Hi, I'm Carlos!

A seasoned Software Developer based in Kingston, Ontario. I use my expertise in Artificial Intelligence, Signal Processing and QA Test Automation to turn ideas into MVPs.

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About Me

Get to know me!

Hi, my name is Carlos and I am a highly ambitious and self-motivated software developer based in Kingston, Ontario.

I graduated from Western University with a Master's in Electrical and Computer engineering. I am passionate about turning concepts into reality and I leverage Artificial Intelligence, Signal Processing and QA Test Automation to architect state-of-the-art Minimum Viable Products (MVPs).

I am a tinkerer at heart and I find joy discovering new niches to dive into, from software development and test engineering to regulations, quality standards, and documentation. If any part of my background resonates with you, please feel free to connect. I am always open to discussing new opportunities. 🙂

My Skills

Python

Nix

Tailwind CSS

HTML

JavaScript

Computer Vision

Git

Test Automation

Natural Language Processing

Technical Writing

Projects

LLM Building Code Expert

DollyExpertBuilder is an LLM assistant capable of domain-specific Question Answering by Retrieval using a custom Vector Database based on the XML sitemap of the Ontario Building Code.

Automatic Beverage Inspection

SpiritVision is a multi-class image classifier capable of recognizing methanol spikes in mezcal drops. Trained with Transfer Learning using Pytorch and image processing with OpenCV.

Image-based Surgical Planning Tool for Bone Conduction Devices

Developed and validated a computer vision algorithm to aid in surgical planning of bone conduction devices by ray-tracing and segmentation of clinical CT images of the skull.

Secure Multiparty Computation Course Development

Developed course materials on Additive Secret Sharing and Beaver Triplets (Private Matrix multiplication) cryptography concepts and Python algorithm implementations and use cases of the PySyft library.

AWS Geospatial Flask App

A Web App displaying hospital bed availability in the USA originally deployed on AWS using a S3 hosted dataset, an EC2 instance and Elastic Beanstalk.