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Research and Development (R&D)

Research and Development (R&D)Research and Development (R&D)Research and Development (R&D)

Aerospace R&D, Control Systems, Real-Time Simulation, Artificial Intelligence, Test & Instrumentation, Automation.

Contact

Research and Development (R&D)

Research and Development (R&D)Research and Development (R&D)Research and Development (R&D)

Aerospace R&D, Control Systems, Real-Time Simulation, Artificial Intelligence, Test & Instrumentation, Automation.

Contact

Welcome!

Ulices Santa Cruz Leal, Ph.D.

Solutions Engineer at Applied Dynamics International (ADI) and full-time onsite consultant for JetZero in California, actively contributing to the development of JetZero’s groundbreaking Blended Wing Body (BWB) aircraft. My work focuses on the design and implementation of advanced System Integration Laboratory (SIL) facilities, including the Iron Bird—a cutting-edge testing lab designed for comprehensive and rigorous evaluation of aircraft systems. This innovative endeavor pushes the boundaries of aerospace technology, leveraging real-time closed-loop testing and cyber-physical integration to elevate aviation safety and reliability.
 

I hold a Ph.D. in Electrical Engineering and Computer Science from UC Irvine, where I focused on improving the safety and reliability of AI-driven, perception-based autonomous systems. My research, under the guidance of Prof. Yasser Shoukry in the Resilient Cyber-physical systems group, specialized in applications like autonomous aircraft landing and self-driving vehicles. By integrating machine learning, formal methods, control theory, and machine vision, I created robust frameworks for these critical systems.


Prior to my doctoral studies, I gained valuable industry experience at Honeywell Aerospace. I also hold a Master’s degree in Astronautics and Space Engineering from Cranfield University and a Bachelor's degree in Mechatronics Engineering from Universidad Autónoma de Baja California


R&D Projects

• (CDC-23) Certified Vision-based State Estimation for Auto Landing Systems using Mixed-Monotone Reachability Analysis.
• (NFM-22) Neural Network Formal Verification Framework for Vision-Based Autonomous Aircraft Landing.
• (CDC-22) Convex Optimization Approach for Repairing Unsafe Two-Level Lattice Neural Network Controllers.
• (CDC-21) Provably Safe Model-Based Meta Reinforcement Learning.
• (GNSS-19) Orbit Modeling for Simultaneous Tracking and Navigation using LEO Satellite Signals.

• (IAF-18) Networked and Distributed Cooperative Attitude Control of Fractionated Small Satellites.

Projects

    Blog

    Book Downloads

    PhD Thesis: Formal Verification of Perception Based AI Systems (pdf)Descargar
    CV Ulices Santa Cruz 2025 (pdf)Descargar

    Consulting Services

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