Lance Menthe

Senior Physical Scientist; Professor of Policy Analysis, Pardee RAND Graduate School

Santa Monica Office

Education

Ph.D. in physics, University of California, Los Angeles; M.S. in physics, University of California, Los Angeles; B.A. in physics, economics, University of California, Berkeley

One Page Bio

Overview

Lance Menthe (he/him) is a senior physical scientist at RAND and a member of the Pardee RAND Graduate School faculty. He works primarily on command and control, intelligence, surveillance, and reconnaissance issues for the U.S. Air Force and U.S. Army, including the use of artificial intelligence. Menthe is the lead developer of RAND's Systems and CONOPs Operational Effectiveness Model (SCOPEM), an agent-based model of air, ground, and space domains. Prior to joining RAND, Menthe received a Ph.D. in physics from the University of California, Los Angeles, with a thesis on the physics of twisting conformations of DNA.

Research Focus

Recent Projects

Close Air Support for COIN/CT
Closing the PED Gap
Defining Characteristics for the Army's Next-Generation Aerial ISR Fleet
Optimizing Army Intelligence with Artificial Intelligence and Machine Learning
Building a Bridge to the Future Joint All-Domain Command & Control Sensing Grid

Selected Publications

Menthe, Lance, Dahlia Anne Goldfeld, Abbie Tingstad, Sherrill Lingel, Edward Geist, Donald Brunk, Amanda Wicker, Sarah Lovell, Balys Gintautas, Anne Stickells, and Amado Cordova, Technology Innovation and the Future of Air Force Intelligence Analysis: Volume 1, Findings and Recommendations, RAND Corporation (RR-A341-1), 2021

Menthe, Lance, Myron Hura, and Carl Rhodes, The Effectiveness of Remotely Piloted Aircraft in a Permissive Hunter-Killer Scenario, RAND Corporation (RR-276-AF), 2014

Lance Menthe, Amado Cordova, Carl Rhodes, Rachel Costello, Jeffrey Sullivan, The Future of Air Force Motion Imagery Exploitation: Lessons from the Commercial World, RAND (TR-1133), 2012

Menthe, Lance, Jeffrey Sullivan, A RAND Analysis Tool for Intelligence, Surveillance, and Reconnaissance: The Collections Operations Model, RAND Corporation (TR-557-AF), 2008

Honors & Awards

Research Excellence Award 2011, RAND Project AIR FORCE
Bronze Medal Award 2023, RAND

