Technical Knowledge Intermediate
Summary
Strong foundation in the mathematical underpinnings of data science, with hands-on experience implementing core algorithms from scratch in R. Proficient in linear algebra techniques including SVD, QR factorization, Gram-Schmidt orthonormalization, eigenvalue analysis, and pseudo-inverse computation. Applied PCA for dimensionality reduction and data exploration on real-world datasets.
Experience with graph algorithms (Dijkstra’s shortest path, Markov chains, network analysis) and regression methods (least squares, line of best fit with genetic algorithm optimization). Contributed to published research on predicting Long COVID using data mining and classification techniques.