National Academies Press: OpenBook
« Previous: Appendix B: Public Meeting Agendas
Suggested Citation:"Appendix C: Committee Member Biographical Information." National Academies of Sciences, Engineering, and Medicine. 2023. Test and Evaluation Challenges in Artificial Intelligence-Enabled Systems for the Department of the Air Force. Washington, DC: The National Academies Press. doi: 10.17226/27092.
×

C

Committee Member Biographical Information

May Casterline, Co-Chair, is an image scientist and software developer with a background in satellite and airborne imaging systems. Her research interests include deep learning, hyperspectral and multispectral imaging, innovative applications of machine learning (ML) approaches to remote sensing data, multimodal data fusion, data workflow design, high-performance computing applications, and creative software solutions to challenging geospatial problems. She holds a PhD and a BS in imaging science from the Rochester Institute of Technology, with a focus on remote sensing. In industry, Dr. Casterline has acted as a product owner, technical lead, lead developer, and image scientist on both research initiatives and development projects. She joined the NVIDIA federal solution architecture team in 2017 focusing on deep learning and artificial intelligence (AI) applications.

Thomas A. Longstaff, Co-Chair, is the chief technology officer (CTO) of the Software Engineering Institute (SEI) at Carnegie Mellon University. As CTO, Dr. Longstaff is responsible for formulating a technical strategy and leading the funded research program of the institute based on current and predicted future trends in technology, government, and industry. Before joining the SEI as CTO in 2018, he was a program manager and principal cybersecurity strategist for the Asymmetric Operations Sector of the Johns Hopkins University Applied Physics Laboratory (JHU APL), where he led projects on behalf of the U.S. government, including nuclear command and control, automated incident response, technology transition of cyber research and development (R&D), information assurance, intelligence, and global information networks. Dr. Longstaff also was the chair of

Suggested Citation:"Appendix C: Committee Member Biographical Information." National Academies of Sciences, Engineering, and Medicine. 2023. Test and Evaluation Challenges in Artificial Intelligence-Enabled Systems for the Department of the Air Force. Washington, DC: The National Academies Press. doi: 10.17226/27092.
×

the Computer Science, Cybersecurity, and Information Systems Engineering Programs and the co-chair of Data Science in the Whiting School at JHU. His academic publications span topics such as malware analysis, information survivability, insider threat, intruder modeling, and intrusion detection. He maintains an active role in the information assurance community and regularly advises organizations on the future of network threat and information assurance. Dr. Longstaff is an editor for Computers and Security. He has previously served as the associate editor for IEEE Security and Privacy and general chair for the New Security Paradigms Workshop and Homeland Security Technology Conference and numerous other program and advisory committees. Prior to joining the staff at JHU APL, Dr. Longstaff was the deputy director for technology for the CERT Division at the SEI. In his 15-year tenure at the SEI CERT Division, he helped create many of the projects and centers that made the program an internationally recognized network security organization. His work included assisting the Department of Homeland Security and other agencies to use response and vulnerability data to define and direct a research and operations program in analysis and prediction of network security and cyber terrorism events. Dr. Longstaff received a bachelor’s degree in physics and mathematics from Boston University and a master’s degree in applied science and a PhD in computer science from the University of California, Davis.

Craig R. Baker is the president of Baker Development Group, LLC, a consulting, leadership, and teaching company. He is a trusted executive leader widely known as a strategic planner and executor of large, important, highly visible projects and products to mitigate risks. Mr. Baker retired from the U.S. Air Force as a Brigadier General in July 2021. He graduated from the U.S. Military Academy at West Point in 1992, was a command combat test pilot, and instructed at the U.S. Air Force Fighter Weapons School (“Top Gun”). Mr. Baker commanded at both the squadron and wing levels. Additionally, he was the technical director GM/test program manager of the 59th Test and Evaluation Squadron achieving $500 million in savings cultivated and lives saved by creating and establishing an innovative process and software program that required 60 percent fewer assets and personnel; and met 60 percent of worldwide objectives in developing and integrating a congressionally directed fleet capability while delivering a historical first milestone highlighted to the enterprise president weekly. Mr. Baker led multi-service weapons assessment teams into Iraq and Afghanistan after OIF and OEF, which resulted in revolutionary software program and new weapon developments. He earned two MS degrees in strategic intelligence and strategic studies.

