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AlexJumaW99/README.md
Alex Juma: Agentic AI Γ— 3D Vision Engineer, Winnipeg, Canada

LinkedIn Β  Email me

About me

class AlexJuma:
    def __init__(self):
        self.location = "Winnipeg, MB, Canada πŸ‡°πŸ‡ͺ πŸ‡¨πŸ‡¦"
        self.roles = ["AI Engineer", "3D Vision Engineer", "Full-Stack & Desktop Developer"]
        self.agents = ["LangGraph", "Gemini", "RAG + pgvector", "human-in-the-loop"]
        self.vision = ["Gaussian Splatting", "TRELLIS", "COLMAP", "PyTorch + CUDA"]
        self.building = "multi-agent pipelines and GPU-native 3D reconstruction"

    def say_hi(self):
        print("Thanks for dropping by! Let's build something amazing together.")

me = AlexJuma()
me.say_hi()

What I build

πŸ€– Agentic AI systems 🧊 3D vision on the GPU
AdForge
A crew of specialised agents (director, art director, cinematographer, editor, QA supervisor) that turns a product brief into consistent video ads with Veo 3.1 and Gemini 2.5.
trellis-blackwell
Microsoft's TRELLIS image-to-3D model, made to run on Linux with NVIDIA Blackwell GPUs.
Maiya
Multi-agent RAG that ingests code, PDFs, images, audio and spreadsheets into pgvector and answers with citations.
Gaussian Splatting pipelines
Video β†’ COLMAP β†’ gsplat / Nerfstudio β†’ web viewer, containerised for Blackwell GPUs.
LangGraph Email Reviewer
Support-triage agent that classifies intent and urgency, retrieves policy, drafts replies with Gemini and waits for human approval.
Motion-Detector
Webcam motion detection with OpenCV that logs when each event starts and ends.

Tech stack

Tech stack. Agentic AI: LangGraph, LangChain, Gemini, FastAPI, pgvector, Streamlit. 3D and GPU: PyTorch, CUDA, Gaussian Splatting, OpenCV, Docker, Linux. Data and ML: scikit-learn, pandas, NumPy, Jupyter, D3.js, SQL. Languages and web: Python, JavaScript, C, HTML5, CSS, Django, Git.

Activity

3D skyline of my GitHub contributions over the last year, with total contributions and streaks

Includes private work Β· rebuilt every 6 hours by GitHub Actions

Snake eating my contribution graph

Audentes Fortuna Iuvat: fortune favours the bold

Pinned Loading

  1. ads_veo ads_veo Public

    A production-grade pipeline that orchestrates a team of specialised AI agents to generate consistent, high-quality product video advertisements using Google Veo 3.1 and Gemini 2.5.

    Python 1

  2. trellis-blackwell trellis-blackwell Public

    Trellis Fork that works on Linux Debian with NVIDIA Blackwell GPUs.

    Python 1

  3. RAGReady RAGReady Public

    Maiya is a LangGraph-powered RAG pipeline that ingests any file type β€” code, docs, PDFs, images, audio, spreadsheets β€” extracts text, generates metadata via Gemini, and stores 384-dim vector embedd…

    Python 1

  4. Langgraph-Email-Reviewer- Langgraph-Email-Reviewer- Public

    An agentic LangGraph workflow that automates customer support triage: classifies inbound email intent and urgency, retrieves relevant policies from a local knowledge base, drafts context-aware repl…

    Python 1