2021.
  8. Talk - Spatiotemporal learning for climate modeling using graph neural network, Climate and Energy Action Initiative Town Hall on Advancing Predictive Climate Science, June 8, 2021.
  9. Talk - Graph-Partitioning-Based Diffusion Convolution Recurrent Neural Network for Large-Scale Traffic Forecasting, AI and HPC Seminar, Argonne National Laboratory, 2020.
  10. Talk - Graph-Partitioning-Based Diffusion Convolution Recurrent Neural Network for Large-Scale Traffic Forecasting, CELS Computing Coffee Hours, Argonne National Laboratory, 2020.
  11. Tutorial lead - Diffusion convolution recurrent neural network for traffic forecasting, Argonne Training Program on Extreme-Scale Computing (ATPESC) 2019 -- Presentation Video
  12. Talk - Graph-Partitioning-Based Diffusion Convolution Recurrent Neural Network for Large-Scale Traffic Forecasting, Postdoc society e-seminar, Argonne National Laboratory, 2019.
  13. Presentation - Graph-Partitioning-Based Diffusion Convolution Recurrent Neural Network forLarge-Scale Traffic Forecasting, Transportation Research Board (TRB 2020).
  14. Invited participant - Department of Energy - AI for Science Townhall, Lawrence Berkeley National Laboratory, 2019.
  15. Invited talk - Diffusion Convolution Recurrent Neural Network for Traffic Forecasting, Argonne Physical Sciences and Engineering (PSE) AI in Science and Engineering Townhall Meetings, 2019.
  16. Tutorial lead - Object detection using machine learning, Argonne Leadership Computing Facility (ALCF) AI4Science tutorial, Argonne National Laboratory, 2019.