About Me
Hi, I’m Husayn. I’m a Senior Data Scientist and Georgia Tech Ph.D. with over eight years of experience working with machine learning, geospatial analytics, and complex real world data. I enjoy taking messy information and turning it into insights that help people make better decisions.
My work spans remote sensing, environmental analytics, and applied AI, backed by models, pipelines, and dashboards I’ve built for researchers, engineers, and operational teams. I also mentor students and early career professionals who are developing their skills in data science and programming.
Grounded in civil engineering and hydrology, I bring a practical way of understanding complex systems, and that foundation still shapes how I approach data and problem solving. I now apply these skills across a wider range of fields where careful analysis can support meaningful, evidence based improvements in science, technology, and public health.
Skills
Portfolio
Remote Sensing & ML for Water Quality Assessment at Lake Lanier
Satellite-based ML workflow to monitor chlorophyll-a and assess water quality compliance for Lake Lanier.
Climate-Informed Crop Yield & Irrigation Projections for the ACF River Basin
Modeled climate-adjusted crop yields and irrigation demand to support long-term agricultural and water planning.
Continental-Scale Climate Bias-Correction, Projection, & Interactive Dashboard
Built bias-corrected climate projections and an interactive dashboard to explore multi-model climate futures.
Customer Churn Modeling & Retention Optimization with SparkML, MLflow, & Neural Networks
Developed scalable churn prediction models and experiment tracking to inform retention strategies.
AI-Automated Lead Generation Pipeline for Engineering Consultancy (RAG + Web Data)
RAG-powered pipeline to mine regulatory and web data, rank prospects, and surface qualified engineering leads.
AI-Powered Retinal Disease Detection with Deep Learning & Computer Vision Pipeline
TensorFlow-based CNN that classifies retinal images into disease categories to support early detection.
Multi-Agent GenAI System for Automated Hydrology Literature Review (CrewAI + LLMs)
Multi-agent LLM workflow to search, summarize, and synthesize hydrology papers into actionable briefs.
Voice-AI Customer Service Agent for Medical Lab Appointments
Voice AI system to automate medical lab appointment scheduling, rescheduling, and support calls.
Professional Experience
Data Scientist (Research Engineer)
- Developed end-to-end ML applications and dashboards for near-real-time water quality monitoring in Georgia’s Lake Lanier, enabling proactive, data-driven decisions for the Gwinnett County Dept. of Water Resources.
- Applied deep learning models (RNN/LSTM) to forecast crop yield and irrigation demand, enhancing watershed-scale agricultural decision support.
- Built a multi-agent GenAI system (CrewAI + LangChain + GPT + Gemini LLMs) to automate hydrology literature review workflows, reducing a 7-day manual research process to 1 day and accelerating scientific reporting productivity by ~85%.
- Oversaw $400K+ in annual federal and state research projects as Assistant Director, Georgia Water Resources Institute.
- Mentored and supervised student researchers in data science methods, guiding successful publications, conference presentations, and career advancement.
Engineering Consultant (Part-Time)
- Developed physics and data-driven system models and AI-Ops pipelines for real-time AWS IoT sensor analytics, improving engineering efficiency and reducing time-to-market by 20%.
Data Scientist (Postdoctoral Fellow)
- Applied ML and geospatial analytics to improve predictive flood-risk models, delivering actionable intelligence for government and community resilience planning across East Africa.
- Developed ML techniques that improved climate forecast accuracy and spatial coherence by over 50%, strengthening data-driven insights for long-term water resources planning and policy.
Machine Learning Researcher (Ph.D. Research)
- Applied ML to fuse multi-sensor NASA satellite imagery and climate time-series data, boosting accuracy of crop-yield, drought, irrigation, and streamflow forecasts and enabling basin-scale, data-driven water-management decisions across multi-decadal climate scenarios.
Data Scientist (Graduate Research Assistant)
- Built and validated ML models to reconstruct missing environmental data, improving accuracy and spatial consistency for hydrologic and climate analyses.
Education
Ph.D., Civil Engineering
Master of Science, Civil Engineering
Bachelor of Science, Civil Engineering
Contact
Interested in collaborating or discussing a project? Send me a message and I’ll get back to you.