About

Hi, I’m Ronak Fathi, a statistical consultant and educator with a master’s degree in mathematical statistics. I specialize in probability, stochastic modeling, simulation, and applied statistical analysis using R, Python, and SPSS.

Across my work, whether analyzing random recursive trees, forecasting environmental phenomena, or modeling health and behavioral outcomes, I focus on modeling uncertainty, dependence, and variation in complex systems using both theoretical and computational approaches. This unifying theme bridges my theoretical research with applied projects and ensures that insights are both rigorous and actionable.

My applied projects span health, psychology, economics, and environment, with experience in forecasting, risk modeling, and behavioral analytics.

I’m currently exploring interdisciplinary applications of statistical modeling and machine learning, and I’m eager to collaborate on projects where rigorous quantitative methods inform real-world decision-making across domains such as health, social science, and environment.

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Table of Contents

• About
• Projects
  • Health & Psychology
  • Finance & Economics
  • Environmental & Infrastructure
  • Behavioral & Social
  • Consulting & Education
• Certificates
• 📬 Contacts

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Projects

Health & Psychology

• COVID-19 – Predicting Patient Risk Urgency(Python) Built a predictive model to classify patient risk using demographic and symptom data.
• Mental Health Trends During COVID-19(R) Modeled non-linear temporal trends in anxiety and depression using GAMs, mixed models, and multivariate analysis.
• Heart Disease Risk Prediction(R) Applied classification models to predict heart disease risk from patient data.
• Stroke Prediction(R) Developed predictive models for stroke incidence, focusing on interpretability and risk assessment.
• Parkinson's Disease Prediction(R) Used machine learning to predict Parkinson’s onset based on clinical and behavioral features.
• Cognitive Load & Reaction Time(R) Analyzed experimental data on cognitive performance under varying conditions.

Finance & Economics

• Store Sales Forecasting – Time Series Modeling(Python) Forecasted sales using ARIMA/SARIMA models, capturing seasonality and trends for business planning.
• Automatidata – Predicting Customer Tipping Behavior(Python) Modeled tipping patterns to understand consumer behavior and microeconomic decision-making.
  • Automatidata Visualization(Tableau)
• Waze – Predicting High-Risk Churn Segments(Python) Identified user segments likely to churn, supporting market retention strategies.
• Salifort Motors – Job Satisfaction Analysis(Python) Investigated the relationship between employee satisfaction and organizational outcomes, framed as labor economics.

Environmental & Infrastructure

• Lightning Strike Forecasting – Time Series Modeling with SARIMA(Python) Forecasted lightning strike frequency using seasonal ARIMA models and visualized regional patterns.
  • Lightning Strikes in the US(Tableau)
• Seoul Rental Bike Summary(Tableau) Visualized urban transportation patterns and seasonal usage trends.

Behavioral & Social

• TikTok – Identifying Claims vs. Opinions(Python) Classified social media content to distinguish factual claims from opinions, with applications in sentiment analysis and behavioral research.
  • TikTok Visualization(Tableau)

Consulting & Education

• Student Projects Portfolio: A collection of mentoring and consulting work in areas like psychology and behavioral science. Includes longitudinal study analyses, survey modeling, and guided workflows developed with students.
• Statisticians World Tutorials: Code, datasets, and walkthroughs from my YouTube tutorials on R and Python. Topics include statistical modeling, data wrangling, and machine learning fundamentals.

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Certificates

• Machine Learning Specialization – Stanford University
• Google Advanced Data Analytics Professional Certificate

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📬 Contacts

• 🔗 LinkedIn
• 📧 Email
• 🎥 YouTube – Statisticians World
• 🌐 Consulting Website

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