AI/ML Engineer building scalable intelligence | Computer Vision & NLP Specialist
Accra, Ghana
As an AI/ML Engineer and researcher, I specialize in developing scalable machine learning solutions that address critical challenges in healthcare, agriculture, and social impact domains. My work spans computer vision, natural language processing, and IoT integration, with a strong emphasis on deploying production-ready models that drive measurable outcomes.
My research contributions include award-winning solutions in healthcare AI (clinical reasoning, disease outbreak prediction) and agricultural technology (crop disease detection for mobile deployment). I am particularly interested in responsible AI development, with focus on building systems that are accessible, ethical, and beneficial for underserved communities in developing regions.
Currently pursuing advanced research opportunities to further explore the intersection of AI and social good.
• Accelerated claims processing by 40% through custom OCR and object detection models integrated into SnapInsure app
• Increased claims validation accuracy by 45% via RAG model using FAISS and LangChain for real-time document analysis
• Built electronic signature model integrated into core application enabling seamless document signing with YoloV8
• Developed claim cause-to-loss validation system using damage detection models to verify reported damages
• Built cost estimator for damaged car parts with instant web scraping for price comparison to accelerate claims processing
• Implemented Ghana Card OCR system for automated identity verification with paddleOCR
• Developed object tracking model for vehicle inspection to prevent fraud during claim uploads
• Built ASR models using OpenAI Whisper and PyAnnote for speech diarization, automatic transcription, and multi-language translation pipelines
• Developed trash classifier model using YOLOv11 for deployment on robotic arm systems
• Built face recognition-based attendance system with anti-spoofing capabilities
• Developed comprehensive investment management module integrated into Phrontlyne ERP system
• Automated critical business processes in Phrontlyne ERP, improving operational efficiency by 30%
• Executed complex data migration projects ensuring seamless system transitions with zero data loss
• Designed and built comprehensive claims analysis reports using JasperStudio for executive decision-making
• Architected interactive Reinsurance Dashboard using Metabase for real-time risk assessment and portfolio monitoring
• Built advanced claims analytics dashboard featuring word clouds for location analysis, loss description insights, and n-grams visualization for cause-of-loss pattern recognition
• Fine-tuned Mistral model for AI mentorship platform, improving interaction quality by 15%
• Developed mentor-mentee matching algorithm using cosine similarity, achieving 30% better matching accuracy
• Developed diabetes prediction models achieving 85% accuracy using diverse patient attributes
• Created interactive Tableau dashboards, improving stakeholder engagement by 25%
Challenge: "Can you turn the tide on waterborne diseases by predicting the next outbreak in Tanzania?"
Developed machine learning models to predict outbreaks of climate-sensitive waterborne diseases (typhoid, amoebiasis, diarrhoea, schistosomiasis, intestinal worms) in Tanzania using comprehensive datasets spanning water sources, sanitation quality, waste management, health facilities, and climate data from 2019-2023.
Impact: Enabling governments and health organizations to implement timely, targeted interventions and optimize resource allocation for vulnerable populations.
Challenge: "Can you build a model for mobile phones to identify diseases on tomatoes, corn, and peppers?"
Built robust machine learning models for accurate prediction of multiple diseases in corn, pepper, and tomato crops, with focus on generalization to unseen diseases and efficient operation on entry-level smartphones used by subsistence farmers in Africa.
Impact: Supporting food security for millions by enabling timely disease detection in crops that form the backbone of Sub-Saharan African agriculture.
Challenge: "Can your model match real clinicians in rural Kenyan healthcare?"
Developed AI models to replicate clinical reasoning of trained healthcare professionals using 400 authentic clinical prompts from diverse Kenyan healthcare settings. Models predict clinician responses across maternal health, child health, and critical care scenarios.
Impact: Supporting frontline healthcare workers in resource-limited settings with AI-assisted clinical decision making.
BSc. Computer Engineering | GPA: 3.84
Research Interests: Machine Learning, AI in Healthcare, Computer Vision & Robotics, Deep Learning, LLMs & NLP, Scalable AI, AI Ethics
Honors: Provost's List (2020-2023), Multiple Excellent Student Awards
Advanced multilingual document analysis platform supporting 160+ languages with comprehensive agentic capabilities. Features include natural language document interaction, voice chat, web search agents, custom data visualization and regression analysis, research assistant agents, and CV analysis tools.
Key Features: Document upload and analysis, voice-enabled queries, intelligent web search, automated data visualization, custom regression modeling for dataset analysis, research assistance with citation management, and comprehensive CV/resume analysis.
Production AppIntelligent recruitment platform providing personalized job-fit assessments and candidate matching using advanced ML algorithms.
Production AppIoT-enabled water quality prediction system using LSTM and Gradient Boosting Models, achieving 96% accuracy for real-time monitoring.
Research ProjectComprehensive customer sentiment analysis and booking prediction system for British Airways. Analyzed customer sentiments, booking patterns, and developed predictive models to enhance customer satisfaction and optimize booking processes.
Simulation ProjectConvolutional Neural Network built with TensorFlow for multi-class image recognition with data augmentation and transfer learning.
ML ProjectComprehensive business intelligence analysis uncovering sales patterns and customer insights using statistical modeling.
AnalyticsClimate data exploration and predictive modeling for weather pattern analysis and forecasting.
Data ScienceUber data analysis revealing mobility patterns and optimizing transportation efficiency through geospatial analytics.
AnalyticsEnd-to-end machine learning pipeline for loan default prediction using ensemble methods and feature engineering.
ML Pipeline