I'm a tech-savvy graduate student pursuing an MS in Computer and Information Sciences at SUNY Albany, equipped with expertise in Java, Python, and SQL. With hands-on experience , I've streamlined software processes and pioneered AI algorithms. Certified in Google Cloud and AWS, I thrive in collaborative environments, driven by a passion for innovation and continuous learning.
0 + Projects completed
Project 1: LA (louisiana) MEDS
Project 2: Wells Fargo
Course work: OS , Advanced Computer Architecture , Software Engineering , Advanced Programming Concepts.
Course work: C, AI, Data Structures and Algorithms, DBMS, ML, Distributed Systems, Soft Computing, Deep Learning.
Below are the sample Data Analytics projects on SQL, Python, Power BI & ML.
Pioneered the development of a responsive website using a tech stack comprising SQL, Express.js, React.js, and Node.js.
Modeled an advanced driver drowsiness detection system, achieving a 20% increase in accuracy through innovative motion detection techniques. Implemented webcam-based alarms, enhancing real-time responsiveness by 15%.
Developed an NLP model using Python (NLTK, Scikit-learn) to analyze 10,000+ customer reviews, identifying key sentiment drivers. Improved feedback classification accuracy by 15%, refining marketing strategies and product improvements. Created Power BI dashboards to visualize sentiment trends, enhancing stakeholder decision-making.
Engineered an innovative system using OpenCV libraries, capturing input from various external devices like webcams. Conducted in-depth analysis of object motions, achieving a 20% improvement in accuracy, and optimizing data storage by saving results in CSV format for efficient retrieval and interpretation.
This project optimized retail inventory by developing a Python-based machine learning model for forecasting demand, reducing stockouts by 25%. A real-time SQL pipeline and Tableau dashboard were also created to monitor stock levels and sales, enhancing data-driven decision-making.
Created a Power BI dashboard to track and forecast customer sales trends, using SQL for data queries. Applied time series forecasting in Python (Scikit-learn), improving sales forecast accuracy by 20%. Visualized key metrics like revenue growth, sales by region, and customer segmentation for data-driven decisions.
Used the Springboot framework to implement the e-voting website
Constructed a sturdy SQL database that guarantees the careful maintenance of large client databases.
Below are the details to reach out to me!
Albany, Newyork