DATA ANALYST | GEOSPATIAL DATA SCIENTIST | NETWORK ANALYSIS SPECIALIST | PUBLISHED RESEARCHER
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.
Modeled global supply chains as geospatially embedded small-world networks, integrating network science and spatial analysis. Key findings: pronounced small-world structure, strong regional clustering, and asymmetric resilience under targeted disruptions. Manuscript and code repository will be linked after submission.
Applied clustering algorithms and time-series forecasting to 30+ years of earthquake data, achieving 85% accuracy in high-risk zone identification across 100+ geographic regions.
Earthquake Data Heatmap 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