Jediah Michael D’Souza

Summary

A Highly Motivated, Enthusiastic and Detail-Oriented Undergraduate Student, eager to gain hands on Experience on Technologies related to Software Development, Cloud Computing, Networking and CyberSecurity. Experienced in building and deploying academic and personal projects using databases, distributed systems, and web technologies. Eager to contribute to internship opportunities by applying theoretical knowledge to real-world scenarios, collaborating in Team environments, and gaining exposure to cutting-edge technologies under expert mentorship.

Skills

• Programming: Java, C/C++, Python
• Web Technologies: HTML, CSS
• Databases: SQL (Microsoft SSMS)
• Tools: VS Code, GitHub, CursorAI, Windsurf, Warp, Eclipse, Jupyter, Packet Tracer
• OS: Windows, Ubuntu (Linux)
• AI Automation Tools/Agents: GitHub Copilot, Replit, bolt.new, Lovable, Emergent, v0(Vercel), PentestGPT
• MS Office Suite

Education

BS Computer Science - IQRA University (Oct 2022 – Present)

Intermediate in Computer Science - St. Patrick’s College, Karachi (2020 – 2022)

Matriculation (Computer Science) - St. Paul’s English High School (2010 – 2020)

Projects

Personal Portfolio Website

• Developed a Simple, Responsive, and Visually Appealing Fresher-Based Personal Portfolio Website using Web Technologies: HTML, CSS.

Cloud-Based Leave Management System

• Built using HTML, CSS, JavaScript with Firebase for authentication and real-time database.
• Enabled employee leave tracking and approval via an intuitive interface.

Sorting and Searching Algorithm Simulator

• Implemented in Java with support for multiple algorithms like Bubble, Merge, Quick Sort, etc.
• Compared algorithm performance metrics in real-time.

University Entrepreneurship Incubation Management System

• Developed in SQL with role-based access, business logic enforcement via procedures/triggers.
• Managed students, mentors, funding rounds, and evaluations.

Traffic Light Flow Simulation System

• Python-based simulation with serial, parallel, and distributed (MPI) models.
• Improved simulation time from ~24s to ~5s using multiprocessing and zone-based distribution.

Get In Touch

I'm always open to discussing new opportunities, collaborations, and innovative projects. Let's connect!