Aidan Hallberg

Mechanical Engineering and Computer Science Student

Hardware and Product Engineering

aidanhallberg.com

I'd like to highlight some of my engineering projects across hardware and software development.

Hardware

Caliber – Smart Nutrition Scale

Manufacturing-ready smart nutrition scale that combines load-cell sensing, barcode scanning, and a connected app to automatically log food and nutrition.

Hardware + Software · 2025 – Present

First hand-soldered prototype. Top plate removed for visibility.

Redesigned using PCBs for manufacturability. Top plate removed for visibility.

C++ESP32PCB Design Design for ManufacturingAWS IoTMQTTReact Native

Project details

Designed and fabricated a manufacturing-ready smart nutrition scale with a custom multi-board PCB; sourced components and negotiated with suppliers to reduce BOM cost.
Implemented load-cell sensing, barcode scanning, and C++ firmware on ESP32, integrating the device and React Native app through an AWS IoT/MQTT cloud backend.
V2 prototype demonstrates seamless barcode scanning, automatic item tracking, and live app–scale communication in the demo video.
V4 redesign targets manufacturing with a multi-board PCB and solderless connections; ESP32 S3 Supermini integration and antenna testing in progress.
Updated BOM (PCB only): two-board design — motherboard: ESP32 S3 Supermini, M5Stack Mini Scales Module, resistors, MOSFET; daughterboard: capacitors, 2.4" TFT LCD, EMT8120AD barcode scanner, push buttons (enclosure and assembly hardware excluded).

Demo
View project demo at caliberscale.com

U.S. Air Force-Sponsored Research — Morphing Wing Test Article

Reconfigurable morphing-wing test article with an analytical model for predicting failure loads and ligature-driven twist morphing.

Undergraduate Research · Smart Materials & Structures Design Lab · Dec 2025 – May 2026

U.S. Air Force morphing wing research poster

Research presented at the ME Undergrad Symposium.

SolidWorksMATLAB Analytical ModellingExperimental ValidationMorphing Structures

Project details

Designed and fabricated a reconfigurable morphing-wing test article with interchangeable ligature layouts and adjustable spring preload.
Developed a matrix-based analytical model predicting failure loads and moments for any ligature configuration and spring preload.
Validated the model across four axial/torsional loading modes, correctly predicting motion and failure thresholds with 12% mean error; demonstrated ligature-driven twist morphing.

Research Poster
View poster

Software

Commitd – Social Productivity App

Mobile app that helps students track tasks, share progress, and keep each other accountable through timelines, groups, and streaks.

Full Stack · 2024 – 2025

Commitd app home screen — Home screen with streaks and group progress.

Commitd app features — Friend's daily productivity and tracking your own goals.

Built with React Native, Expo, and Firebase. Features timeline scheduling, group progress views, streaks, and push notifications. Currently in beta with campus testers, iterating based on user feedback before App Store submission.

TypeScriptReact Native ExpoFirebase

Project details

Timeline scheduling and group progress views for shared accountability.
Streaks and consistency tracking to make habits visible.
Push notifications for reminders and check-ins.
Implemented core UI flows with Expo/React Native.
Designed Firebase auth, data model, and querying.
Set up beta testing, interviews, and an iteration loop.

Demo Video
App walkthrough

FlightSwap – Pilot Scheduling & Trades

Web app for airline pilots to swap trips and optimize schedules, powered by an agentic RAG engine that evaluates trades using rules and preferences.

Full Stack · 2024 – 2025

Account creation.

FlightSwap preferences — Set preferences for schedule.

FlightSwap marketplace — Trip trading marketplace.

FlightSwap proposed optimised trades — Finalize trades with other pilots.

Built with Next.js, Supabase, and AeroDataBox API. Features flight search, assigned trips, trade proposals, and an AI-assisted decision engine that uses RAG to recommend and evaluate trades based on pilot constraints and preferences.

Next.jsReact SupabaseAeroDataBox API LLM / RAG

Project details

Flight search, assigned trips, and trade proposals between pilots.
AI-assisted decision engine using an agentic RAG setup.
Built the Next.js UI and end-to-end data flows.
Set up Supabase auth, SQL schema, and queries.
Prototyped the recommendation logic and RAG pipeline.
Conducted several interviews with pilots to gather requirements and feedback.

Demo Videos
Profile creation · Preferences saving · Marketplace & trades

Happy to walk through any project live or dive deeper into implementation details!