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Data Science and Mathematical Modelling
Data Science and Mathematical Modelling
Welcome to my website!
Welcome to my website!
I specialize in synthesizing data from various domains to reveal actionable insights, demonstrating my proficiency in leveraging Data Science and ML across multidisciplinary research. With a versatile experience spanning different industries, I’m committed to crafting cutting-edge solutions as a Data Scientist and Machine Learning Engineer.
I specialize in synthesizing data from various domains to reveal actionable insights, demonstrating my proficiency in leveraging Data Science and ML across multidisciplinary research. With a versatile experience spanning different industries, I’m committed to crafting cutting-edge solutions as a Data Scientist and Machine Learning Engineer.
Under the mentorship of Prof. Caroline Colijn within the MAGPIE group, I explored the interdisciplinary blend of Applied Mathematics, and Data Science, focusing on their potent applications in biology, evolution, epidemiology, and genomics. This work allowed me to tackle complex problems, offering valuable insights and innovative solutions with significant implications for public health strategies.
Under the mentorship of Prof. Caroline Colijn within the MAGPIE group, I explored the interdisciplinary blend of Applied Mathematics, and Data Science, focusing on their potent applications in biology, evolution, epidemiology, and genomics. This work allowed me to tackle complex problems, offering valuable insights and innovative solutions with significant implications for public health strategies.
PhD Successfully Defended on December 16, 2024
Title: "Genomic Epidemiology of Infectious Diseases"
Research Objectives and Methods
Research Objectives and Methods
Early Prediction of TB Transmission Clusters in British Columbia:
Objective: Identify high-risk individuals and clusters.
Method: Machine Learning-Based Classification Models.
Potential TB Cases Preventable by Predictive Models:
Objective: Estimate the impact of the predictive model on public health.
Method: Statistical Simulation.
Improving Transmission Reconstruction in TransPhylo:
Objective: Enhance accuracy with time-dependent sampling.
Method: Bayesian Inference.
Addressing Public Health Challenges (Published in Nature):
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