Professional Overview
I'm a Computer Science undergraduate at UAJK (expected 2027) with completed coursework in statistics and data mining and hands-on Python experience (Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn). To practice evaluating AI output, I wrote 20 statistics problems with step-by-step reference solutions, ran them through an LLM, and graded every answer. The model scored 19/20 (95%, 95% Wilson CI 76.4% to 99.1%), and I documented the incorrect answer and its error type. The responses, grading data, and code are public on my GitHub. I also built a 4-agent LangChain document-processing pipeline (DocuFlow) and ML classification pipelines comparing Decision Tree, SVM, and Random Forest models. I write technical articles on AI concepts and bring clear, structured written communication to model evaluation work.
Areas of Expertise
AI & Machine Learning Engineers
Design, train, and ship production ML models — from data pipelines to model inference at scale. Covers supervised learning, neural networks, LLM integration, and model optimisation.
Data Science & Analytics
Extract business insights from raw data using statistical modelling, predictive analytics, A/B testing, and interactive dashboards.
Automation & AI Workflows
Build intelligent automation pipelines, integrate AI APIs into existing tools, and replace manual workflows with agentic AI systems.
NLP & Prompt Engineering
Build natural language processing systems, fine-tune large language models, and craft reliable production prompts for AI-powered products.
