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.
Grant is the program manager for cybersecurity research in the Division of Chemical and Biological Sciences (DCBS) at Ames Laboratory. His focus has been on developing software for integrations with cyber defensive tools for the automated cyber threat information sharing program, the Cyber Fed Model (CFM), at Argonne National Laboratory. Additionally, he has provided expertise in research projects developing correlation of publicly exposed devices with vulnerabilities and machine learning for intrusion detection of grid systems. Prior to joining Ames Laboratory, he was in the Aerospace industry in various product development and management roles with formerly United Technologies Aerospace Systems. This included supporting development of cybersecurity policy and secure development life cycles for safety critical systems as well as secure design and assessment of real-time systems bridging security domains on various aircraft network busses. He received an M.S. in technology management from the University of St. Thomas and B.S. in computer engineering from Iowa State University.
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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