Lewis Tem Bueh
AI/ML Researcher, Healthcare, Software Developer
Discover my research, projects and experiences in the world of AI and software development. I forge new paths and create innovative solutions to the most complex problems, defining what is possible with AI, healthcare and technology.
Who I Am
About Me
I am a Masters student in Data Science at the University of Buea and a skilled software engineer based in Buea, Cameroon. My passion lies at the intersection of AI and Healthcare, where I strive to build responsible solutions for real-world problems.
With a strong foundation in Machine Learning and Bioinformatics, I have contributed to impactful research in drug discovery and disease prediction. I am also the founder and Lead of Data Science Hub (DSH), a community at the intersection of AI and Sustainability engaging students in collaborative learning and real-world applications. Cultivating the next generation of African AI leaders to drive a new era continental innovation.
I am driven by curiosity and a commitment to excellence, defining whats possible with AI Research in Africa and beyond. I am always eager to connect with like-minded individuals and explore new opportunities to make a positive impact through technology.
Expertise
Technical Skills
Programming Languages
Machine Learning/AI
Bioinformatics
Data Science
Databases
Tools
Career Path
Work Experience
Codeathon Research Fellow
- Built BrainRoute, a machine learning-based tool for predicting Blood-Brain-Barrier (BBB) permeability of small molecules, utilizing molecular structure data to facilitate drug discovery for neurological diseases.
- Developed machine learning models to predict Blood-Brain-Barrier(BBB) permeability of small molecules from molecular structures, achieving 94% accuracy with F1 of 0.94 and AUC-ROC of 0.98 on best model.
- Implemented and optimized K-Nearest Neighbors and XGBoost classifiers for deployment in a web application enabling real-time BBB prediction.
- Built a curated database(BrainRoute-db) of predicted molecules with permeability scores to facilitate public access of data for drug discovery researchers.
Codeathon Research Fellow
- Developed machine learning classification model achieving 94% accuracy (F1: 0.85, Recall: 0.79) for predicting bioactive compounds against dengue virus.
- Collaborated with team to conduct molecular docking studies using AutoDock Vina and molecular dynamics simulations (100ns) with GROMACS.
- Performed comprehensive ADMET profiling and MMPBSA calculations to assess drug-likeness and binding energetics of predicted inhibitors.
- Co-authored publication in Frontiers in Chemistry (Impact Factor: 5.5) presenting integrative computational drug discovery approach.
Machine Learning Engineer Intern
- Engineered automated web crawling pipeline using Python (Selenium, Beautiful Soup) that collected and preprocessed data from over 3,000,000 webpages for NLP applications.
- Fine-tuned large language model on curated dataset to provide career guidance and scholarship information, improving response relevance and accuracy by 20%.
- Implemented data validation and quality control measures to ensure training data integrity across diverse web sources.
Academic Background
Education
University of Buea
Masters of Science. Data Science
Coursework: Machine Learning, Big Data Processing, Data Mining, Information Visualization, Advanced Object-Oriented Programming, Database Management, Research Methodology and Scientific Writing
University of Buea
Bachelors of Engineering. Software Engineering
Coursework: Data Structures and Algorithms, Machine Learning and AI, Database Management, Operating Systems