🔭 B.Tech ECE-AI Student at IGDTUW
🌱 Currently learning AI/ML, Data Structure and Core CS. 👯 Passionate about hackathons, building projects & solving real-world problems
💬 Ask me about Web Development, ML Tools & Frontend Projects
⚡ Fun fact: I love turning ideas into creative web applications

• Engineered an end-to-end forensic pipeline extracting 6 behavioural signals across social networks using TF-IDF trait weighting and top-$k$ cosine similarity graphs.
• Formulated a degree-preserving permutation null model ($\tau_{\text{floor}}$) to eliminate false-positive organic clusters and Louvain community detection to isolate coordinated campaigns.
• Benchmarked across 142k+ real-world posts with an interactive FastAPI backend and Cytoscape.js network visualizer.
• Tech Stack: Python, FastAPI, Cytoscape.js, NetworkX, TF-IDF, Graph Analytics

• Developed a pure-Python, zero-dependency Apache Parquet format parser with Thrift compact-protocol metadata decoding.
• Implemented decoding primitives for plain variable-length byte arrays, dictionary encoding, and bit-packed run-length encoding (RLE).
• Built custom Snappy block decompression and predicate pushdown filters for fast in-memory columnar query execution.
• Tech Stack: Python, Binary Serialization, Thrift, Snappy Compression, Columnar Storage

• Built an end-to-end machine learning pipeline to predict customer churn.
• Performed data preprocessing, feature engineering, customer segmentation (K-Means), and compared models including Random Forest, XGBoost, LightGBM and CatBoost.
• Tech Stack: Python, Pandas, NumPy, Scikit-learn, XGBoost, CatBoost, LightGBM

• Developed an AI-powered quiz generation application using transformer-based models.
• Generated MCQs and short-answer questions from textual content using Hugging Face models.
• Tech Stack: Python, Hugging Face, Transformers

• Built a Retrieval-Augmented Generation (RAG) application for semantic document retrieval.
• Explored embeddings, retrieval pipelines, and LLM-based question answering using Streamlit.
• Tech Stack: Python, Streamlit, RAG

• Contributed to an agriculture-focused platform designed to support farmers through digital solutions.
• Worked on frontend development and project integration.
• Tech Stack: HTML, CSS, JavaScript

• Developed a responsive YouTube-inspired web interface to strengthen frontend development skills.
• Implemented reusable layouts and responsive design principles.
• Tech Stack: HTML, CSS, JavaScript

🏅 Reliance Foundation Scholarship Recipient

🥈 Top 20 Teams (2500+ Teams) Entrepreneurship Hackathon – IIT Guwahati

🥉 Top 100 Teams (1400+ Teams) CodeX 2.0 National Hackathon

🎖 Gargi Puraskar Awarded for academic excellence