He received his BS in chemical engineering at Michigan State University (2001) while also working as a research assistant in the Composite Materials and Structures Center under the supervision of Dr. Lawrence T. Drzal. He completed his MS (2003) and PhD (2006) in chemical engineering at Stanford University under the direction of Prof. Stacey F. Bent in collaborative research project with IBM T. J. Watson Research Center’s Drs. Nicholas C. Fuller and Stephen M. Gates studying the interactions between ashing plasmas and low-k dielectric thin films. He was a Postdoctoral Fellow at Lawrence Livermore National Laboratory (2006-2008) before his current position as a Staff Scientist in the Advanced Materials Synthesis group. Currently, his research focuses on nanostructured and porous materials (e.g. aerogels and functional nanocomposites) for a wide range of applications, such as energy storage, sensing, and catalysis. This includes both the development of materials with novel properties and the development of feedstock materials for various additive manufacturing (a.k.a. 3D printing) techniques.
He is a staff scientist in the Computational Engineering Division at LLNL. He currently supports project acquisition and execution in the areas of building energy efficiency control optimization, power system simulation, and hybrid artificial intelligence and optimization control served as Principal Investigator. He was research scientist for energy system analysis at LBNL in Berkeley, CA, and the section manager for renewable energy investment, operation manager for power generation at Huaneng Power Group in Beijing, China. Dr. Qin received the B.S. M.S. and PhD degrees in electrical engineering and computer science from the University of Dalian Tech, Dalian, with emphasis on advanced control theory. He served as researcher for building energy automated control and power system operation for more than 20 years. His patent technology – commercial building optimization won the first Energy I-Corps of DOE in 2015. His areas of expertise include building energy modeling-simulation-optimization, power generation & transmission & Distribution optimization, smart grid, deep learning, complex system optimization, and optimization analytics for near-field.
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