Invited Talks

  • 08/31/2023, IEEE J-MMCT, Online: Physics-guided Deep Learning Methods for Time Domain EM Simulations [video]
  • 01/27/2021, Katy Drilling Software Center (KDSC) at Schlumberger, Houston: Physics-guided machine learning/deep learning for forward & inverse modeling

Workshop Presentation

  • Yanyan Hu, “Deep Learning Enhanced Joint Inversion for Multiple-physics Data”, Workshop on IMAGE ‘23: Energy Transition: How to use multidiscipline and multiphysics to power energy transition? 2023. [News Posts]

Oral Presentations

  • Yanyan Hu, et al., “Deep Learning Enhanced Joint Inversion for Mineral Exploration Using Airborne Geophysics: Application in Decorah Area”, IMAGE ‘23 , the joint SEG/AAPE Annual Meeting, 2023.
  • Yanyan Hu, et al., “Deep learning enhanced 3D joint inversion”, XXXVth URSI General Assembly and Scientific Symposium, Sapporo, Japan, Aug. 2023.
  • Yanyan Hu, et al., “Simulating Time Domain Electromagnetic Waves on a Differentiable Programming Platform”, The International Council for Industrial and Applied Mathematics (ICIAM) , Tokyo, Japan, Aug. 2023.
  • Yanyan Hu, et al., “Deep Perceptual Loss for Multi-Physics Joint Inversion”, 83rd EAGE Annual Conference & Exhibition, 2022. [Abstract]
  • Yanyan Hu, et al., “Deep Learning Enhanced Joint Inversion of Multiphysics Data with Nonconforming Discretization”, 2021 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting (APS/URSI), 2021. [Abstract]
  • Yanyan Hu, et al., “Deep Learning-Enhanced Multiphysics Joint Inversion”, IMAGE ‘21 , the joint SEG/AAPE Annual Meeting, 2021. [Abstract]
  • Y. Jin, Yanyan Hu, X. Wu, J. Chen, “RNN-based Gradient Prediction for Solving Magnetotelluric Inverse Problem”, SEG International Exposition and Annual Meeting, 2020. [Abstract]
  • S. Wnag, W. Hu, Yanyan Hu, X. Wu, J. Chen, “A Physics-augmented Deep Learning Method for Seismic Data Deblending”, SEG International Exposition and Annual Meeting, 2020. [Abstract]
  • Yanyan Hu, et al., “A Supervised Descent Learning Technique for Inversion of Directional Electromagnetic Logging-While-Drilling Data”, SEG International Exposition and Annual Meeting, 2020. [Abstract]
  • Yanyan Hu, et al., “A Physics-driven Deep-learning Inverse Solver for Subsurface Sensing”, 2020 IEEE USNC-CNC-URSI North American Radio Science Meeting (Joint with AP-S Symposium), 2020. [Abstract]
  • Yanyan Hu, et al., “Solving Time Domain Electromagnetic Problems using a Differentiable Programming Platform”, 2020 IEEE USNC-CNC-URSI North American Radio Science Meeting (Joint with AP-S Symposium), 2020. [Abstract]

Poster Presentations

  • Yanyan Hu, et al., “Deep Learning Enhanced Joint Inversion for Monitoring of Underground CO2 Storage Sites”, UH Energy Research Day, 2023. [Poster] [News Posts]
  • Yanyan Hu, et al., “A flexible and versatile joint inversion framework using deep learning”, IMAGE ‘22 , the joint SEG/AAPE Annual Meeting, 2022. [Poster]