Skilled in Data Analysis and Digital Transformation
Analytical and detail-oriented data science graduate student with 1.5+ years of experience in data analysis, visualization, and machine learning. Skilled in Python, Power BI, and SQL, with a strong track record of developing data-driven solutions, automating workflows, and driving operational efficiency.
Passionate about leveraging advanced technologies like Generative AI and digital twins to transform manufacturing processes and optimize decision-making.
Applied small-world network theories and machine learning to analyze 30 years of trade data, revealing actionable insights.
Evaluated spatial datasets using parallel computing techniques for insights in urban development on the Carnie supercomputer.
Used R and Python to model trade data spanning 30 years, uncovering actionable global trends.
Evaluated machine learning models for earthquake prediction, providing insights into seismic hotspots and risk assessment strategies.
Built a web-based drawing application and automated test cases using Selenium IDE to ensure functionality and performance.
Analyzed recent cyber-attacks using data mining algorithms, uncovering business impacts and risk mitigation strategies.
My research focuses on leveraging advanced data science techniques to solve real-world problems. Below is an interactive visualization from my earthquake dataset analysis project, demonstrating my expertise in geospatial data visualization and machine learning applications.
Link to the Research Paper: Earthquake Data Analysis
Interactive visualization of global earthquake patterns using machine learning models for seismic hotspot identification and risk assessment.
285 Old Westport Rd
Dartmouth, MA, 02747