I am a First Class Honours Computer Engineering graduate specializing in building robust, scalable AI systems. My research focuses on the intersection of Deep Learning and Systems Engineering—specifically how to deploy high-fidelity models in resource-constrained environments (Edge AI) and how to orchestrate complex decision-making systems.
Currently, I am executing an intensive Research Engineering Roadmap to master JAX, Distributed Training, and Geometric Deep Learning.
| Domain | Technologies |
|---|---|
| Deep Learning |    |
| Edge & MLOps |    |
| Development |    |
| Math | Stochastic Processes • Linear Algebra • Graph Theory • Optimization |
I am currently working through a "Zero-to-SOTA" Research Engineering Curriculum:
- 🌱 Learning: Implementing Vision Transformers (ViT) from scratch in PyTorch & JAX.
- 🔭 Project: Building an Agentic LLM Orchestration system using local models (Llama 3).
- ⚙️ Engineering: Mastering Docker and Kubernetes for distributed training pipelines.
- 🧩 Grind: Solving 1 LeetCode problem daily (Graphs & Dynamic Programming).
👉 Follow my Daily Progress Log here
- AI-Driven Plant Health Diagnosis System (Final Year Thesis - Grade A)
- Engineered a hybrid Edge-Cloud orchestration system for agricultural disease diagnosis.
- Features: Weighted Ensemble (ResNet/EfficientNet) on Cloud + Quantized MobileNetV2 (TFLite) on Edge.
- Impact: Achieved 94.9% Accuracy and enabled offline inference for rural farmers.
- 💼 LinkedIn: linkedin.com/in/josué-signe
- 📧 Email: signeemmanuel28@gmail.com