Robert A. Bond, prior to his appointment as principal staff, served for 5 years as the CTO at the Massachusetts Institute of Technology Lincoln Laboratory (MIT LL). He was formerly the associate head of the Intelligence, Surveillance,

Suggested Citation:"Appendix C: Committee Member Biographical Information." National Academies of Sciences, Engineering, and Medicine. 2023. Test and Evaluation Challenges in Artificial Intelligence-Enabled Systems for the Department of the Air Force. Washington, DC: The National Academies Press. doi: 10.17226/27092.
×

Reconnaissance and Tactical Systems Division. In his 42-year career, Mr. Bond has led research initiatives in very-large-scale integrated (VLSI) circuits, software technology, parallel processors, adaptive and nonlinear signal processing, AI, C2ISR systems, and big-data analytics. He joined the MIT LL in 1987 and led the software and integration activities for the Radar Surveillance Technology Experimental Radar. In the 1990s, Mr. Bond conducted seminal studies on the use of massively parallel processors (MPP) for real-time signal processing. He then pioneered the development of a custom VLSI processor and a 1,000-node MPP for radar space-time adaptive processing. Mr. Bond led the development of a middleware technology for portable and scalable parallel signal processors that evolved into the Parallel Vector Tile Optimized Library (PVTOL), which won an R&D 100 award. In 2003, he received the MIT LL’s prestigious Technical Excellence Award, for his “technical vision and leadership in the application of high-performance embedded processing architectures to real-time digital signal processing systems.” Since 2015, Mr. Bond has led the MIT LL’s strategic initiatives in AI and autonomous systems. As the CTO, he oversaw and funded the applied research portfolios in these areas. In 2018, Mr. Bond founded the Recent Advances in AI for National Security workshop. He is currently the MIT LL’s program manager for the Air Force-MIT AI Accelerator program. Mr. Bond has a BS (honors) in physics, is a member of the Association for the Advancement of Artificial Intelligence (AAAI), and a senior member of the Institute of Electrical and Electronics Engineers (IEEE).

Rama Chellappa is a Bloomberg Distinguished Professor in the Departments of Electrical and Computer Engineering (Whiting School of Engineering) and Biomedical Engineering (School of Medicine) at JHU. At JHU, he is also affiliated with the Center for Imaging Sciences, the Center for Language and Speech Processing, the Institute for Assured Autonomy, and the Mathematical Institute for Data Science. Dr. Chellappa holds a non-tenure position as a College Park Professor in the Electrical and Computer Engineering (ECE) department at the University of Maryland (UMD). From 1981 to 1991, he was an assistant and associate professor in the Department of EE-Systems at University of Southern California. He received an MSEE (1978) and a PhD (1981) in electrical engineering from Purdue University. His current research interests span many areas in computer vision, pattern recognition, AI, and ML. Dr. Chellappa is an elected member of the National Academy of Engineering (NAE). He received the 2023 Distinguished Career Award from the Washington Academy of Sciences, the 2020 Jack S. Kilby Medal for Signal Processing from the IEEE, and the K.S. Fu Prize from the International Association of Pattern Recognition (IAPR). Additionally, Dr. Chellappa is a recipient of the Society, Technical Achievement and Meritorious Service Awards from the IEEE Signal Processing Society, the Technical Achievement and Meritorious Service

Suggested Citation:"Appendix C: Committee Member Biographical Information." National Academies of Sciences, Engineering, and Medicine. 2023. Test and Evaluation Challenges in Artificial Intelligence-Enabled Systems for the Department of the Air Force. Washington, DC: The National Academies Press. doi: 10.17226/27092.
×

Awards from the IEEE Computer Society, and the inaugural Leadership Award from the IEEE Biometrics Council. At UMD, he received numerous college- and university-level recognitions for research, teaching, innovation, and mentoring of undergraduate students. He was recognized as an Outstanding ECE by Purdue University and as a Distinguished Alumni by the Indian Institute of Science. Dr. Chellappa is a Golden Core Member of the IEEE Computer Society and has served as a Distinguished Lecturer of the IEEE Signal Processing Society and as the president of IEEE Biometrics Council. He is a fellow of AAAI, the American Association for the Advancement of Science (AAAS), the Association for Computing Machinery (ACM), the American Institute for Medical and Biological Engineering, IAPR, IEEE, the Optical Society of America, and the National Academy of Inventors and holds nine patents.

