Hello, I am Richard Djarbeng.

I hope to give you an introduction of myself here and possibly answer questions regarding myself on this page. There is a contact form at the bottom if you want to contact me.

Generally I am interested in the Internet of Things (IoT), Computer Vision and Machine Learning (ML) applications. I am currently improving my ML skills with the FastAI:practical deep learning course by Jeremy Howard as well as exploring applications of nano-banana; google’s latest computer vision model for Gemini.

I am currently working with Prof Edwin Mugume on a project building low cost weather sensors and focusing on deployment of these solutions across East Africa.

Previously, I worked with Prof Albert Presto at the Center for Atmospheric Particle Studies (CAPS) -Carnegie Mellon University, to build models to classify pollution sources from Particulate Matter (PM) filters using smartphone images. The aim was to conduct low-cost source apportionment of different pollution sources.

Contact with the form below or via email: rdjarbeng@rdjarbeng.com

I have summarized my experience, skills and a brief summary of my personal interests.

Computer Engineer | Machine Learning Enthusiast | IoT Developer

I specialize mostly in web development machine learning and Internet of Things (IoT) devices such as the Raspberry Pi and Arduino.

Professional Summary

Specialized in web development, machine learning, and IoT devices (Raspberry Pi, Arduino)
Experienced in developing progressive web applications and data-driven solutions
Skilled in cloud technologies, particularly Google Cloud Platform
Contributor to the complete machine learning package

Technical skills

Languages: JavaScript (ES6+), Python, Java, C++
Web Development: React.js, Node.js, Express.js, RESTful APIs, WebSockets
Cloud & ML: Google Cloud (Vertex AI, BigQuery), CNN Architectures
Tools & Practices: Git, Test-Driven Development
Others: PWAs, Performance Optimization, IoT (Raspberry Pi), Satellite Image Processing