Biomedical Engineering · AI / ML / DL Engineer
Biomedical Engineering student building AI solutions for healthcare and real-world challenges. Passionate about Machine Learning, Computer Vision, and AI Engineering. Seeking opportunities to build impactful, intelligent systems.
A Biomedical Engineering student passionate about the intersection of healthcare and artificial intelligence.
I'm a Biomedical Engineering student with a deep passion for AI, Machine Learning, and Deep Learning — especially their applications in the medical sector. I completed the SPARK Academy program where I built AI-driven medical imaging projects, and I'm constantly exploring new ways to combine healthcare with intelligent systems.
My projects range from credit scoring models and flood alert systems to patient health record platforms and brain tumor segmentation. I believe technology should serve humanity, and I'm on a mission to build AI that directly improves and saves lives.
Technologies & Tools
Real-world applications built with ML, AI, and a focus on impact.
Affordable Point-of-care, BloodTyping, impedance-based prototype (works like a glucometer but different principle) for rapid detection of blood group and Rhesus factor. Co-Founder, designed electrode prototypes, built a custom PCB copper strip, and 3D-printed the device.
Scattered Radiation Monitoring Prototype: A low-cost engineering prototype for monitoring scattered radiation near diagnostic X-ray environments. Worked on sensing circuits with silicon photodiodes, op-amps, and integrated real-time alerting.
Streamlit-based patient identity portal with AI-powered clinical assistant, fingerprint biometrics, cross-hospital record sharing, and NIN integration.
Maternal monitoring device that helps mothers understand their body before, during, and after pregnancy. Assists doctors in making swift decisions during childbirth by annotating baby's position with AI.
Research project comparing Kolmogorov-Arnold Networks (KANs) against traditional MLPs. Colab-based implementation exploring modern neural architectures.
Regression model predicting Boston housing prices using XGBoost with EDA, feature engineering, and evaluation metrics (MAE, RMSE, R²).
ML-powered flood risk prediction with SMS alerts via Twilio. Uses Random Forest to estimate probabilistic flood risk from weather data. End-to-end deployable system.
Pushing the boundaries at the intersection of AI and medicine.
Explored the performance of Kolmogorov-Arnold Networks against traditional Multi-Layer Perceptrons on benchmark tasks. Implemented in Google Colab with full reproducibility.
View GithubDeveloping deep learning models for automated brain tumor segmentation from MRI scans. Exploring U-Net architectures and attention mechanisms for improved accuracy.
In ProgressBuilding, competing, and winning.
First place in the 234 Artificial Intelligence Hackathon
Emerged as winner of the Nimeche Innovation Challenge
Second place in the Biodrive 2.0 competition
Pictures from hackathons, events, and achievements.
Physical devices built from the ground up — design, electronics, and fabrication.
For more images of the hardware, visit this link.
Continuous learning — expanding my knowledge every day.
Get the full picture of my experience, education, and skills.
Download ResumePDF · Updated June 2026
Have a project, idea, or opportunity? I'd love to hear from you.
odiwebenedict@gmail.com
/in/emeka-odiwe
/meeks627
linktr.ee/emekaodiwe