Lois Nhyira Amoah Otoo
ACCRA
Overview
3
3
years of professional experience
1
1
Certification
Work History
AI & ROBOTICS TRAINER
Coderina Education and Technology Foundation
ACCRA
10.2022 - Current
• Designed and implemented ML-based robotics training modules for schools and communities.
• Trained students in Python-based AI algorithms for robot control and automation.
• Developed a computer vision project using OpenCV for object detection in robotics.
AI & MACHINE LEARNING INTERN
West African Centre for Cell Biology of Infectious Pathogens (WACCBIP)
ACCRA
02.2024 - 03.2024
• Applied machine learning and deep learning algorithms to biomedical datasets for drug target prediction.
• Developed AI models to analyze medical images and detect lesions in tumor scans.
• Collaborated with research scientists to train predictive models for early-stage disease detection and drug efficacy analysis.
• Gained hands-on experience in data preprocessing, model training, validation, and interpretation in a healthcare context.
INTERN
STEM Academy Achievers Ghana
ACCRA
07.2022 - 09.2022
• Built and programmed robots using Lego Spike, WeDo, EV3 Mindstorms, integrating ML models.
• Assisted in data processing and analysis for student performance assessment.
• Introduced basic AI concepts to students, including supervised learning and neural networks.
Education
Bachelor of Science - Biomedical Engineering
UNIVERSITY OF GHANA-LEGON
ACCRA,GHANA02-2026
Key strengths
|Artificial Intelligence & Machine Learning|Programming|Research|Robotics
Research Experience
Undergraduate Research-(Sep 2024-August 2025)
Instituition:University of Ghana at the Biomedical Engineering department
Title:Design of an Interpretable Deep Learning Web-Based System for Classification and Segmentation for Early Alzheimer's Detection using MRI Scans
· Developed ADPRED, a web-based deep learning pipeline for automated brain MRI segmentation and multi-class Alzheimer's disease classification, with interactive visualization for clinical use.
· Preprocessed ADNI MRI data via skull stripping, bias field correction, normalization, registration, and ROI masking (hippocampus and lateral ventricles) to enhance input features.
· Implemented 3D U-Net for segmentation, ResNet18 classifier, and Grad-CAM interpretability; deployed as a web app supporting MRI upload, processing, segmentation, classification, and results visualization.
· Achieved 0.84 Dice Similarity Coefficient for segmentation and 97.2% classification accuracy across four AD stages, with Grad-CAM confirming alignment with known biomarkers.
Technical/Software Experience
Scripting & Programming: Python, C++,Matlab
Data Management & Storage: MySQL, MySQLite, Pandas
Machine Learning Scikit-learn, Pandas, Numpy
Deep Learning: TensorFlow, keras. ConvNets
Data Visualization: Excel, Matplotlib, Seaborn
Robotics & Automation: Raspberry Pi, Arduino, Lego Mindstorms
Software Engineering: Object-Oriented Programming, Version Control (Git)
Office Tools: Microsoft Office Suites
Scholarly Accomplishments
Poster Publications
1.Abubakar Sadiq Yusuf, Lois Nhyira Amoah Otoo, Issabella Mensah, Nana Yaa Doku-Amponsah. Design and Deployment of a Smart Telemedicine Station for Rural Healthcare Delivery, Presented at the Medical Innovation Expo 2025, October 13-15th, 2025, Academic City University
Certification
• Intro to AI & Machine Learning – Coursera
• Python for Data Science – IBM Data Science Professional Certificate (2024)
• National Science & Math Quiz Team – Methodist Girls’ high school
• Python for Data Science – IBM Data Science Professional Certificate (2024)
• National Science & Math Quiz Team – Methodist Girls’ high school
Languages
English
First Language
Timeline
AI & MACHINE LEARNING INTERN
West African Centre for Cell Biology of Infectious Pathogens (WACCBIP)
02.2024 - 03.2024
AI & ROBOTICS TRAINER
Coderina Education and Technology Foundation
10.2022 - Current
INTERN
STEM Academy Achievers Ghana
07.2022 - 09.2022
Bachelor of Science - Biomedical Engineering
UNIVERSITY OF GHANA-LEGON