Paul Okafor

Paul Okafor is a highly skilled Data Scientist and AI Engineer with a strong foundation in machine learning, deep learning, and natural language processing (NLP). He excels at developing and deploying AI-powered solutions, with experience spanning computer vision, LLM, AI Research, and the creation of intelligent AI agents. Paul has a proven ability to leverage data to solve complex problems, as demonstrated by his work on projects addressing healthcare challenges, unemployment, and the digital lending landscape in Africa.

His technical expertise encompasses a wide range of tools and technologies, including Python, Streamlit, TensorFlow, PyTorch, scikit-learn, and various cloud platforms. Paul's projects, such as his sentiment analysis of Nigerian digital lending platforms and his contributions to hackathons focused on African health and unemployment, highlight his commitment to using data science for social impact. He is proficient in building end-to-end machine learning pipelines, from data collection and preprocessing to model development, deployment, and visualization.

Passionate about continuous learning and contributing to the open-source community, Paul is also focused on developing cutting-edge AI solutions for healthcare, including cost-sensitive online learning models for anomaly detection in real-time monitoring and interpretable machine learning models for optimizing biomanufacturing processes. His research has been published at the 2024 IEEE Big Data Conference, demonstrating his commitment to advancing the field. He is adept at transforming complex data into actionable insights and is driven by the potential of AI to create positive change. His experience includes building custom LLM chatbots, license plate detection systems, and predictive models for disease classification, showcasing his versatility and adaptability across different domains.