Melvin Greer is an Intel Fellow and the chief data scientist at the Americas, Intel Corporation. He is responsible for building Intel’s data science platform through graph analytics, ML, and cognitive computing to accelerate transformation of data into a strategic asset for public sector and commercial enterprises. His systems and software engineering experience has resulted in patented inventions in cloud computing, synthetic biology, and Internet of Things bio-sensors for edge analytics. Dr. Greer functions as a principal investigator in advanced research studies, including nanotechnology, additive manufacturing, and gamification. He significantly advances the body of knowledge in basic research and critical, highly advanced engineering, and scientific disciplines. Dr. Greer is a member of the AAAS and serves on the board of directors for the National Academies of Sciences, Engineering, and Medicine. He has been appointed to senior advisor and fellow at the Federal Bureau of Investigation (FBI) IT and Data Division and is charged with acceleration of the FBI mission by supporting appropriate data collection, data analytics, discovery, and visualization via advanced data science and AI techniques. Dr. Greer is one of the 2018 LinkedIn Top 10 Voices in data science and analytics. He also received the Washington Exec Inaugural Pinnacle Award as the 2018 Artificial Intelligence Executive of the Year, and received the 2017 Black Data Processing Associates Lifetime Achievement Award and the 2012 Black Engineer of the Year Awards Technologist of the Year Award, which recognized his outstanding technical contributions that have had a material impact and high value to society as a whole. Dr. Greer has been appointed a fellow of the National Cybersecurity Institute where he assists government, industry, military, and academic sectors on meeting the challenges in cyber security policy, technology and education. He is professor for the MS of science in data science program at Southern Methodist University and adjunct faculty, advanced academic program at JHU, where he teaches the MS course on practical applications of AI. In addition to his professional and investment roles, Dr. Greer is the founder and managing director of the

Suggested Citation:"Appendix C: Committee Member Biographical Information." National Academies of Sciences, Engineering, and Medicine. 2023. Test and Evaluation Challenges in Artificial Intelligence-Enabled Systems for the Department of the Air Force. Washington, DC: The National Academies Press. doi: 10.17226/27092.
×

Greer Institute for Leadership and Innovation, focused on research and deployment of a 21st-century leadership model. He is a frequent speaker at conferences and universities and is an accomplished author; his fifth book, Practical Cloud Security A Cross Industry View, is his most recently published book. Dr. Greer is a board of director member at the National GEM Consortium where he oversees and aligns its strategic direction, educational policy, finances, and operations with the mission of the fellowship program. As a popular educator and board member at a number of Historical Black Colleges and Universities, Dr. Greer is leading science, technology, mathematics, and engineering research initiatives, directly trying to shape a more diverse generation of up-and-coming technical talent.

Tamara G. Kolda is an independent mathematical consultant under the auspices of her company MathSci.ai based in California. She is also a distinguished visiting professor in the Department of Industrial Engineering and Management Science at Northwestern University. From 1999 to 2021, Dr. Kolda was a researcher at Sandia National Laboratories in Livermore, California. She specializes in mathematical algorithms and computation methods for tensor decompositions, tensor eigenvalues, graph algorithms, randomized algorithms, ML, network science, numerical optimization, and distributed and parallel computing. Dr. Kolda is a member of the NAE, a fellow of the Society for Industrial and Applied Mathematics (SIAM), and a fellow of the ACM. She holds a PhD in applied mathematics from UMD.

Robin R. Murphy is the Raytheon Professor of Computer Science and Engineering at Texas A&M University and a director of the Center for Robot-Assisted Search and Rescue. Her research focuses on AI, robotics, and human–robot interaction for emergency management. Dr. Murphy has deployed ground, aerial, and marine robots to over 30 disasters in five countries including the 9/11 World Trade Center, Fukushima, Hurricane Harvey, and the Surfside collapse. She is an AAAS, ACM, and IEEE fellow, a TED speaker, and her contributions to robotics have been recognized with the ACM Eugene L. Lawler Award for Humanitarian Contributions and a United States Air Force Exemplary Civilian Service Award medal. She holds a PhD (1992) and an MS (1989) in computer science and a BME (1980) in mechanical engineering from the Georgia Institute of Technology.

