Alex Popov design · robotic systems · programming

I studied physics and computer science at the University of Redlands and am now pursuing electrical engineering at Columbia University. My work sits at the intersection of experimental instrumentation, RF and microwave systems, prototyping, system design, and software—from CAD and analog signal conditioning to embedded firmware, test automation, and validation with bench instruments and field tests.

I’m motivated by R&D-style problems: defining measurable requirements, iterating on hardware and algorithms, and documenting results clearly. I've also led student teams (robotics, SEDS) where the goal is to ship defensible technology on a timeline.

View projects Résumé (PDF) LinkedIn GitHub
Portrait photo of Alex Popov

Experience

R&D RF Engineering Intern

Glenair

June 1 – August 21, 2026

Developed software and RF-test proof-of-concept systems for cable manufacturing, dielectric characterization, and automated antenna verification. The work combined signal processing, microwave measurements, mechanical design, electronics, and production-facing software.

Manufacturing software · DSP

Live Cable OD & FFT Analysis Software

Built production-facing software for RF cable manufacturing that streamed outer diameter measurements from LaserLinc laser gauges over OPC UA. The application performed live spatial FFT analysis, local-defect detection, PASS/FAIL logic, pause and reconnection handling, and automated engineering exports.

RF instrumentation · Material characterization

Microwave Cavity Resonator

Designed, simulated, manufactured, and VNA-tested a TE101 resonator to estimate the effective permittivity of finished PTFE and FEP cable-insulation constructions.

View case study

Embedded RF test · Proof of concept

Handheld Antenna PASS/FAIL Tester

Integrated a Raspberry Pi, NanoVNA, display, battery power system, calibration recall, and automated 902–928 MHz sweeps into a field-oriented antenna verification prototype.

Additional team contribution: supported the development and testing of two high-speed cable constructions with Glenair’s high-speed cable engineering team.

Research & projects

CAD render of a 3D printed doppler shift measuring device

Instantaneous Velocity Doppler Radar Device

Physics capstone · Instrumentation · Crank-Slider System

A stationary HB100 Microwave Sensor is mounted in front of an aluminum deflector that moves back and forth in a linear motion. The disk incorperates magnets and a stationary hall sensor beaneath it to be able to calculate RPM. As the deflector moves back and forth in front of the HB100 sensor, the emitted microwaves are stretched or compressed. An oscilloscope can display the instantaneous shifts in frequency (and therefore instantantanous velocity can be calculated) at specific crank angles.

  • Mechanism — 3D printed crank–slider (disk + rod) back-and-forth deflector motion
  • Deflector — Aluminum structure that moves back and forth in front of the HB100 sensor
  • RPM Calculation — magnets under disk; Hall + reference Hall for rotation phase
  • Data Collection — oscilloscope on HB100, Hall, and reference Hall; ESP32 RPM calculation

SolidWorks · HB100 · Hall effect · Crank–slider kinematics · Oscilloscope · ESP32

research & paper
Rover build session in a workshop

Multiterrain Aluminum Rover

SEDS Redlands · Systems integration

Structural rover: custom 5052 aluminum frame, jackshafts, drivetrain, and field-range telemetry. Led mechanical design and assembly plus electrical and communications.

  • Frame — 5052 structural aluminum and corner brackets
  • Drivetrain — 24 V motors (~24 N·m/mot) with custom jackshafts
  • Power — distribution, buck converters, motor drivers, and logic rails
  • Comms — telemetry range ~740 m (field tested)

CAD · Machining · Power distribution · Motor control · Telemetry

Mel spectrogram visualization from UrbanSoundAI

UrbanSoundAI (CNN & spectrogram generator)

Machine learning · Audio

Trained a CNN on UrbanSound8K to classify sound sources. Generates spectrograms from audio and runs inference end to end.

  • Data — UrbanSound8K
  • Pipeline — audio → spectrogram → CNN classification
  • Output — predicted class with confidence and spectrogram view

Python · CNN · Audio DSP · Spectrograms

github

Leadership

President, UoR Robotics & Drones

September 2025–Present

Focused on drones, applied CNNs, and student engineering projects. Past work includes FPV drones and AI smart cars with LiDAR and ROS object recognition.

  • Builds — drones, AI smart cars, perception systems
  • Support — funding and mentorship for student projects
  • Execution — roadmaps and steady weekly progress

President, SEDS Redlands

February 2024–Present

Students for the Exploration and Development of Space: rocketry, rover hardware, SpaceVision, and industry networking.

  • Programs — rocketry and rover development
  • Community — conferences and networking events
  • Mission — pathways into the space industry

Skills

Mechanical / CAD

SolidWorks, device enclosure design, rotational mechanics, crank mechanisms, MATLAB.

Electronics

Circuit and PCB design, Altium Designer, bench instruments, ANSYS HFSS, RF, VNAs, soldering.

Software / AI

Python, C, deep learning (CNNs), DSP.

Leadership

Planning, communication, and coordinating multidisciplinary teams.

Contact