Aerospace R&D, Control Systems, Real-Time Simulation, Artificial Intelligence, Test & Instrumentation, Automation.
Aerospace R&D, Control Systems, Real-Time Simulation, Artificial Intelligence, Test & Instrumentation, Automation.
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 two major System Integration Laboratory (SIL) environments into full operational capability: the Flying Qualities Lab (FQL)—focused on evaluating and refining aircraft Control Laws (CLAWs)—and the Integration Test Facility (ITF), used for real-time testing of actual aircraft systems through Software-in-the-Loop, Hardware-in-the-Loop, and Man-in-the-Loop configurations. 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
• (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.