Projects
Below are the projects I have completed. To access and download the source code for each project, please click on the respective project image.
Course Management System (CMS)
Tech Stack: HTML, CSS, PHP, MYSQL
Developed a multi-login Course Management System using PHP, Docker, Jenkins, and Selenium, enabling efficient course and assignment management for admins, teachers, and students. Automated testing and deployment reduced deployment time by 50% and improved system reliability.
WoodCorp O2C Process Mining Celonis Case Study
Tech Stack: Celonis EMS, Excel, PowerPoint
Conducted an in-depth Order-to-Cash (O2C) process mining case study for WoodCorp using Celonis EMS. Analyzed event logs to identify root causes of delivery delays and proposed strategies to improve on-time delivery from 65.6% to 80%, targeting €5M in cost savings. Collaborated on building interactive dashboards and presented insights to stakeholders to drive process efficiency.
Nexamed Scheduler
Tech Stack: VB.NET, MySQL
Developed a Doctor Appointment Scheduling System using VB.NET and MySQL, reducing receptionist workload by 40% and streamlining the booking process. The system featured a user-friendly interface and built-in reporting tools to enhance staff efficiency, improve scheduling accuracy, and support better resource management.
Hospital Management
Tech Stack: Python, MySQL
Developed a Hospital Management System as part of my Class 12 Computer Science project using Python and MySQL. The system efficiently manages key hospital operations including token generation, appointment scheduling, medical records handling, and ambulance booking. Designed to simplify administrative tasks, the project showcases my foundational skills in Python programming, database integration, and system design.
Languages Tested: Python, C++, Java, Go
A benchmarking study evaluating four popular programming languages across key software metrics, including execution time, memory usage, stability under load, and debugging ease. The analysis involved implementing identical tasks — recursive Fibonacci calculation, 100MB CSV I/O operations, 1000×1000 matrix multiplication, and HTTP load testing — under controlled conditions.
Phishing Detection System
(SafeSurfX)
Tech Stack: Python, Scikit-Learn, Pandas, NumPy, Flask , Machine Learning
Developed a machine learning–based Phishing Detection System that identifies malicious URLs using feature extraction and classification algorithms. Built a full train-and-deploy pipeline with real-time URL prediction and an interactive interface, ensuring reliable detection through optimized feature engineering and model tuning.
