Accelerating Operational Efficiency

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Data Analytics

Operations Research and System Analysis

Economic Analysis

Homeland Security Risk Sciences

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Arizona State University



CAOE Factsheet


Center Leadership 

Ross Maciejewski
Director, CAOE, A DHS Center of Excellence
Associate Professor, School of Computing, Informatics & Decision Systems Engineering, ASU

Pitu Mirchandani
Chief Scientist, CAOE, A DHS Center of Excellence
Professor, Computing, Informatics and Decision Systems Engineering, ASU 
Senior Sustainability Scientist - Global Institute of Sustainability, ASU 


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Center for Accelerating Operational Efficiency

The Center for Accelerating Operational Efficiency (CAOE), led by Arizona State University, applies advanced analytical tools to optimize efficiency in homeland security operations.

Center Activity

News Release: DHS Selects Arizona State University to Lead Center of Excellence for Accelerating Operational Efficiency

Release Date: 
August 7, 2017

For Immediate Release
DHS S&T Press Office, John Verrico, (202) 254-2385

WASHINGTON – The U.S. Department of Homeland Security (DHS) Science and Technology Directorate (S&T) announced today the selection of Arizona State University to lead a consortium of U.S. academic institutions and other partners for a new Center of Excellence for Accelerating Operational Efficiency (CAOE).  S&T will provide CAOE with a $3.85 million grant for its first operating year in a 10-year grant period. 

“By applying advanced analytical tools, this new Center will support real-time decision making that enables the Department’s operational components and other security practitioners to achieve improvements in operational efficiency,” said Acting Under Secretary for Science and Technology William N. Bryan. “This new Center will work to provide an extra edge to the personnel protecting our ports, border crossings, airports, waterways, transit systems and cyber infrastructure.”

“As lead institution, Arizona State University will spearhead a consortium of academic, industry, government, and laboratory partners throughout the country to develop advanced analytic tools and technologies,” said Dr. Matthew Clark, director of S&T’s Office of University Programs, which manages the DHS Centers of Excellence (COE) system as part of S&T’s Research and Development Partnerships Group. “Based on our rigorous and extensive selection process, we believe Arizona State University will be a strong and enthusiastic partner with the Department’s operational agencies and the COE network.

CAOE’s quantitative analytics research portfolio will focus on four major theme areas: data analytics, operations research and systems analysis, economics, and homeland security risk analysis.  The Center will work closely with the DHS operational components to develop tools and technologies that could be expected to yield significant and measurable efficiency gains.

This Center’s research portfolio will also support DHS leadership for policy analysis.

“To continue to improve homeland security strategic planning, the Department must integrate technical analysis to understand issues arising in the dynamic threat environment and prioritize opportunities to address them,” said Susan Monarez, DHS Deputy Assistant Secretary for Strategy and Analysis in the Office of Policy. “This new Center of Excellence will make a significant contribution to Departmental strategic planning and the cascading impacts on resource management, accountability, and oversight.”

In addition, the Center will provide education and training to extend analytical capabilities and diversity across the homeland security workforce, leveraging Arizona State University’s success in enrolling and graduating increasing numbers of minorities in the science, technology, engineering, and mathematics (STEM) disciplines.

The DHS COEs were established by the Homeland Security Act of 2002 to be a “…coordinated, university-based system to enhance the Nation’s homeland security.” S&T’s COEs are a well-integrated network of researchers and educators focused on specific high-priority DHS challenges.  The COEs work directly with the Department’s operational agencies to solve complex and difficult problems across the homeland security enterprise.

Each COE is led by a U.S. college or university and involves multiple partners for varying lengths of time.  COE partners include other academic institutions, industry, DHS Operational agencies, Department of Energy National Laboratories and other Federally-Funded Research and Development Centers, as well as other federal agencies that have homeland security-relevant missions, state/local/tribal governments, non-profits, and first responder organizations.

This is one of two new DHS S&T Center of Excellence awards. Last week, S&T announced the selection of George Mason University to lead the Center for Criminal Investigations and Network Analysis (CINA). The CAOE and CINA are the first 10-year awards issued for COEs.

For more information about OUP and the COEs, please visit


Development of a Real-Time Decision Support System for Proactive Response, including Recourse Planning, under Uncertain Active Cascading Emergencies 

PI: Pitu Mirchandani  

Co-PI:  David Morton    

Co-PI: Lauren Davis


Detecting, Characterizing, Tracking and Forecasting Rare Events in Multi-Sourced Networks: An Application in Analyzing Isolated Malicious Activities 

PI: Jingrui He    

Co-PI:  Hanghang Tong  


Dynamic Resource Allocation for Predicted Demands at a Network of Screening Facilities  

PI: Ruey Long (Kelvin) Cheu        

Co-PI:  Ronald Askin       


Simulation, Analytics and Modeling for Border Apprehension and Security (SAMBAS)

PI:  Brandon Behlendorf

Co-PI:  Catherine Lawson             


Predictive Analysis of Massive Streaming Graphs

PI:  David Bader


Risk Detection, Operations Efficiency & Economic Analysis      

PI:  Eva Lee        


Interdependencies & Cascading Effects of Disasters on Critical Infrastructure  

PI:  Eva Lee        


Enhancing Aviation Security through the use of Signal Detection Theory   

PI:  Nicolas Scurich                          


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