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David Alderson, PhD

Professor, Operations Research

Dr. David Alderson is a Professor in the Operations Research Department and serves as Founding Director for the Center for Infrastructure Defense at the Naval Postgraduate School. He is also a member of the NPS Cyber Academic Group, which has academic oversight of interdisciplinary cyber curricula on campus.


Alderson's research focuses on the function and operation of critical infrastructures, with particular emphasis on how to invest limited resources to ensure efficient and resilient performance in the face of accidents, failures, natural disasters, or deliberate attacks. His research explores tradeoffs between efficiency, complexity, and fragility in a wide variety of public and private cyber-physical systems. Alderson has been the Principal Investigator of sponsored research projects for the Navy, Army, Air Force, Marine Corps and Coast Guard.


Alderson received his doctorate from Stanford University and his undergraduate degree from Princeton University. He has held research positions at the California Institute of Technology (Caltech), the University of California Los Angeles, the Xerox Palo Alto Research Center (PARC), and the Santa Fe Institute. He has extensive industry experience and has worked for several venture-back startup companies. His early career was spent developing technology at Goldman Sachs & Co. in New York City. Alderson is the 2021 recipient of the Richard W. Hamming Teaching Award.

From DOD to NATO, to state and local governments, you and your many thesis students collect data and perform field experiments around the world, tackling today's complex public and battlefield-centric problems. In what ways do the OR students at NPS contribute to our Nation's ability to maintain its competitive advantage and to solutions that can be applied around the globe?

Operations Research is the science of going "from data to decision." We educate analysts so they can apply the latest tools in data analysis, computation, optimization, machine learning, modeling and simulation, so they are fully capable of conducting independent analytical studies of military problems and advising senior leaders. Our students and faculty use the latest mathematical modeling ideas and computing technology to penetrate deeply into important, real-world problems ranging from capital planning, scheduling and logistics to emergency response and critical infrastructure.

There are many fine schools that teach the theory and tools of operations research, but in many cases their applications are limited to "textbook problems." Solving real problems is more challenging because the real world is messy, with data that is incomplete, incorrect and confusing. Our students use their operational experience as military officers to identify, formulate and solve problems that defy textbook solutions. The growing complexity of the world requires problem solvers who combine quantitative methods and operational art, not just in theory but in practice. 

"Our students practice in the real world — by working with real sponsors on real problems in their master's theses and capstone projects — to deliver immediate solutions and gain valuable experience in operational thinking, planning, and execution."


Can you tell us about the Center for Infrastructure Defense and what makes NPS different in its capabilities and methodology for vulnerability analysis and infrastructure resilience?

NPS has been studying critical infrastructure since (at least) the 1980s, long before my time. Much of the early foundational work focused on targeting critical infrastructure systems to achieve a specific effect (e.g., interrupting electric power). It turns out the same mathematics used for attacking critical infrastructure is important for understanding how to defend it. NPS has been a leader in the development and application of these Attacker-Defender models for critical infrastructures and other systems.

However, protecting critical infrastructure (e.g., via hardening) is not enough. We continue to see the regular occurrence of surprising failures in civilian and military systems at organizational, regional, national scales—breakdowns that trigger or threaten widespread service outages with large financial, operational, and/or human costs. We see these arise from extreme weather events (and longer-term climate volatility), unintended fragilities that accompany the deployment of new technologies, and/or new paths for adversarial conflict. The real questions have become: How do we better anticipate changing threats and recognize emerging new vulnerabilities in an increasingly interconnected world? How do we learn to offset changing risks before failures occur in these evolving systems? How do we build the capability to be poised to adapt to keep pace and stay ahead of the trajectory of growing complexity? This is where we hope the NPS Center for Infrastructure Defense will continue to make its mark in the years ahead.


How is NPS and the CID addressing the increasing integration of cyber-physical systems into traditional critical infrastructure? How does it affect how we prepare for future warfare?

Many modern critical infrastructure systems, such as the electric grid, are so complicated that it is near impossible to operate them without the support of computer-based decision-support tools, which have become their own type of digital infrastructure. These systems rely on automation, and there is increasing use of advanced artificial intelligence and machine learning (AI/ML) tools to provide faster and often better decisions. In the media, we have seen tremendous progress on the development of computers who beat humans at Chess, Go, and just about everything else. Understanding how human-machine teams can perform even better, in infrastructure management and warfare, is an active area of research.

NPS OR educates students in the latest AI/ML tools and techniques, for example via our Certificate in Operational Data Science and Statistical Machine Learning. These tools can find patterns in data that would otherwise be invisible to humans, and these patterns can be used to inform decision-making. However, there are limits to what these technologies can and cannot do. For example, one of the ongoing lessons is the difficulty that computers (including modern AI-based systems) have dealing with surprise. To date, humans are the only ones able to reframe problems when previous assumptions or models are found to be incorrect. Despite the push for AI-enabled decision support, humans (our students!) remain imperative as critical thinkers and decision-makers. This is true when these systems work as planned, and it becomes even more important when they don't work as planned (as always happens eventually). When it comes to deploying such systems, the need for human expertise actually goes up, not down. 

All of this makes our research and work with students across disciplines more important than ever.

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