Earth Sciences Division Staff: Jinsong Chen

Biographical Summary

Jinsong Chen is a geological staff scientist at the Lawrence Berkeley National Laboratory. He received a B.Eng. (1988) in water-resources engineering, a B.S. (1988) in applied mathematics, and an M.Eng. (1990) in hydrology from Tsinghua University in China. He also received an M.S. (1997) in environmental fluid mechanics from Georgia Institute of Technology, an M.A. (2001) in statistics, and a Ph.D. (2001) in environmental engineering from the University of California at Berkeley. He worked in Tsinghua University from 1990 to 1995 and was a postdoctoral fellow at the University of California at Berkeley and at the Lawrence Berkeley National Laboratory from 2002 to 2003. Since 2004, he has worked as a geological scientist in the Earth Sciences Division.
His research interests are in development and applications of mathematical and statistical methods for solving complex problems in earth and environmental sciences.

Research Interests

Jinsong Chen's research focus is on the development and application of statistical and mathematical models for solving complex problems in earth and environment sciences. His interests are interdisciplinary and across surface hydrology, hydrogeology, geophysics, and statistics. His current research areas include:

• Hydrogeophysics/biogeophysics is the use of geophysical methods for imaging subsurface properties and for monitoring important processes related to hydrogeological and biogeochemical studies. One main challenge in hydrogeophysics/biogeophysics is the lack of effective methods for integrating multi-scale and multi-source information, such as geological, hydrogeological, geophysical, geochemical, and biological data. read more »
• Geophysical inverse problems are the inferences of physical properties from geophysical measurements. They are typically ill-posed because of non-uniqueness of the solutions and nonlinearity of the forward modeling. The main tasks of my research in the area: (1) To formulate inverse problems properly within a Bayesian framework, (2) To develop efficient (often problem-specific) Markov chain Monte Carlo (MCMC) sampling strategies... read more »
• Environmental Applied Statistics. Modern statistics provides a variety of methods for solving complex problems in earth and environmental sciences, such as spatial statistics (geostatistics), time series analysis, Bayesian statistics, multivariate data analysis, linear and nonlinear regression, and multiple testing techniques. Fast growing of computing power makes it possible to implement many computationally intensive methods. read more »

Education

• Ph.D. (Environmental Engineering) and M.A. (Statistics) University of California, Berkeley, CA, 2001 Thesis: Bayesian approach for subsurface characterization using hydrogeological and geophysical data (Download)
• M.S. (Environmental Fluid Mechanics) Georgia Institute of Technology, Atlanta, GA, 1997
• M.Eng. (Hydrology and Water Resources) Tsinghua University, Beijing, China, 1990
• B.Eng. (Water Resources Engineering) and B.S. (Applied Mathematics) Tsinghua University, Beijing, China, 1988

Professional Experience

• Geological scientist, Lawrence Berkeley National Laboratory, Berkeley, CA, 04/2004—Present
• Research Statistician, University of California, Berkeley, CA, 10/2005—8/2006
• Research Engineer, University of California, Berkeley, CA, 2003—2005
• Postdoctoral Fellow, Lawrence Berkeley National Laboratory, Berkeley, CA, 2003
• Postdoctoral Fellow, University of California, Berkeley, CA, 2002
• Research Scientist and Lecturer, Tsinghua University, Beijing, China, 1990—1995

Related Links

• MCMC Reprint Service
• American Geological Union (AGU)