About Me
I am a PhD student in Computer Science at Loyola University Chicago, advised by Ifeoma Ozodiegwu, Francisco Iacobelli, and Mohammed Abuhamad. My research is in agentic AI, with a focus on how AI agents reason, plan, and execute multi-step tasks. My current interests include:
- Reasoning and planning in AI agents for complex workflows
- Reliability and error propagation in multi-agent systems
- Benchmarking and improving LLM reasoning for data analytics
I am currently investigating how reasoning models perform across data analytics benchmarks, studying where step-by-step planning breaks down and how to build better training data to improve agent capabilities. This early-stage work is shaping my broader dissertation direction in agentic AI, grounded in real-world applications through ChatMRPT, a conversational AI system I built for public health decision-making in Nigeria.
Education
PhD in Computer Science
Loyola University Chicago
2026 - Present
Research Focus: Reliable Reasoning in Tool-Using AI Systems
Master of Science in Data Science
Loyola University Chicago
December 2024
Experience
AI Engineer
May 2025 - December 2025Nilotic Hoops AI, Chicago, IL
- Built AI-powered basketball talent discovery platform using pose estimation and object detection to analyze game footage and generate automated skill assessments for athlete recruitment.
- Developed multi-factor scoring engine ranking athletes on shooting form, athleticism, and game performance with personalized training recommendations.
- Deployed full-stack recruiting platform (React 18, FastAPI, Supabase) with video analysis pipeline, scout discovery dashboard, and role-based authentication at <500ms response times.
Machine Learning Engineer
May 2024 - December 2025Loyola University Chicago, Chicago, IL
- Built AI-powered malaria prioritization chatbot (ChatMRPT) with multi-model routing, integrating 10+ geospatial analysis tools to process environmental raster data for public health decision-making.
- Developed ensemble ML model combining gradient boosting with spatial clustering to predict disease hotspots, achieving 95% classification accuracy.
- Deployed production system on AWS (EC2, ALB, CloudFront, ElastiCache) with sub-second response times supporting concurrent users.
Selected Projects
ChatMRPT
AI-Powered Malaria Prioritization System
Multi-model conversational AI with 10+ geospatial analysis tools for public health decision support; deployed for active use by research collaborators.
Technical Skills
AI & Machine Learning
LLM systems, multi-model routing, pose estimation (MoveNet), object detection (YOLO), PyTorch, scikit-learn, LangGraph
Data Science & Analysis
Pandas, NumPy, GeoPandas, raster processing, spatial analysis, Plotly, statistical modeling, ensemble methods
Full-Stack Development
FastAPI, Flask, React, TypeScript, PostgreSQL, Redis, WebSockets
Cloud & Infrastructure
AWS (EC2, ALB, CloudFront, ElastiCache), Docker, GitHub Actions CI/CD