Internship @ ONGC

Summer Intern | Database Group (WOB)

Developed an ML-based Network Intrusion Detection System (NIDS) to address the limitations of static signature-based security. Engineered a data pipeline processing the UNSW-NB15 dataset (2M+ records) and optimized detection models (RandomForest, XGBoost) using SMOTE to handle class imbalance. Analyzed zero-day attack patterns under the guidance of the Database Programming division.

MendikotZero: AlphaZero RL Agent

Engineered an autonomous AI agent for the Indian card game 'Mendikot' using Deep Reinforcement Learning. Implemented the AlphaZero architecture from scratch, utilizing Monte Carlo Tree Search (MCTS) guided by a Dual-Head Neural Network. The agent was trained via self-play without human data, evolving from random moves to advanced strategic planning.

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CS50 Introduction to Cybersecurity: Final Project

Anatomy of a Critical Failure : CVE-2025-61882

CS50 Cybersecurity Capstone: Conducted a technical forensic analysis of a critical (CVSS 9.8) Path Traversal vulnerability in Oracle Agile PLM. Deconstructed the input validation failure and proposed defense-in-depth remediation strategies including Path Canonicalization and Least Privilege architecture.

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Network Intrusion Detection System

Developed a high-performance NIDS using machine learning to detect novel and zero-day attacks. Executed a full data science workflow on the UNSW-NB15 dataset. The final Random Forest model (with SMOTE) achieved an excellent balance between high detection rates and low false positives.

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