Alvaro Alva — IoT engineer · M.S. Cybersecurity · edge-AI builder
Miami, FL — Trujillo, Perú · Dual U.S.–Peru citizenship · U.S. Army veteran
Now: building field telemetry and edge-AI systems for remote field operations.
Experience
Independent builder — present
Field telemetry, offline-first AI, UAV platforms.
R&D Graduate Intern, Sandia National Laboratories — 2023–24
Dynamic electrical-grid controller predicting over/under-loads from time-series data; secure energy-trading platform with fraud detection and honeypots.
CyberCorps® Scholarship for Service recipient — 2022–24
Federal cybersecurity scholarship; UAV-security research, FIU ACyD Lab.
Programmer Intern, American Express — 2020
Web application interfaces and reporting automation.
Fail-safe research for UAV platforms built on ROS2 under a federal cybersecurity scholarship.
Industrial ML — Research Experience for Undergraduates (2021)
Supervised model predicting factory pump pressure losses from process data.
Smart-home HVAC threat analytics — ShellHacks (2023)
Reinforcement-learning identification of attack vectors in a consumer HVAC control system, with homeowner-facing threat analytics.
Studies
B.S. Internet of Things — FIU, 2022
M.S. Cybersecurity — FIU, 2024
CompTIA Security+ — 2022
Doctoral research in CS — AI and edge agents; on founder leave to build.
Blockchain energy-transaction platform for prosumers on the Ethereum Sepolia testnet; privacy-preserving ledger storing the hash of Apparent Power per transaction; integrated anomaly-detection service reaching 98.36% accuracy.
Thesis, defended May 14, 2024 — full thesis on request.
Full thesis and resume available on request — online@alvaroalva.com.
Research
Detecting UAV intrusion from the motor wires
When GPS is spoofed or jammed, the sensors lie — but the motors don't. My first-author IEEE work detects attacks from the PWM signals that drive the aircraft itself, at the physical layer, below the software an attacker touches.
Alva et al., Secured UAV Navigation: A Novel Intrusion Detection System Based on PWM Signal Analysis, IEEE SDS 2024 — IEEE Xplore. Preprint on request.
Physical-layer IDS that detects GPS spoofing and jamming from motor-control signals when sensors are compromised.
Control room
Grid demand, replayed
U.S. EIA hourly demand, public domain.
A two-week slice of U.S. hourly electricity demand (EIA, public domain), replayed on an accelerated loop. The same class of time-series I worked with on grid controllers at Sandia and in my M.S. thesis.
About
Selected work
The essay
Planned · 2026