David S. Rosenblum is the Planning Research Corporation Professor and the chair of the Department of Computer Science at George Mason University. Since receiving his PhD from Stanford University, Dr. Rosenblum has held positions as a member of the technical staff at AT&T Bell Laboratories (Murray Hill); associate professor and associate chair at the University of California, Irvine; CTO and principal architect at PreCache, Inc.; professor of software systems at University College London; and Provost’s Chair Professor, dean of the School of Computing,

Suggested Citation:"Appendix C: Committee Member Biographical Information." National Academies of Sciences, Engineering, and Medicine. 2023. Test and Evaluation Challenges in Artificial Intelligence-Enabled Systems for the Department of the Air Force. Washington, DC: The National Academies Press. doi: 10.17226/27092.
×

and founding director of the NUS-Singtel Cyber Security R&D Lab at National University of Singapore. He has made significant contributions to a broad array of research problem areas in computer science, including software engineering, distributed systems, ubiquitous computing, and ML. Among his most highly cited research are works on Internet-scale publish/subscribe computing; assertion processing techniques and regression testing methods for software engineering; and ML and deep learning techniques for recommendation systems, activity recognition, and social media analytics. Dr. Rosenblum is a fellow of the ACM and IEEE and has received two 10-year, test-of-time awards, including the International Conference on Software Engineering (ICSE) 2002 Most Influential Paper Award for his ICSE 1992 paper on assertion processing, and the inaugural 2008 ACM SIGSOFT Impact Paper Award for his Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering 1997 paper on Internet-scale event observation and notification (co-authored with Alexander L. Wolf). He also received the 2018 ACM SIGSOFT Distinguished Service Award.

John (Jack) N.T. Shanahan retired from the United States Air Force in 2020 after a 36-year military career. In his final assignment, he served as the inaugural director of the Department of Defense (DoD) Joint Artificial Center. Mr. Shanahan served in a variety of operational and staff positions in various fields, including flying, intelligence, policy, and command and control. He established and led DoD’s Pathfinder AI fielding program (Project Maven) and is an adjunct senior fellow with the Technology and National Security Program at the Center for a New American Security. Mr. Shanahan is a member of the IEEE Standards Association Autonomous Weapons Systems Assurance and Safety Subcommittee.

Rebecca Willett is a professor of statistics and computer science at The University of Chicago. Her research is focused on ML, signal processing, and large-scale data science. Dr. Willett received the National Science Foundation (NSF) CAREER Award in 2007, was a member of the Defense Advanced Research Projects Agency Computer Science Study Group, received an Air Force Office of Scientific Research Young Investigator Program award in 2010, was named a fellow of the SIAM in 2021, and was named a fellow of the IEEE in 2022. She is a co-principal investigator and member of the executive committee for the Institute for the Foundations of Data Science, helps direct the Air Force Research Laboratory University Center of Excellence on Machine Learning, and currently leads The University of Chicago’s AI+Science Initiative. In addition, Dr. Willett serves on advisory committees for the NSF’s Institute for Mathematical and Statistical Innovation, the AI for Science Committee for the Department of Energy’s Advanced Scientific Computing Research program, the Sandia National Laboratories Computing and Information Sciences Program, and the University of Tokyo Institute for AI and Beyond.

Suggested Citation:"Appendix C: Committee Member Biographical Information." National Academies of Sciences, Engineering, and Medicine. 2023. Test and Evaluation Challenges in Artificial Intelligence-Enabled Systems for the Department of the Air Force. Washington, DC: The National Academies Press. doi: 10.17226/27092.
×

She completed her PhD in electrical and computer engineering at Rice University (2005) and was an assistant and then tenured associate professor of electrical and computer engineering at Duke University (2005–2013). Additionally, Dr. Willett was an associate professor of electrical and computer engineering, the Harvey D. Spangler Faculty Scholar, and a fellow of the Wisconsin Institutes for Discovery at the University of Wisconsin–Madison (2013–2018).

