London, England, United Kingdom
• Classifying researchers based on interdisciplinary collaboration between Engineering and Healthcare Engineering through analysis of 200,000+ publications and 300,000+ researchers at University College London, leveraging Latent Dirichlet Allocation (LDA) & Support Vector Machine (SVM) algorithms
• Established reliable data mining engine and data processing infrastructure, deployed on MS Azure
• Delivered usable front-end using Django for data visualization (TSNE clustering, Intertopic Distance Map, Bubble chart), analysis & validation
• Technologies used: Python, LDA, SVM, Microsoft Azure, MongoDB, PostgreSQL, SQL Server, Django
