معرفی
Lijing Wang is an Assistant Professor at the University of Connecticut, specializing in geostatistics and hydrogeology. Her research focuses on integrating hydrologic modeling with multiscale datasets to explore watershed and aquifer dynamics, quantifying uncertainties through machine learning and Bayesian methods. She co-authored the textbook Data Science for the Geosciences, emphasizing data science education for geoscientists.
Education: Ph.D. in Geological Sciences from Stanford University (with a minor in Computer Science) and B.S. in Space Physics and Applied Mathematics from Peking University.
Her research interests include subsurface heterogeneity, snow dynamics in mountainous regions, and climate impacts on hydrology. She develops advanced statistical and computational tools for geophysical inversion and uncertainty quantification. Her work also explores the application of surrogate models for environmental decision-making under climate change scenarios.
Key contributions include the GStatSim software package for geostatistical analysis and collaborations on Antarctic ice shelf bathymetry modeling. Her research bridges geoscience and data science, addressing challenges in mineral exploration, groundwater contamination, and climate resilience.
