Hi!

I'm Chidubem, a Mechatronics Engineer. I build robots and the Machine Learning Systems.

Open to Machine Learning and Robotics engineering roles. Best way to reach me: email.

About

Mechatronics Engineer interested in the intersection of Robotics and AI, and I also build Machine Learning systems that solve problems

Outside of building, I write The Nerd Stack, a newsletter on robotics, MLOps, and ROS2, and occasionally on Medium.

Currently Building GramAI for the Africa Deep Tech Challenge 2026 (Gate 1: Aug 25).
Interests ROS2 & Robotics Machine Learning Technical Writing

Achievements

  1. 2026 (Current)

    Africa Deep Tech Challenge 2026

    Paste a traceback, get a fix. Building GramAI, an offline Python debugging assistant, for Gate 1 (Aug 25).

  2. July 2026

    B.Eng. Mechatronics Engineering, Nile University of Nigeria

    Graduating with a capstone project on Cika, an autonomous ROS2-based waste-collecting robot.

  3. 2025

    Reservoir Performance Intern, SLB

    Seven-month internship in Port-Harcourt covering data acquisition, demand forecasting, and Power BI reporting.

    Maintenance of oil field equipment for Coiled Tubing and High-Pressure pumping services.

  4. 2025

    Sentinel: Fraud Detection MLOps Platform

    Built and documented a eight-container MLOps stack for real-time credit card fraud detection.

  5. 2022–2023

    Hamoye AI Internships

    Data analytics and MLOps internships, including containerized model deployment with Docker and Kubernetes.

Currently Shipping

4WD skid-steer AMR running ROS2 Humble with SLAM Toolbox, Nav2, and EKF sensor fusion. RPLIDAR + OAK-D Lite for perception, YOLOv8 on-device waste detection, 6-DOF arm via MoveIt2. Capstone project, compute split across Raspberry Pi and laptop over a UART-to-ESP32 control bridge.

End-to-end MLOps platform for credit card fraud detection. Nine-container Docker Compose stack: Airflow, MLflow, Feast, FastAPI, PostgreSQL, MinIO, Redis, Streamlit. Sub-10ms feature serving, daily automated training pipeline.

Python traceback debugging assistant built on Qwen2.5-3B via llama.cpp, with a two-tier RAG corpus for grounded fixes. Built for the Africa Deep Tech Challenge 2026.

Comparative study of BFS, DFS, A*, and a Genetic Algorithm on static and dynamic grid environments. Custom C++ visualization engine built with Raylib, benchmarked across a 100x100 grid with moving obstacles.

Recent Writing

Vision Language Action (VLA) Models

A look at how VLA models bridge perception and physical movement, from RT-2 to pi0.

· robotics, deep learning, computer vision · 8 min read

GitHub Activity

Duks31

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