I’m Syed Sarib Naveed, a Machine Learning Engineer with a BSc in Computer Science from Namal University. Over my career I’ve merged research and industry engineering to solve real-world problems and publish novel work. I co-authored two papers in Scientific Reports (Nature Portfolio):
- One on scene flow based deep network for 3D hand reconstruction (I developed the module that merges motion and spatial features and enforced temporal smoothness).
- The other on genetic algorithm augmentation for imbalanced learning (I built the GA pipeline and trained the neural models to benchmark performance against SMOTE/ADASYN).
In industry and academic-applied projects I’ve built ML systems for: classification, regression, time-series forecasting, anomaly detection, OCR, and production-ready deployments (Python, TensorFlow, PyTorch, Docker, AWS, CI/CD). On the research-writing side, I have experience in drafting literature reviews, formulating research methods, implementing experiments, writing up results, and publishing peer-reviewed work.
Here’s how I help clients:
Custom ML Models & Services: I develop end-to-end solutions (data ingestion, preprocessing, model development, evaluation, deployment).
Research & Technical Writing: I draft research proposals, experiment reports, journal-style papers, conference submissions, and white-papers in machine learning.
Model Improvement & Deployment: I tune models (for performance, fairness, especially on imbalanced data), then deploy as APIs or containerised services.
My strength lies in bridging theoretical research ideas and practical deployment, enabling you not only to get a model or paper, but to produce a solution or publication you can use. If you have an ML challenge, a research writing need, or a deployable system in mind — let’s connect and map out a plan.