Suggested Citation:"Appendix C: Committee Member Biographical Information." National Academies of Sciences, Engineering, and Medicine. 2023. Test and Evaluation Challenges in Artificial Intelligence-Enabled Systems for the Department of the Air Force. Washington, DC: The National Academies Press. doi: 10.17226/27092.
×
Page 149
Suggested Citation:"Appendix C: Committee Member Biographical Information." National Academies of Sciences, Engineering, and Medicine. 2023. Test and Evaluation Challenges in Artificial Intelligence-Enabled Systems for the Department of the Air Force. Washington, DC: The National Academies Press. doi: 10.17226/27092.
×
Page 150
Suggested Citation:"Appendix C: Committee Member Biographical Information." National Academies of Sciences, Engineering, and Medicine. 2023. Test and Evaluation Challenges in Artificial Intelligence-Enabled Systems for the Department of the Air Force. Washington, DC: The National Academies Press. doi: 10.17226/27092.
×
Page 151
Suggested Citation:"Appendix C: Committee Member Biographical Information." National Academies of Sciences, Engineering, and Medicine. 2023. Test and Evaluation Challenges in Artificial Intelligence-Enabled Systems for the Department of the Air Force. Washington, DC: The National Academies Press. doi: 10.17226/27092.
×
Page 152
Suggested Citation:"Appendix C: Committee Member Biographical Information." National Academies of Sciences, Engineering, and Medicine. 2023. Test and Evaluation Challenges in Artificial Intelligence-Enabled Systems for the Department of the Air Force. Washington, DC: The National Academies Press. doi: 10.17226/27092.
×
Page 153
Suggested Citation:"Appendix C: Committee Member Biographical Information." National Academies of Sciences, Engineering, and Medicine. 2023. Test and Evaluation Challenges in Artificial Intelligence-Enabled Systems for the Department of the Air Force. Washington, DC: The National Academies Press. doi: 10.17226/27092.
×
Page 154
Suggested Citation:"Appendix C: Committee Member Biographical Information." National Academies of Sciences, Engineering, and Medicine. 2023. Test and Evaluation Challenges in Artificial Intelligence-Enabled Systems for the Department of the Air Force. Washington, DC: The National Academies Press. doi: 10.17226/27092.
×
Page 155
Next: Appendix D: Acronyms and Abbreviations »
Test and Evaluation Challenges in Artificial Intelligence-Enabled Systems for the Department of the Air Force Get This Book
×
 Test and Evaluation Challenges in Artificial Intelligence-Enabled Systems for the Department of the Air Force
Buy Paperback | $42.00 Buy Ebook | $33.99
MyNAP members save 10% online.
Login or Register to save!
Download Free PDF

The Department of the Air Force (DAF) is in the early stages of incorporating modern artificial intelligence (AI) technologies into its systems and operations. The integration of AI-enabled capabilities across the DAF will accelerate over the next few years.

At the request of DAF Air and Space Forces, this report examines the Air Force Test Center technical capabilities and capacity to conduct rigorous and objective tests, evaluations, and assessments of AI-enabled systems under operational conditions and against realistic threats. This report explores both the opportunities and challenges inherent in integrating AI at speed and at scale across the DAF.

READ FREE ONLINE

  1. ×

    Welcome to OpenBook!

    You're looking at OpenBook, NAP.edu's online reading room since 1999. Based on feedback from you, our users, we've made some improvements that make it easier than ever to read thousands of publications on our website.

    Do you want to take a quick tour of the OpenBook's features?

    No Thanks Take a Tour »
  2. ×

    Show this book's table of contents, where you can jump to any chapter by name.

    « Back Next »
  3. ×

    ...or use these buttons to go back to the previous chapter or skip to the next one.

    « Back Next »
  4. ×

    Jump up to the previous page or down to the next one. Also, you can type in a page number and press Enter to go directly to that page in the book.

    « Back Next »
  5. ×

    Switch between the Original Pages, where you can read the report as it appeared in print, and Text Pages for the web version, where you can highlight and search the text.

    « Back Next »
  6. ×

    To search the entire text of this book, type in your search term here and press Enter.

    « Back Next »
  7. ×

    Share a link to this book page on your preferred social network or via email.

    « Back Next »
  8. ×

    View our suggested citation for this chapter.

    « Back Next »
  9. ×

    Ready to take your reading offline? Click here to buy this book in print or download it as a free PDF, if available.

    « Back Next »
Stay Connected!