Welcome!

About Me

I am a data-driven professional with a Ph.D. in Fiber & Polymer Science and extensive experience in data analysis, predictive modeling, and machine learning. My research background has equipped me with a strong foundation in deriving actionable insights from complex data sets, while my recent work in data science has focused on applying advanced analytics to solve real-world business problems.

Throughout my career, I have worked on interdisciplinary projects, collaborating with academic and industry partners to drive innovation. My skills in Python, SQL, and data visualization tools (Tableau, Matplotlib) have allowed me to tackle various challenges, from nanoparticle modeling to market trend forecasting.

Research Focus

My research primarily revolves around:

• Predictive Modeling: Leveraging machine learning techniques such as Random Forest and Gradient Boosting to predict complex behaviors and optimize systems.
• Data Analysis & Insights: Conducting trend analysis and business intelligence to provide actionable insights for decision-making.
• Interdisciplinary Collaboration: Partnering with universities and industries to apply data-driven solutions to diverse problems, from smart textiles to sustainable materials.

Bio

I hold a Ph.D. from North Carolina State University, where I conducted cutting-edge research in material science and led data-driven projects. Recently, I completed a diploma in Data Science from BrainStation, where I honed my skills in machine learning, focusing on predictive analytics and trend forecasting. I am passionate about solving complex problems through data and am eager to continue applying my expertise to new challenges in the data science field.