Publications

Report
Data-Enabled Approaches for Enhancing the Air Force Transformational Capability Pipeline
To aid the Air Force Transformational Capabilities Office, the authors of the report developed a data science tool to extract information from free-text descriptions. They demonstrate the tool and foresight methods in three case studies.
Mar 23, 2023
Report
Outsmarting Agile Adversaries in the Electromagnetic Spectrum: Executive Summary
This executive summary encapsulates the findings in Outsmarting Agile Adversaries in the Electromagnetic Spectrum (RR-A981-1) 2023.
Jan 19, 2023
Report
Outsmarting Agile Adversaries in the Electromagnetic Spectrum
RAND researchers conducted case studies comprising key elements necessary for creating near-real-time, autonomous, inflight software reprogramming and artificial intelligence–enabled cognitive electronic warfare capabilities for the U.S. Air Force.
Jan 19, 2023
Report
Graph Theoretic Algorithms for the Ground Based Strategic Deterrent Program: Prioritization and Scheduling
The Ground Based Strategic Deterrent program is large and complex and has many interdependent tasks that must proceed efficiently. The authors of this report present novel methods to help program managers avoid rework and reduce schedule risk.
Nov 8, 2021
Report
Exploring the Feasibility and Utility of Machine Learning-Assisted Command and Control: Volume 1, Findings and Recommendations
This report describes the potential for artificial intelligence (AI) systems to assist in Air Force command and control (C2). The authors develop a framework and metrics for assessing the suitability of a given AI system for a given C2 problem.
Jul 15, 2021
Report
Exploring the Feasibility and Utility of Machine Learning-Assisted Command and Control: Volume 2, Supporting Technical Analysis
This volume serves as the technical analysis to a report concerning the potential for artificial intelligence systems to assist in Air Force command and control (C2).
Jul 15, 2021
Report
Assessing the Value of Intelligence Collected by U.S. Air Force Airborne Intelligence, Surveillance, and Reconnaissance Platforms
This report presents an approach to intelligence, surveillance, and reconnaissance (ISR) assessments that seeks to articulate the costs and benefits of U.S. Air Force airborne ISR in specific operational contexts.
Jun 11, 2021
Report
Technology Innovation and the Future of Air Force Intelligence Analysis: Volume 2, Technical Analysis and Supporting Material
The authors recommend tools, technologies, and processes to address the growing demand for Air Force Distributed Common Ground System support as it relates to intelligence squadrons within the 480th Intelligence, Surveillance and Reconnaissance Wing.
Jan 27, 2021
Report
Technology Innovation and the Future of Air Force Intelligence Analysis: Volume 1, Findings and Recommendations
There is growing demand for the Air Force Distributed Common Ground System to analyze sensor data. The authors assessed how new tools and technologies, including artificial intelligence and machine learning, can help meet these demands.
Jan 27, 2021
Report
Operationally Relevant Artificial Training for Machine Learning: Improving the Performance of Automated Target Recognition Systems
The authors explore whether an object-detection model trained on artificial images could evaluate real images as an automated target recognition system, an important advancement in artificial intelligence and machine learning for the U.S military.
Nov 18, 2020
Report
Command and Control of Joint Air Operations in the Pacific: Methods for Comparing and Contrasting Alternative Concepts
This report recommends methods for comparing and contrasting alternative organizational concepts for command and control of joint air operations in the Pacific in different scenarios.
Jan 18, 2018
Report
Leveraging the Past to Prepare for the Future of Air Force Intelligence Analysis
This report describes steps the U.S. Air Force can take to help ensure that it has the capability needed to provide intelligence analysis support to a broad range of service and combatant commander needs.
Apr 27, 2016
Report
The Effectiveness of Remotely Piloted Aircraft in a Permissive Hunter-Killer Scenario
This report analyzes the operational effectiveness of several new concepts for employing remotely piloted aircraft in a permissive hunter-killer mission.
May 9, 2014
Report
Motion Imagery Processing and Exploitation (MIPE)
This report defines and investigates the potential of motion imagery processing and exploitation (MIPE) systems to enable military intelligence analysts to respond to the current information deluge and exploit a range of motion imagery collections.
Dec 4, 2013
Report
Virtual Collaboration for a Distributed Enterprise
Addresses the challenges to team effectiveness caused by geographic diversity through an assessment of three modes of virtual collaboration.
Apr 22, 2013
Report
Assessment of Beddown Alternatives for the F-35: Executive Summary
RAND assessed the savings potential of reconfiguring the U.S. Air Force's combat-coded F-35s into larger squadrons and adjusting the Primary Aerospace Vehicle Authorized mix across the Active and Reserve Components.
Apr 3, 2013
Report
Assessment of Beddown Alternatives for the F-35
RAND assessed the savings potential of reconfiguring the U.S. Air Force's combat-coded F-35s into larger squadrons and adjusting the Primary Aerospace Vehicle Authorized mix across the Active and Reserve Components.
Apr 3, 2013
Report
Methodologies for Analyzing Remotely Piloted Aircraft in Future Roles and Missions
This briefing describes a suite of tools to help the Air Force think through future roles for remotely piloted aircraft.
May 30, 2012
Report
The Future of Air Force Motion Imagery Exploitation: Lessons from the Commercial World
Commercial television production practices inspire an approach to managing exploitation of the Air Force's rapidly growing motion imagery collections.
Mar 6, 2012
Report
A RAND Analysis Tool for Intelligence, Surveillance, and Reconnaissance: The Collections Operations Model
The Collection Operations Model is a stochastic, agent-based simulation that supports the analysis of command, control, communications, intelligence, surveillance, and reconnaissance (C3ISR) processes.
Nov 25, 2008
Report
Allocation of Forces, Fires, and Effects Using Genetic Algorithms
Using information about friendly and enemy forces and the terrain, a RAND-developed model that incorporates a genetic algorithm (1) determines preferred Blue routes around Red forces and (2) allocates forces to these routes.
Jun 11, 2008
Research Brief
New Approaches to Planning, Executing, and Assessing Intelligence, Surveillance, and Reconnaissance Operations
This research brief summarizes research detailing a methodology for assessing the benefits and costs of U.S. Air Force intelligence, surveillance, and reconnaissance employment strategies.
Apr 13, 2008
Report
Methodology for Improving the Planning, Execution, and Assessment of Intelligence, Surveillance, and Reconnaissance Operations
Presents alternative methods to approach U.S. Air Force intelligence, surveillance, and reconnaissance (ISR) tasking and assessment processes and presents a methodology for assessing the benefits and costs of different ISR employment strategies.
Mar 29, 2008