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CS/CTE Educator · AI Engineer · Robotics Instructor
I build robots, train models, ship software, and — most importantly — teach the next generation how to do all three.
Passionate educator and engineer with a Master's in Atmospheric Science and deep hands-on expertise across AI, machine learning, robotics, and full-stack software engineering. I design inclusive, standards-aligned CS curriculum that bridges theory with real-world applications — from training neural networks and building ROS2 robots to deploying Next.js web apps and programming ESP32, Arduino, and Raspberry Pi microcontrollers. Proven track record of lifting student proficiency to 91% through project-based learning and AI integration across K-12 and higher education environments.
Four domains where I build, teach, and ship real things.
Building agentic AI systems with CrewAI, LangChain, and LangGraph. From multi-agent pipelines to AI-powered classroom tools and intelligent automation.
End-to-end ML pipelines with TensorFlow, PyTorch, and Scikit-Learn. Applied to atmospheric science, education analytics, and real-world prediction systems.
Full-stack robotics from microcontroller to autonomous robot. ROS2 systems, ESP32 & Arduino circuits, Raspberry Pi projects, and IoT sensor networks.
Production-grade full-stack development with Python, React, and Next.js. REST APIs, Django backends, responsive frontends, and everything in between.
Every tool I reach for — organized by domain, visualized by icon.
University of Wyoming
Aug 2022 – Aug 2024
Advanced research in computational atmospheric modeling, large-scale data analysis, and scientific Python. Applied ML and neural network techniques to climate data pipelines.
Kwame Nkrumah University of Science and Technology
Sep 2017 – Oct 2021
Foundation in atmospheric science, climate modeling, and scientific computing. Introduced to data-driven problem solving, computational research, and statistical analysis.
Open to teaching roles, collaborations, speaking, and consulting.