R&D engineer focused on machine learning, network applications, and GPU programming.
I build applied systems at the intersection of:
- machine learning and computer vision
- scalable software engineering
- networked application design
- GPU-accelerated and high-performance workflows
My work centers on practical research and development: prototyping intelligent systems, refining models, and turning technical ideas into deployable solutions. I enjoy collaborating on research-driven engineering, applied AI projects, and performance-focused software development.
- Machine learning and computer vision
- AI model tuning and optimization
- Edge inference and lightweight deployment
- Network application development
- Performance-oriented software engineering
- GPU programming and acceleration
A livestock image classification project focused on cattle face recognition, general livestock identification, invalid-image filtering, and edge deployment using TFLite.
High-performance and parallel computing work focused on scalable processing and computational throughput for demanding workloads.
- Repo: [Add repo link]
- Python
- TensorFlow / Keras
- Computer Vision
- Model Training and Fine-Tuning
- GPU Programming
- Network Applications
- Software Engineering
- Performance Optimization
I work across research, prototyping, and implementation — from experimental modeling to practical engineering. I’m especially interested in projects that blend technical depth with real-world impact, and I’m open to collaboration, contract work, and R&D partnerships.
- R&D engineering collaborations
- machine learning and AI engineering work
- GPU / performance-focused projects
- network application development
- contract and consulting engagements