I’m a mechanical and aerospace engineer focused on robotics, autonomous systems, and intelligent 3D reconstruction. My background combines hands-on engineering design, simulation, research, and applied AI, with experience across robotic mapping, next-best-view planning, Gaussian splatting, UAV/rover simulation, and mechanical prototyping.

I hold a B.S. in Mechanical Engineering from Tecnológico de Monterrey and an M.S. in Aerospace Engineering from Arizona State University. I’m currently a Volunteer Research Assistant at ASU’s DREAMS Laboratory, where I work on autonomous exploration and reconstruction pipelines using tools such as ROS 2, PX4, Gazebo, RViz, Python, point clouds, photogrammetry, and 3D Gaussian Splatting.

My work focuses on helping robots perceive, map, and reconstruct complex environments more intelligently. I have contributed to research involving active 3D reconstruction, next-best-view planning, digital twins, Gaussian-splatting-based scene representation, and autonomous sensing platforms. I’m especially interested in systems that connect simulation, perception, autonomy, and real-world deployment.

Before focusing heavily on robotics research, I developed a strong foundation in mechanical design and fabrication through projects involving aircraft structures, composites, CNC machining, conventional manufacturing, SolidWorks, and experimental testing. This gives me a practical engineering perspective: I enjoy not only designing algorithms and simulations, but also understanding how robotic systems are built, tested, and deployed in the real world.

My current goals are to grow as an engineer at the intersection of robotics, AI, autonomous systems, and technical strategy. I’m particularly interested in roles and projects involving robotic perception, simulation, synthetic data generation, autonomous mapping, UAVs/rovers, and AI-enabled engineering workflows.

I’m always looking to build useful systems, learn from challenging technical problems, and contribute to work that makes autonomous robots more capable, reliable, and useful in real environments.