Jose Ignacio de Alvear Cardenas

Affiliation– NASA Ames Research Center

Division– Human Systems Integration Division (TH)

Phone– 650-604-3236

Email– joseignacio.dealvearcardenas@nasa.gov

Mail Stop– 262-4

Professional Bio

José Ignacio de Alvear Cárdenas is an Aerospace Research Engineer at NASA Ames Research Center, where he supports the integration of new entrants in the low-altitude national airspace, including drone package delivery and public safety operations. From the beginning in 2023, he has worked in collaboration with the FAA towards enabling safe and efficient Beyond Visual Line of Sight (BVLOS) operations through his research on pre-departure and in-flight deconfliction, as well as conformance monitoring services. 

At NASA, he has developed tools that significantly expanded the project’s simulation capabilities, enabling more comprehensive modeling of complex airspace scenarios. He has also contributed to the integration of a probabilistic approach to the safety analysis of UTM services, aligning more closely with the inherent uncertainties of vehicle positioning and supporting more robust risk assessments. In parallel, his work has explored the potential of artificial intelligence techniques—particularly the use of reinforcement learning for services such as tactical deconfliction—demonstrating how these methods could enhance automation and scalability within the UTM ecosystem.

He received his B.Sc. and M.Sc. degrees in Aerospace Engineering from Delft University of Technology, where he specialized in Control and Simulation. For his Bachelor thesis, José Ignacio worked in the development of Silentium, a Silent Delivery Drone, and for his Master thesis he developed a Vision-based UAV Fault Detection and Diagnosis framework. In 2017, as part of the Netherlands Aerospace Center (NLR), he participated in the SCALAIR project within the Clean Sky 2 European research program. In 2019, he worked at the German Aerospace Center (DLR) Institute of System Dynamics and Control focusing on System Identification and Intelligent Control.

Education

Delft University of Technology, The Netherlands – M.Sc. Aerospace Engineering, specialization in Control & Simulation, 2022

Delft University of Technology, The Netherlands – B.Sc. Aerospace Engineering, minor in Software Design and Application with Data Science, 2018

Professional Experience

San José State University Research Foundation @ NASA Ames Research Center (ARC), United States – Aerospace Research Engineer, 2023-Current

INCYDE Foundation, Spain – UAV Educational Consultant, 2020-2023

German Aerospace Center (DLR), Germany – Flight Dynamics and Control Intern, 2019-2020

Netherlands Aerospace Laboratory (NLR), The Netherlands – Engineering Intern, 2017

CT Engineering Group, Spain – Engineering Intern, 2016

Research Interests

My research spans the intersection of autonomous aerial systems, intelligent control, and machine perception, with a strong emphasis on safety, adaptability, and real-world deployment. I am broadly interested in the following subjects: Unmanned Aircraft System Traffic Management (UTM), autonomous flight of micro air vehicles, system identification, nonlinear and adaptive control, intelligent fault detection and diagnosis, deep reinforcement learning, and computer vision for aerial robotics. Much of my work has explored how these areas can be integrated to enable safe, autonomous operations in the future complex and dynamic airspace.

Recent research has focused on the following topics, with the recurring theme of bridging the simulation-to-reality gap:

• Safety and Efficiency Study of Strategic Deconfliction and Conformance Monitoring for Situational Awareness Services in UTM
• Integrated Vision and Sensor Fusion for Onboard UAV Health Monitoring and Fault Diagnosis (Code)
• Reinforcement Learning for Tactical Deconfliction and Autonomous Control
• Nonlinear Control for Overweight Transport Aircraft Emergency Landing

While these areas currently shape my research, I remain open to interdisciplinary collaborations and emerging challenges in autonomous systems, robotics, and learning-based control.

Conference Proceedings

de Alvear Cárdenas, J.I., Pradeep, P., Xue, M., Lee, S., Kuo, V.H. (2025). Confidence-Based Buffer for Strategic Deconfliction with Probabilistic Operational Intent, AIAA SciTech 2025 Forum, Orlando, FL, USA (Paper)

Xue, M., Kuo, V.H., de Alvear Cárdenas, J.I., Pradeep, P. (2025). Safety Benefit Analysis of Conformance Monitoring for Situational Awareness in UTM, AIAA SciTech 2025 Forum, Orlando, FL, USA (Paper)

Xue, M., Kuo, V.H., de Alvear Cárdenas, J.I., Pradeep, P. (2024). A Method of Compliance for Achieving Target Collision Risk in UTM Operations, AIAA Aviation Forum and Ascend, Las Vegas, NV, USA (Paper)

de Alvear Cárdenas, J.I., de Visser, C.C. (2024). Blade Element Theory Model for UAV Blade Damage Simulation, AIAA SciTech 2024 Forum, Orlando, FL, USA (Paper) (Project) (Code) (Validation)

de Alvear Cárdenas, J.I., de Visser, C.C. (2024). Unreal Success: Vision-Based UAV Fault Detection and Diagnosis Framework, AIAA SciTech 2024 Forum, Orlando, FL, USA (Paper) (Project) (Code) (Data)

de Alvear Cárdenas, J.I., Sun, B., van Kampen, E.J. (2021). Intelligent Adaptive Control Using LADP and IADP Applied to F-16 Aircraft with Imperfect Measurements, AIAA SciTech 2021 Forum, Virtual Event (Paper)

de Alvear Cárdenas, J.I., Looye, G. (2021). Automatic Landing Design for Overweight Transport Aircraft with Explicit Flare Controller and Incremental Backstepping, AIAA SciTech 2021 Forum, Virtual Event (Paper)

de Alvear Cárdenas, J.I., Eggers, Y., van Hoorn, F., Jou Ferrer, L., Oosterhof, E., Stikker, R., Terenzi, L., Veder, R., Velthausz, L.A.H., van de Waals, M. (2018). Silentium: Silent Delivery Drone, Unmanned Cargo Aircraft Conference, Amsterdam, The Netherlands (Report)

NASA Technical Memorandum

Pradeep, P., Lee, S., Silva, J.P., de Alvear Cárdenas, J.I., Kuo, V.H., Xue, M., Yarramreddy, G.S. (2025). Simulation Studies of 4D Volume-based Pre-departure Strategic Deconfliction under Wind Uncertainty for Package Delivery sUAS, NASA/TM-20250005293

Yarramreddy, G.S., de Alvear Cárdenas, J.I., Pradeep, P., Xue, M., Lee, S., Kuo, V.H. (2025). Simulation Framework for Tactical Separation Assurance Service using Deep Reinforcement Learning, NASA-TM-20250002761

Kuo, V.H., Xue, M., Pradeep, P., de Alvear Cárdenas, J.I., Lee, S. (2024). Safety Assessment of Conformance Monitoring for Situational Awareness in UTM Operations, NASA/TM-20240015613

Awards/Prizes

Holland in the Valley Fellow, Internships in the Valley, 2023

Dutch2USA Internship Grant, The Netherland-American Foundation, 2023

Honorary Mention in the Advanced Air Mobility Concepts – Innovation Challenge, IEEE Vehicular Technology Society, 2022

Newcraft 24 Hour Data Challenge Winner, Newcraft, 2019

ASML Technology Scholarship, ASML, 2018

Miscellaneous

European Robotics Forum Hackathon Technical Organizer, 2022

CERN IdeaSquare & Nikhef e-Summer School Ideation Challenge Innovator, 2020

180 Degrees Consulting Delft-Rotterdam Co-founder and Consulting Director, 2018

ESA Ladybird Guide to Spacecraft Operations Alumni, 2018

IDEA League Challenge Programme Alumni, 2017