Dr. Mark Karpenko is a Research Professor of Mechanical and Aerospace Engineering (MAE) at the Naval Postgraduate School. He has a joint appointment in the Space Systems Academic Group. He is the Associate Director of Control and Optimization and program manager for NPS’ Applied Trajectory Optimization Certificate.
At NPS, Karpenko has directed student thesis work on a variety of diverse research projects involving dynamic optimization applications including the development of autonomous trajectory planning for robotic arms and mobile ground robots as well as optimal mission design for unmanned aerial vehicles. Karpenko has worked with Naval Air Weapons Station China Lake on trajectory optimization for advanced missile guidance and has participated in the design of flight profiles for high-speed weapons with RTX.
Karpenko has extensive experience in trajectory optimization and efficient operation of space systems including attitude guidance for spacecraft rotational control, orbit transfers orbital maneuvers and satellite formations. He was a lead flight engineer on the TRACE Optimal Maneuver Experiment conducted at NASA Goddard Space Flight Center. He also worked with Goddard Space Flight Center to improve the efficiency and autonomy of NASA’s Lunar Reconnaissance Orbiter. He was a recipient of the NASA NESC Engineering Excellence Award for his contributions to this effort.
Karpenko has published over 100 technical papers and his research has appeared in various journals. He is a co-inventor on 9 US government patents and has additional patents pending on optimal and robust control applications. His current teaching and research focus areas include dynamic systems. control and optimization with a focus on aerospace and space systems. Karpenko is an Associate Fellow of the AIAA.
Both MAE and SSAG provide opportunities for students to get hand-on experience with practical systems in robotics, aerospace and space and via SSAG, allow faculty from across various disciplines to work together with students on some very challenging problems. Hands-on opportunities obviously reinforce what is taught in the classroom, but our faculty’s involvement with real systems in the field ‘ups the ante’ because things absolutely have to work – we can’t just reset the experiment! For example, one of our recent students (LT Jeremy Lopez-Vazquez) worked on using machine learning to automate aspects of propulsion control for a long-endurance aircraft. A key challenge was getting it to successfully work within the constraints of the available flight hardware. This is challenging and must be done carefully because of resource constraints of the flight system. Similarly, LT Zachary Michael and LTJG Catherine Barta worked on designing energy-efficient flight paths, also for long-endurance aircraft. Because their work focused on developing solutions for an actual military exercise, there was little room for error in the energy calculations. Projects like these emphasize that when you use ideas from the classroom to do things for real, you really have to make sure to get things right. The same goes for operating spacecraft and other military systems that our students can ‘touch’ through our various research projects in MAE and SSAG.
My research focus is primarily on dynamical systems and optimization. The later topic is a key underlying technology of artificial intelligence and machine learning. One of our recent efforts, with Distinguished Professor Mike Ross (MAE) led to a recently licensed patent (US 2023/0274128 A1) on accelerated optimization that can be used to speed up machine learning processes. I spend much of my time doing something called trajectory optimization, which seeks to find the most efficient way to operate a system in order to perform a specified task. For example, how to quickly re-point a satellite to obtain additional pictures of the Earth. This idea was recently transitioned to NASA who use it to maneuver the Lunar Reconnaissance Orbiter to collect science on the Moon.
Dr. Vladimir Dobrokhodov (MAE) and I also use trajectory optimization to find energy-efficient paths for long endurance flight. You can think of this as finding a way to steer the aircraft so as to leverage tailwinds and stay out of head winds as much as possible. Sometimes, this means changing altitudes to achieve more favorable winds while also staying out of weather and icing conditions. Part of being successful at this also requires us to find the right recipe for flying along these paths. What I mean by that is, it is not enough to know what direction you need to fly but also how to properly set the controls on the propulsion system to achieve maximum efficiency. Driving 100mph in first gear is not a good way to save gas! I have been working on this aspect with Dr. Kevin Jones (MAE). Long endurance unrefueled flight of nearly 8 to 10 days is possible by marrying these ideas with the right airframe as we have recently demonstrated at the Joint Military exercise Arctic Edge 2025. There are numerous military applications for that can leverage these advancements.
Long endurance unrefueled flight of nearly 8 to 10 days is now possible by leveraging some of the research that I have been involved in at NPS. So, why not try to fly around the world! Some of the key challenges in planning such a mission is handling weather data. After all, the weather will make or break a trip like this. Weather predictions are ‘big data’ and we plan to leverage a suite of NVIDIA tools and hardware to enable a trip around the world. For example, Omniverse (a real-time 3D graphics collaboration platform created by NVIDIA) can help use get a picture of weather global patterns that can be used to path plan using our algorithms. Omniverse will be a perfect tool for visualizing our mission as it evolves over time. Jessica Herman (MAE) will be helping us understand the right way to use the tool to provide the right information at the right time to the pilots tasked with flying the aircraft. We also need to be able to handle real-time weather information and incorporate it into our planning process. For example, what if the prediction did not call for rain, but local sensors tell a different story. We need to be able to adjust our mission plan ‘on-the-fly’ in order to avoid inclement weather as efficiently as possible. This requires an ability to process large amounts of data efficiently on board the aircraft itself. We plan to explore NVIDIA’s Jetson hardware to instantiate an updateable weather digital twin on the aircraft that we can update using real time measurements based on some work that was done by MAE student ENS Alan Gardner. This hardware will also be used to integrate an aircraft digital twin model to ensure we operate the vehicle as efficiently as possible.
A flight around the world requires us to incorporate many of the features of our existing ground planning infrastructure that we have been developing for our DoD sponsors on the aircraft itself. For DoD missions on board computations may only be needed for certain tasks. However, it is crucial to enable on board calculations for an unrefueled around the world trip because every decision has the potential to make or break the trip. The funding we received from the 2025 NPS Digital Trident AI Challenge will allow us to make quick progress in migrating our process to the aircraft system. In doing so, we will be ahead of the game as far as getting this technology ready for transition to DoD.
At NPS we have a cadre of very capable people turning every stone to identify ways that NPS can work with various DoD and industry partners to solve problems for the Navy and DoD. In fact, this is how the Digital Trident AI Challenge came to be. NPS also supports CRADAs with many companies from the industry. Under one such CRADA, I am working with Dr. Wenschel Lan (SSAG) to develop and test algorithms that support alternative position, navigation and timing. As part of the Digital Trident AI Challenge, we plan to see how this capability can be used to augment our navigation picture to safeguard against loss of GPS signals. Without access to the cutting-edge work being done by our industry partners, many of the ideas that come from the minds of NPS faculty might never make it off the drawing board.
