Computer Science undergraduate focused on software engineering, systems, AI, and problem solving. I enjoy building practical applications and exploring how software and computer systems work under the hood.

Currently interested in:

• Software Engineering & Backend Development
• Computer Architecture & Systems
• AI & Optimization
• Databases
• Data Structures & Algorithms

Languages: Python, C, SQL, Java

Web & Backend: HTML, CSS, Flask, REST APIs

Databases: MySQL, SQLite

Developer Tools: Git, GitHub, Linux, VS Code

Core CS: Data Structures & Algorithms, OOP, DBMS, Operating Systems, Computer Networks, Software Engineering, Computer Architecture

Java • JDBC • MySQL • JavaFX

Layered hospital management platform following a Model–DAO–Service architecture.

• Manages patients, doctors, staff, rooms, appointments, billing, and medical records
• Designed a normalized MySQL database with relational constraints
• Uses JDBC PreparedStatement for secure database operations
• Provides both JavaFX dashboard and CLI interfaces
• Shared service layer keeps business logic independent of the UI

View Repository

Node.js • Express.js • SQLite • JavaScript

Software engineering project for continuous system monitoring, anomaly detection, and automated alerting.

• Monitors CPU, memory, disk, and network I/O
• Provides real-time monitoring dashboards
• Uses predictive anomaly detection for resource-breach forecasting
• Implements authentication, role-based access control, rate limiting, and alerts
• Validated with a 61-test Jest automated test suite

View Repository

Python • NumPy • PSO • Tabu Search

Optimization-based AI agent for the OpenAI Lunar Lander environment.

• Implemented a softmax policy over a linear model
• Optimized policy parameters using Particle Swarm Optimization and Tabu Search
• Achieved 87% landing success across 1,000+ simulated episodes
• Built reusable inference logic with input validation and observation clipping

View Repository

C++ • ChampSim • Computer Architecture

Research work conducted under Dr. Arijit Nath at IIIT Guwahati.

Designed a Last-Level Cache replacement policy combining history-based hit prediction with a perceptron-weighted reuse signal.

• Built a 512×16 Hit History Table
• Implemented a 256-entry ghost directory
• Evaluated using ChampSim and SPEC CPU2006 traces
• Achieved up to 8.8 percentage-point LLC hit-rate improvement
• Achieved up to 6.77% IPC improvement over LRU

• Ranked 377 / 3,100+ contributors
• Top 12% of contributors
• Contributed 2,000+ lines of production code
• Merged 15+ pull requests
• Maintained a 90% PR approval rate

• Advanced Data Structures & Algorithms
• Backend Development
• System Design Fundamentals
• Computer Architecture
• AI & Machine Learning

LinkedIn • GitHub

Building software, understanding systems, and continuously learning.