Daniel Arnold is a research scientist in the Grid Integration Group at Lawrence Berkeley National Laboratory. He received the
B.S. degree in mechanical engineering from the University of California, San Diego, in 2005, the M.S. degree in engineering science from the University of California, San Diego, in 2006. From 2006 to 2009 he conducted research and development of unmanned
underwater vehicles for the United States Navy at the Space and Naval Warfare Center in San Diego, California. He then received his Ph.D. from the Mechanical Engineering Dept. at the University of California, Berkeley in 2015. He was a 2015 ITRI-Rosenfeld
Postdoctoral Fellow at the Lawrence Berkeley National Laboratory. Presently, his research focuses on the application of control,
optimization, and machine learning techniques for electric grid resiliency and cyber security.