Chinedu Ekuma

About Me

I am a computational and AI/ML scientist specializing in transforming complex scientific and business challenges into data-driven, deployable solutions. My work blends advanced mathematical modeling, machine learning, LLMs, and high-performance computing to build predictive, scalable systems used across academia, industry, and enterprise applications. With experience leading multi-million-dollar AI programs and developing next-generation scientific-AI tools, I focus on delivering actionable insights that drive innovation and measurable real-world impact.

Technical Skills

• Python, Fortran, Bash — production ML pipelines & scientific computing
• AI/ML: deep learning, LLMs, multi-agent systems, causal inference, predictive analytics
• Computational & mathematical modeling for complex scientific and business problems
• High-performance computing, large-scale data pipelines, cloud systems (AWS, GCP, Spark)
• Statistical modeling, experimentation design, decision science, workflow optimization

Projects & Code

Selected projects highlighting the intersection of AI, computational science, and business impact:

• SMAtool — Physics-informed AI framework for materials discovery and quantum-scale simulation
• ElasTool — Automated elastic-property prediction using high-performance scientific computing
• PropertyExtractor — ML-based property extraction engine for large scientific datasets
• Enterprise ML Pipelines — Predictive and causal-inference systems delivering 5–45% business lifts in real deployments (code samples available upon request)
• View more on my GitHub →

Professional Links

Official online profiles of Chinedu Ekuma:

View Personal Website of Chinedu Ekuma
LinkedIn Profile of Chinedu Ekuma
Chinedu Ekuma LinkedIn Profile (Direct)
View GitHub of Chinedu Ekuma
Contact Me