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  1. AGU Members
  2. Alexander M. Tartakovsky
AT
Member Since 2000
Alexander M. Tartakovsky
Professor, University of Illinois at Urbana-Champaign
Member, Nonlinear Geophysics Fellows Committee; Associate Editor, Water Resources Research
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Professional Experience
University of Illinois at Urbana-Champaign
Professor
2020 - Present
Pacific Northwest National Laboratory
Scientist
Education
University of Arizona
Doctorate
2002
Alexander's AGU Research
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VAE-DNN: Energy-Efficient Trainable-by-Parts Surrogate Model for Groundwater Flow Modeling and Parameter Estimation
AI ADVANCES IN SUBSURFACE HYDROLOGY AND ENERGY I POSTER
hydrology | 18 december 2025
Latent-Space Surrogate Model for Fast Time-Lapse ERT Inversion
AI ADVANCES IN SUBSURFACE HYDROLOGY AND ENERGY I POSTER
hydrology | 18 december 2025
Interpretable transfer learning for training PDE surrogate models using limited data
EXPLORING SUBSURFACE TRANSPORT AND GEOMECHANICAL PROCESSES USING MACHINE LEARNING AND ARTIFICIAL INTELLIGENCE II POSTER
hydrology | 13 december 2024
Solving High-dimensional Inverse Problems Using Amortized Likelihood-Free Inference and Karhunen–Loève Expansions
EXPLORING SUBSURFACE TRANSPORT AND GEOMECHANICAL PROCESSES USING MACHINE LEARNING AND ARTIFICIAL INTELLIGENCE II POSTER
hydrology | 13 december 2024
Approximate Bayesian Parameter and State Estimation with Reduced-Order Deep Learning Surrogate Model
EXPLORING SUBSURFACE TRANSPORT AND GEOMECHANICAL PROCESSES USING MACHINE LEARNING AND ARTIFICIAL INTELLIGENCE II POSTER
hydrology | 13 december 2024
Randomized Physics-Informed Neural Networks for Bayesian Data Assimilation
DIAGNOSTICS, SENSITIVITY, AND UNCERTAINTY ANALYSIS OF EARTH AND ENVIRONMENTAL MODELS I POSTER
hydrology | 09 december 2024
Approximate Bayesian Deep Learning Surrogate Model for Parameter and State Estimation
DIAGNOSTICS, SENSITIVITY, AND UNCERTAINTY ANALYSIS OF EARTH AND ENVIRONMENTAL MODELS II ELIGHTNING
hydrology | 09 december 2024
Karhunen-Loeve–Deep Neural Network Surrogate Models for Dynamic Simulations and History Matching
PHYSICS-INFORMED AND DATA-DRIVEN MACHINE LEARNING METHODS FOR MODELING SUBSURFACE PROCESSES II POSTER
hydrology | 13 december 2023
Volunteer Experience
2026 - 2028
Member
Nonlinear Geophysics Fellows Committee
2024 - 2027
Associate Editor
Water Resources Research
2024 - 2026
Member
Hydrology-Groundwater Technical Committee
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