Graduating May 2026

Edward Silva

BS Electrical Engineering @ Colorado School of Mines

• Experience

Incoming

SpaceX • Bastrop, TX

Embedded Software: Customer Hardware, DSP applications.

Kratos Defense • Colorado Springs, CO • June - August 2025

Achieved 1.6x execution speedup by optimizing legacy DSP algorithms in C++ through code refactoring and performance analysis, reducing computational overhead for real-time signal processing applications.
Improved system throughput by developing and implementing SIMD-optimized mathematical algorithms using vectorized operations for parallel data processing.
Researched and demonstrated an improved approach to coding a FIR filter, presenting positive findings and performance gains to the team for adoption in future projects.
Reduced debugging time and improved system maintainability for development teams by designing and deploying a comprehensive logging framework with configurable severity levels and error tracking.

Skills Used

C++ MATLAB Python SIMD

Jordan and Skala Engineers • Denver, CO • January - June 2025

Contributed to electrical design of 20+ multi-unit residential and specialty building developments, spanning initial takeoffs, layout design, riser diagrams, NEC verification, and QC review.
Developed proficiency in Autodesk Revit and MEP AutoCAD, strategically placing electrical receptacles, lighting, and circuits to ensure NEC compliance and practical, user-centered functionality.
Performed circuit loading and voltage drop calculations, balancing panel schedules and selecting appropriate breakers to ensure safety, reliability, and adherence to regulatory standards.
Utilized existing automation between Revit/CAD layouts and Excel tracking sheets to streamline design documentation processes and reduce manual errors.

Skills Used

Autodesk REVIT MEP AutoCAD NEC Compliance

Featured Project School Project

Fall 2025 - Spring 2026

Skills Used

MATLAB Python Jupyter Arduino

Designed and validated an internal electromagnetic coil for an actively controlled magnetorheological (MR) fluid mountain bike damper, utilizing a 26-AWG copper coil and steel core operating at 10W and 2A to generate an estimated peak 0.15 Tesla magnetic field across a 2.5 mm radial gap
Modeled magnetic field strength and spatial geometry using the Biot-Savart law and complete elliptic integrals in Python, ensuring field lines oriented perpendicularly to fluid flow to maximize yield stress activation

Fall 2025 • School Project

Skills Used

MATLAB Simulink

Estimated key plant parameters from experimental crane data, then built and validated both nonlinear and simplified simulation models in Simulink before designing a 50 Hz digital controller that moved a 1 m payload command with no overshoot while staying within the 1 m/s cart-speed safety limit.
Tuned the controller for smooth, predictable motion and confirmed robustness with frequency-domain checks, showing healthy stability margin and that the system could tolerate roughly half a second of additional delay before becoming marginally unstable.

Reframed the problem in state space and compared two observer-based LQR strategies, one using reference scaling and one using integral error with anti-windup; both achieved near-zero steady-state error under actuator limits, with about 3.5-4.0 s settling and low overshoot, and the augmented design giving the fastest no-overshoot response.

Fall 2025 • School Project

Skills Used

MATLAB Simulink Python Arduino

Co-developed an autonomous maze robot in a 4-person team by combining onboard vision, embedded motor control, and inter-device communication, helping deliver the second-fastest final run in the class.
Built the Python/OpenCV perception stack using ArUco marker tracking to estimate heading and distance in real time, giving the robot reliable position cues for turn timing and corridor alignment.

Designed a multithreaded 640x480 vision pipeline with HSV-based color segmentation so image capture, marker detection, and navigation decisions could run concurrently without blocking control updates.
Integrated the vision computer with an Arduino motor controller over I2C, streaming navigation telemetry while driving a live RGB LCD status display to improve debugging and on-course tuning.