About Matthew

Matthew is a self-driven and results-oriented individual with a passion for data science and applying data science techniques to solve complex problems in chemistry. His academic background includes a B.Sc. in Chemistry focused on computational chemistry research, and he is currently pursuing a Master's degree in Data Science and Analytics.

Beyond academics, his dedication to music is evident in his 10+ years of experience playing the cello. This experience has instilled in him a deep appreciation for precision and perseverance. An individual with a strong inquisitiveness, he thrives on challenges and enjoys delving into research projects. He cultivates a collaborative spirit by actively building strong connections with colleagues and collaborators, fostering a positive and productive work environment.

Projects

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Investigation into Breast Cancer Genes

This study analyzed BRCA2 gene variants using logistic regression, LDA, QDA, and regression tree models to classify their impacts as benign or damaging. Data from gnomAD and ClinVar provided insights into genetic, population, and in silico predictors, with logistic regression emerging as the most accurate model. While limitations remain, this research offers valuable understanding of the factors influencing BRCA2 variant pathogenicity and lays the groundwork for future genetic studies.

Energy Trends: Financing, Production & Renewables

This analysis examines global trends in renewable energy using data on capacity, production, investment, and utilization. It reveals growth in renewable energy capacity worldwide, with countries like China leading in total capacity and Iceland in per capita capacity. The analysis also finds a moderate correlation between investment and capacity growth, suggesting that increased investment is driving renewable energy development.

Organohalide Nucleophilic Substitution Transition State Analysis with Hydroxide Anion

This study used GAMESS software to find the high-energy intermediate state (transition state) in SN2 reactions of haloethanes and hydroxide. MP2 theory with a small basis set efficiently located the transition state, while a different method (DFT) was less effective. For heavier halogens like iodine, the method faced challenges, suggesting basis set size is crucial for accurate transition state calculations.

Unveiling Hidden Patterns: A PCA and Clustering Analysis of Supermarket Data

This project focused on using data analysis techniques to understand decluttering patterns and preferences among clients. Through this research, I was able to develop personalized decluttering strategies based on data insights. 

Predicting Walmart Sales Using Linear Regression: A Data-Driven Approach

This study built a multiple linear regression model to predict Walmart sales using factors like temperature and holidays. They analyzed data on stores, sales, and economic indicators, then checked the model's assumptions and incorporated interaction terms for a more nuanced picture. Despite limitations, the research offers insights into sales-influencing factors at these Walmart locations.

Unveiling Public Opinion: A multifaceted Analysis of YouTube Comments

This project was focused on using data analysis techniques to understand decluttering patterns and preferences among clients. Through this research, I was able to develop personalized decluttering strategies based on data insights. 

See All Projetcs

Contact Me

matthewhaddad1234@gmail.com

+1 (587) 896-2562

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Blog

Decade of Clarity: A Ten-Year Review of Calgary’s Water Quality
23 Jul 2024
Calgary Water Review