He is a computer scientist in the Global Security Sciences Division at Argonne National Laboratory working on a variety of Modeling and Simulation (M&S) projects. He is an integral part of the Analysis of Mobility Platforms (AMP) logistics modeling project for U.S. Transportation Command. He has also been the lead investigator on a program for the Naval Research Laboratory doing Electronic Warfare (EW) M&S, which includes both EW system modeling as well as detailed Radio Frequency (RF) propagation modeling in complex environments. Among his research interests is the development of remotely distributed deep-learning image recognition systems for Unmanned Aerial Systems (UAS) detection. He participated in numerous government and military test and evaluation events for UAS mitigation systems and did analysis on UAS threats to critical infrastructure and methods for protection. He graduated from Carnegie Mellon University with a degree in computer science and robotics and is currently pursuing a master's in analytics at the University of Chicago with an emphasis on advanced computational models, including computer vision and machine learning algorithms.
He is a staff scientist at Idaho National Laboratory (INL) and a recognized expert in materials characterization and instrumentation. He has a doctorate in materials science and condenser matter physics from the University of California, Davis. His work has spanned global and nationwide collaborations. He has worked at premier nanocharacterization facilities at national laboratories and universities and has expert knowledge of scanning transmission electron microscopy, atom probe tomography and electron loss spectroscopy. His primary research interests lie in the investigation of materials and the origins of their physical properties. He has heavily leveraged the use of multidimensional microscopy, diffraction and artificial intelligence to address delays in data access and extraction, which has led to a new frontier in advanced microscopy. At INL, he continues to focus on the development and application of machine and deep learning in order to decipher and decimate information from images, spectra, and diffraction patterns to maximize the effectiveness, efficiency and utility of advanced microscopy. He is an invited academic faculty member and manager for a diverse group of postdoctoral research scientists, graduate students, and technicians across several national laboratories and universities. He is an author of 45 peer-reviewed publications, a recognized reviewer, and a technical contributing member to energy materials research. He was awarded two patents and has three patents pending, including an innovative approach to computational microscopy using machine learning.
He received a doctorate in computer science at the University of Tennessee in 2009, master’s in computer systems and software design, and his bachelor’s with a double major in computer science and mathematics with physics from Jacksonville State University. His research spans government-scale database and management systems, graphical user interface design, medical software used for surgery, gesture recognition, graph-theoretic analysis, optimization, automation, systems genetic research, magnetic resonance imaging, image processing, artificial intelligence, supercomputing, and energy-efficient buildings. He currently serves at Oak Ridge National Laboratory’s Building Technologies Research & Integration Center (BTRIC) as a subprogram manager for software tools and models with oversight of projects, involving websites, web services, databases, simulation engine development, visual analytics, supercomputing, and artificial intelligence. He has lead creation of the world’s most accurate method for calibrating a simulation model to measured data, fastest building model creator, fastest buildings simulator, and largest archive of simulated building data. He is a joint faculty member at the University of Tennessee’s Electrical Engineering and Computer Science Department, and an active member of American Society of Heating, Refrigerating and Air-Conditioning Engineers and Institute of Electrical and Electronics Engineers.
His expertise includes the application of small Unmanned Aircraft Systems (sUAS) to homeland and national security needs. Argonne National Laboratory’s expertise in this area includes worldwide databases of commercial sUAS technologies and sUAS regulatory frameworks, risk assessment methodologies applied to sUAS threat environments, and the use of sUAS for critical infrastructure monitoring/damage assessment and emergency response. He received his master’s degree from the Johns Hopkins University and his doctorate from Cornell University.
He is the lead for Cyber Operations, Analysis, and Research in Argonne National Laboratory’s Global Security Sciences Division. He is considered a key asset by the U.S. Department of Homeland Security (DHS) for the development of a cybersecurity vulnerability assessment for field use, analysis of cyber-security consequence and threat studies, and leading the pilot cyber-physical regional assessment. Prior to joining Argonne, he managed cyber-security and cyber defense activities at several private-sector companies and involved in the development of a patented operational instance of moving target defense (MTD). He worked in a variety of other cybersecurity research areas, including transportation, satellite communications, social engineering, and offensive cybersecurity. He taught computer networking and cyber-security issues to students in Senegal, Africa through the African Institute for Mathematical Sciences (AIMS) Next Einstein Initiative, a collaboration with the University of Chicago, Argonne, and other institutions.
Lawrence “Paul” Lewis is the Program Lead for Technology Implementation in the Decision and Infrastructure Sciences Division. In this capacity, Paul leads multidisciplinary analyses of critical infrastructure protection and community resilience strategies across the country, and the development of decision support tools to address these challenges. Paul’s primary project is support of the U.S. Department of Homeland Security Office of Infrastructure Protection’s Regional Resiliency Assessment Program (RRAP), which seeks to identify single points of system failure, opportunities for closing gaps in coordinated preparedness, and address potential consequences of cascading impacts to interdependent social and physical infrastructure.
In addition, Paul has developed decision support tools for international humanitarian assistance programs for the U.S. Department of Defense, energy supply chain security programs for the U.S. Department of Energy, and served as lead social scientist in the development of community resiliency frameworks for Argonne’s Center for Integrated Resiliency Analysis. Paul is also a Lecturer in the Threat and Response Management program at the University of Chicago, where he teaches a course on emergency management policymaking, law, and ethics. Paul received his B.A. and M.A. from Tulane University in New Orleans, his J.D. from Tulane University Law School, and his M.S. from the University of Chicago.