Hans Luther

React front-end powered by a GCP/Firebase back-end with a Node.js/Express.js API. The app empowers users to take control of their online meetings by providing transcription, organization, and collaboration features.

After transitioning the project, I quickly began addressing issues to get to a beta release in short order:

* Added key features, such as sharing meetings, automatic action items, and organizing meetings into folders.

* Fixed codebase in adherence to best coding principles, specifically DRY (do not repeat yourself) and ETC (easy to change).

* Converted JavaScript codebase (front- and back-end) to Typescript, introducing type safety and reducing runtime errors.

* Implemented a Design System with all basic and advanced UI elements that are clean, functional, and intuitive. I created components from scratch using HTML and CSS without using UI frameworks such as Material UI.

We launched Anchor AI to a closed beta within a few weeks, followed by a public release shortly after. The app is stable, and Anchor AI has experienced significant user growth. The code base is easy to maintain and allows for quick iteration of features.

A highly-performant SaaS application for business financial planning and reporting. I wrote the statement of work (SOW), designed the business logic, created the initial front-end framework, and developed all back-end functionalities. The system uses a Cloud Firestore NoSQL database and exposes Cloud Functions microservices that perform all calculations and consolidations. The front end is built with Angular, Akita state management, and Angular Material and heavily uses RxJS to take advantage of the real-time features of Cloud Firestore. I also developed Python scripts for ETL and back-end processes.

An application that consolidates data from regulatory reports such as FFIEC and NCUA from all banks nationwide for commercial real estate entities to identify lenders with potential sale assets.

I developed this app using Python to ETL the data into a Cloud Firestore database. A React front end accesses the data through a REST API exposed by Cloud Functions for Firebase.

An analytics app for Las Vegas Strip casinos' gaming revenue based on the data published by the Nevada gaming regulator. I designed and implemented the entire application, beginning with ETL of the source data into a SQL database (SQLite), selecting, aggregating, and filtering the data with SQLAlchemy, creating the API endpoints with Flask, and displaying the analytics in the Angular front end.

I designed and developed a live tracking system for outdoor running events utilizing 3G GPS trackers.

A tracking server implemented as a Windows service receives GPS positions from individual trackers, performs necessary geographic calculations, and saves the positions to the database. The web application displays runners on a map and calculates statistics. The back end is built using C# .NET Web API, accessing the SQL server database using Entity framework. The front end is entirely HTML and JavaScript-based and implemented using the Kendo UI framework around Bootstrap and flat UI design.

I created this system as an alternative to the tracking architecture that required cellular service for deployment in remote event locations. I designed, assembled, and coded an ARM-based tracking device featuring a 900 MHz XBee radio and SiRF IV GPS receiver. The prototype was built with Tiva C LaunchPad.

The WPF client connects to the receiving XBee radio via a serial connection and plots GPS positions on a map enhanced with a predefined GPX course map.