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Dr. Liangping Li
Associate Professor
Geology and Geological Engineering
South Dakota School of Mines
501 E. Saint Joseph St., Rapid City, SD 57701
605.394.2461 | Liangping.Li@sdsmt.edu
*I am looking for motivated undergraduate and graduate students as well as visiting scholar to join my group. If you are interested, please contact me.
update: 8/16/2024
News:
Dr. Li has been appointed as an associate editor of Advances in Water Resources journal
New publication in Mathematical Geosciences: Optimization of Borehole Thermal Energy Storage Using Genetic Algorithm
New supplemental grant from NSF for two graduate student's internships working on geothermal energy in RESPEC: RII Track-4: Inverse methods of Hydraulic Fracturing for enhanced geothermal systems in a deep mine.
New publication in Advances in Water Resources: Leveraging deep learning with progressive growing GAN and ensemble smoother with multiple data assimilation for inverse modeling.
New grant from BLM: South Dakota School of Mines' internship at BLM Montana-Dakota
New grant from BLM: Environmental monitoring and water-quality sampling at the abandoned Belle Eldridge Mine site.
Dr. Li has been appointed as an interim associate head of Department of Geology and Geological Engineering
Dr. Li has been appointed as an associate editor of Mathematical Geosciences journal
New publication in Advances in Water Resources: Stochastic Inversion of Discrete Fracture Networks Using Genetic Algorithms
New publication in Hydrogeology journal: Progressive Growing Generative Adversarial Networks Using Conditioning Ratio for Facies Modeling in Complex Aquifers
New supplemental grant from NSF for a graduate student's internship working on geothermal energy in RESPEC: RII Track-4: Inverse methods of Hydraulic Fracturing for enhanced geothermal systems in a deep mine
New publication in Mathematical Geosciences: Teaching Groundwater Flow and Contaminant Transport Modeling via a Sand-Tank Model
New publication in Mathematical Geosciences: Variational Autoencoder or Generative Adversarial Networks? A Comparison of Two Deep Learning Methods for Flow and Transport Data Assimilation
Dr. Li has been promoted to Associate Professor with tenure
New publication in Frontiers in Eearth Sciences: Stochastic Modeling in Hydrogeology
New publication in Mathematical Geosciences: Special Issue: IAMG 2019
New publication in Journal of Hydrology: Coupling ensembel smoother and deep learning with generative adversiral networks for handling non-Gaussianity in flow and transport data assimilation
New publication in Advances in Water Resources: A novel method for well placement design in groundwater management: extremal optimization
New grant from NSF: RII Track-4: Inverse methods of Hydraulic Fracturing for enhanced geothermal systems in a deep mine
New publication in Mathematical Geosciences: A comparison of extremal optimization, differntial evolution and particle swarm optimization methods for well placement dsign in groundwater management
New publication in Journal of Hydrology: Bridging iterative ensemble smoother and multiple-point geostatistics for better flow and transport modeling
New publication in Groundwater: Calibration of a land subsidence model using InSAR data via ensemble Kalman filter