Christopher Prashad | Public Health | Best Researcher Award

Dr. Christopher Prashad | Public Health | Best Researcher Award

York University, Canada

Author Profile πŸ“š

Orcid

πŸ” Summary

Dr. Christopher Prashad is a PhD candidate in Mathematics and Statistics, specializing in Data Science for Public Health at York University. With a strong foundation in advanced quantitative research, including time series analysis, machine learning, stochastic simulation, and probabilistic programming, Dr. Prashad excels in transforming complex data into actionable insights. He has a proven track record of collaborating with academic and industry teams, effectively communicating technical concepts, and is eager to apply his skills in Data Science to drive meaningful decision-making.

πŸŽ“ Education

Dr. Prashad is currently pursuing his PhD in Mathematics and Statistics – Data Science for Public Health at York University (expected June 2025). He is also completing a MicroMasters in Finance from MIT Sloan School of Management (expected January 2025). He holds a Master’s degree in Mathematics and Statistics from York University and a Bachelor of Science in Mathematics and Chemistry from the University of Toronto.

πŸ’Ό Professional Experience

Dr. Prashad has worked as a Mathematics for Public Health Researcher at York University–Sanofi Pasteur (2022–2024), where he collaborated with pharmaceutical companies and public health organizations to drive evidence-based policies and modeling initiatives. Prior to this, he worked as a Statistician at Western University (2014–2019), conducting longitudinal studies to assess the impact of STEM education programs. He has also served as a Course Director for Statistical Methods in Health Studies at York University (2018–2019), delivering lectures and tutorials while fostering student engagement in applied statistics.

πŸ“š Academic Projects & Presentations

Dr. Prashad has contributed to several notable academic projects, such as Multiperiod Forecasting of Epidemic Prevalence using machine learning to predict the spread of flu-like illnesses, and Stochastic Threshold Analysis for SIRS Model, where he applied advanced mathematical techniques to epidemic modeling. He also analyzed Indexed GIC Investment Products using stochastic volatility models, presenting his findings to industry leaders in finance.

πŸ’» Technical Skills

Dr. Prashad is proficient in a wide range of software and analytical tools, including Python, R, MATLAB, SQL, SPSS, and C. He specializes in Time Series Analysis, Stochastic Simulation, Machine Learning, Multivariate Statistics, and Probabilistic Programming, with expertise in Bayesian Methods, Optimization, and Data Visualization.

πŸ‘©β€πŸ« Teaching Experience

As a Course Director at York University, Dr. Prashad designed and delivered lectures on statistical methods in health studies, supported diverse student learning needs, and contributed to collaborative course design and student development.

πŸ”¬ Research Interests

Dr. Prashad’s research interests lie at the intersection of data-driven public health modeling, machine learning in healthcare, and mathematical epidemiology, with a particular focus on applying quantitative analysis to solve public health challenges.

 

πŸ“– Top Noted Publications

Stochastic Threshold Analysis for Mean-Reverting SIRS Model
    • Authors: Dr. Christopher Prashad (and collaborators)
    • Journal: Journal of Theoretical Biology
    • Year: 2024
Problems and Solutions in Modern Finance, Financial Accounting, Mathematical Methods for Quantitative Finance, and Derivatives Markets
    • Authors: Dr. Christopher Prashad (and collaborators)
    • Journal: Independent publication
    • Year: 2024
Assessing the Impact of Community Mobility on COVID-19 Dynamics
    • Authors: Dr. Christopher Prashad (and collaborators)
    • Journal: PLOS Computational Biology
    • Year: 2024
State-Space Modelling for Infectious Disease Surveillance Data: Stochastic Simulation Techniques and Structural Change Detection
    • Authors: Dr. Christopher Prashad (and collaborators)
    • Journal: Journal of Infectious Disease Modelling, Primer Articles
    • Year: 2024
State-Space Modelling for Infectious Disease Surveillance Data: Dynamic Regression and Covariance Analysis
    • Authors: Dr. Christopher Prashad (and collaborators)
    • Journal: Journal of Infectious Disease Modelling, Primer Articles
    • Year: 2024