👋 Hello, I'm
Passionate about building scalable applications and solving real-world problems.
I'm a Computer Science & Engineering (Data Science) student at Techno Main Salt Lake (2022–2026), with a CGPA of 7.90. I have strong foundations in Java, Python, and MySQL, and I'm deeply passionate about building scalable, real-world applications.
My journey spans machine learning, data analytics, and full-stack web development. I've completed internships at Infotact Solutions (Data Analytics) and EDUNET–Microsoft Foundation (AI & ML), gaining hands-on experience in data pipelines and ML model building.
I believe in writing clean, maintainable code and continuously learning new technologies. Whether it's building an e-commerce platform, a deforestation monitoring system, or a donation web app — I bring curiosity, discipline, and a problem-solving mindset to every project.
Represented school at district-level cricket (U-14 & U-17), secured WBJEE Rank 16,235 among 1,00,000+ candidates. Fluent in English, Hindi, and Bengali.
Infotact Solutions
Completed a 2-month internship in Data Analytics. Gained hands-on experience through projects involving data collection, cleaning, analysis, and interpretation, showcasing strong problem-solving abilities.
EDUNET – Microsoft Foundation (AICTE)
Successfully completed a 4-week internship on Foundations of Artificial Intelligence & Machine Learning — a Microsoft initiative implemented by Edunet Foundation in collaboration with AICTE.
Techno Main Salt Lake
2022 – 2026 | CGPA: 7.90
Howrah Vivekananda Institution
2022 | Percentage: 80.2%
Howrah Vivekananda Institution
2020 | Percentage: 86.85%
Full-featured e-commerce platform for pet products with 12 pages, dynamic product loading from MongoDB, real-time cart, user authentication, search & filter, and complete checkout flow.
Modern web platform connecting donors with meaningful causes. Browse campaigns, donate easily, and track contributions through a clean, responsive interface. Deployed on Vercel.
Web app where students upload, categorize, search, and download study notes. Features user auth, file uploads (PDF, DOCX, PPT), keyword search, download counter, and responsive UI.
Flask + ML web app for monitoring deforestation using satellite imagery. Detects forest loss with TensorFlow models, handles raster data with Rasterio, and visualizes trends via an interactive dashboard.
ML model using Random Forest to predict weekly Walmart store sales based on historical and economic data. Includes data preprocessing, feature engineering, and model evaluation.
Segments mall customers into 5 distinct groups using K-Means Clustering based on annual income and spending score. Provides actionable insights for targeted marketing strategies.
ML model to predict student academic performance based on various factors. Helps educators identify at-risk students early and take proactive measures to improve learning outcomes.
Infosys Springboard
Infosys Springboard
Among 1,00,000+ candidates
U-14 & U-17 Tournaments
Feel free to reach out for collaborations, opportunities, or just a friendly chat.