AerospaceNU / Northeastern University · ME & Physics ’29
Eduardo Snel
I've designed rocket avionics and recovery systems and built an aircraft from scratch — hands-on engineering, backed by real flight data.
I've designed rocket avionics and recovery systems and built an aircraft from scratch — hands-on engineering, backed by real flight data.
I was the sole designer and builder of the electronics bay (E-bay) — the sealed section that integrates the flight computer, altimeters, and deployment charges. I ran the vehicle's center-of-gravity and center-of-pressure (CG/CP) calculations to validate stability, and led on-site assembly and systems integration on launch day. The rocket reached 2,829 ft at Mach 0.5 and was recovered successfully.
I modeled the bay in SolidWorks around the flight computer and altimeters, sized the board, battery, and arming hardware to fit the coupler, and built the wiring harness and ejection-charge wells. The bay had to stay sealed and survive boost loads while keeping the recovery electronics reliable.
My OpenRocket model put the vehicle at a 2.09-caliber stability margin — CG at 111 cm, CP at 132 cm — which drove the fin and mass decisions. On launch day I led on-site assembly and oversaw systems integration, getting avionics, recovery, and airframe working together before the vehicle went on the rail.
About two months after joining AerospaceNU, I independently designed and built a foam-board fixed-wing aircraft from scratch. It completed a successful first flight with no structural failures — every decision, from aerodynamics to center of gravity to control setup, right on the first attempt.
A conventional high-wing layout with a tractor propeller and standard tail, chosen for stable, forgiving handling. I did the design, fabrication, and electronics install myself, dialing in the center of gravity and control-surface throws for a controllable maiden flight.
Taking an aircraft from a blank start to a clean first flight, solo and early on, meant owning every engineering call — airfoil and sizing, structure, balance, and controls — and getting them right without a second chance.
In the Foundational Mathematics of Artificial Intelligence course, I built a predictive model that forecast basketball tournament results with roughly 80% accuracy from team-performance data — the analytical counterpart to the flight-data work: turning raw numbers into decisions you can trust.
I'm a mechanical engineering and physics student at Northeastern University (B.S., May 2029), on the Dean's List with a 3.6 GPA. My hands-on work spans rocketry avionics and recovery with AerospaceNU, a scratch-built aircraft, and predictive modeling — and I'm currently building with Northeastern Electric Racing and BAJA. I like owning hardware end to end: design and analysis through fabrication, then reading the data to see what actually happened.