Machine Learning Crop Yield Drivers
Explainable AI system using XGBoost and SHAP analysis to surface the features that actually drive agricultural yield.
AI systems & data engineering
I'm a Data Science undergraduate who works across the full stack of a model's life — forecasting, explainability, business intelligence and the engineering that gets a system into production.
I'm a Data Science undergraduate building systems that sit at the intersection of machine learning, analytics and software engineering — not just models that score well in a notebook, but tools that hold up once they're deployed.
That's taken me through AI forecasting systems, explainable machine learning, cybersecurity analytics, business intelligence dashboards, and a handful of local engineering tools built because I needed them myself.
Domains I work across
Forecasting, classification, explainability
RAG systems, retrieval, local LLMs
Dashboards, KPIs, executive reporting
CVE analysis, vulnerability research
Explainable AI system using XGBoost and SHAP analysis to surface the features that actually drive agricultural yield.
Time-series forecasting of air quality using Random Forest and XGBoost, deployed as a Streamlit app.
Lightweight LAN file server with drag-drop uploads, live previews and a clean desktop UI.
Executive analytics dashboard built in Tableau for KPI tracking, revenue insight and customer behavior analysis.
KNIME workflow for behavioral segmentation using classification and regression modeling.
Research-driven analysis of kernel CVEs — severity mapping and temporal patterns in security disclosures.
Time-series and geographic analysis of age-group dynamics and workload distribution in national identity systems.
RAG system turning YouTube videos into searchable knowledge — FAISS retrieval with answers generated through local LLMs.
A fast search tool for NCU's LMS courses by ID or name, linking straight through to official course pages.
A Chromium-based desktop browser built with PySide6 and QtWebEngine, with tabs, shortcuts and persistent profiles.
YOLO11-based classifier distinguishing helmet and no-helmet riders — a baseline for automated traffic monitoring.
A Manifest V3 browser extension that lets you select text on any page and ask an AI, through a draggable floating panel.
Open to internships, research collaborations and full-time opportunities. The fastest way to reach me is email.