I am a Computer Engineering student passionate about exploring low-level systems utilities, mastering Data Structures & Algorithms (DSA), and contributing to open-source software.

• Languages: C, Java, Python
• Core Focus: Data Structures & Algorithms, Systems Logic, Database Management
• Tools & Ecosystem: Git, GitHub, GCC Compiler, VS Code

I am an aspiring contributor for GirlScript Summer of Code 2026.I aim to focus on:

• Optimized Data Structure and Algorithm implementations (C/Java/Python)
• Algorithmic Optimizations: Improving the time and space complexity of existing code logic and sorting routines.
• Data Structure Implementations: Writing clean, scalable, and idiomatic data structure scripts in C, Java, and Python.
• Edge-Case Debugging: Identifying and fixing critical logical flaws, pointer mismanagements, or memory leaks in core repositories.

(https://github.com/shafinalam07/raspberry-pi-nextcloud).

• What it is: A private cloud storage server built on a Raspberry Pi 3B+ using Docker and Nextcloud — a personal Google Drive alternative with no monthly fees and full data ownership.
• How it works: Turns a Raspberry Pi 3B+ into a fully functional network-accessible cloud server. Runs Nextcloud inside a Docker container on Linux, configured entirely from scratch with SSH remote access, swap memory tuning, and local network setup for multi-device access.

• What it is: A low-level heap memory manager built completely from scratch in pure C.
• How it works: Replaces standard malloc and free using a custom 10KB array and a Singly Linked List. Features first-fit block scanning, block splitting to minimize waste, and automatic neighboring block merging (coalescing) upon freeing space.

• What it is: A functional text data compression tool utilizing greedy frequency tracking.
• How it works: Implements a custom, self-sorting Min-Heaps queue from scratch to build a binary Huffman Tree. It generates unique, variable-length prefix binary codes to significantly reduce text storage space.

• What it is: A validation syntax tracking utility built using stack data structures.
• How it works: Parses and scans text strings dynamically to track, match, and catch structural errors or unmatched brackets inside nested expressions.

• What it is: A fully offline, browser-based assistant for everyday support and high-pressure emergency contexts.
• How it works: Uses WebAssembly (WASM) via llama.cpp and ONNX web backends to run small language models (LLMs) and vision models entirely inside the client browser. Features 100% local data privacy, on-device audio transcription (STT/TTS pipelines), and local OCR document parsing.

• GitHub Profile: github.com/shafinalam07