Work Experience
Software Engineer Intern
Apple Inc.
Jul 2023 — Nov 2023 (Career Experience)
- Built and updated a secure authentication workflow using Python, Requests, and REST APIs for 2,000+ internal users.
- Developed a modern internal documentation platform replacing legacy Atlassian Confluence for 1,000+ developers.
- Collaborated with engineers using Git/GitHub to deliver solutions and present architecture to SWE leadership.
Applied Scientist
NASA Langley Research Center
Jun 2021 — Jun 2021 (NASA Summer Academy)
- Collaborated with 12+ scholars to determine the mission goals and objectives in accordance with NASA’s decadal survey.
- Designed an Earth observing satellite mission and presented to 20+ NASA scientists, engineers, and planetary experts.
- Documented the assigned portion of the research proposal, leading to acceptance in the first attempt from the headquarter.
Projects
DermaLens - iOS App
DermaLens is an AI-powered skin analysis platform that analyzes facial photos to evaluate key skin indicators and create personalized skincare routines, while tracking measurable progress over time with intelligent insights and routine adjustments, drawing from the user's latest scan, active routine, and stated concerns, without ever diagnosing or prescribing. The platform was researched, designed, implemented, tested, and delivered within 36 hours by a team of four, including Mohammed Abdur Rahman, John Lizama, Aahil Shaik, and Terina Ishaqzai.
Puma CPU Scheduler
Implemented a CPU scheduler in C using singly linked lists and bitwise state encoding. Designed multi-level priority queues with aging-based starvation prevention, process promotion, selection, and termination handling. Ensured memory correctness with Valgrind and validated scheduling behavior via StrawHat and unit tests. Test Coverages: NULL parameter handling, Edge cases (empty queues, boundaries), Priority ordering, State transitions, Memory management, FIFO ordering within priority levels, Starvation prevention.
Binary/AVL Search Tree Simulator
Java-based academic project that implements a recursive Binary Search Tree (BST) and extends it into an AVL self-balancing tree to maintain efficient performance during insertions and lookups. The system recursively processes text input to count the frequency of all characters, including letters, digits, punctuation, and whitespace, and dynamically balances the tree using rotation algorithms. In addition to its AVL operations, the simulator supports both depth-first search (DFS) through recursive in-order traversal and breadth-first search (BFS) through a custom level-order iterator for exploring the tree structure.
Credentials
Bachelor of Science in Computer Science
George Mason University
Graduation: Dec 2027
- Relevant Courses: Object-Oriented Programming, Data Structures, Software Engineering, Systems Programming
Certificate in Software Engineering & LLM
CodePath
Sep 2025 — Present
- Relevant Courses: Intro to iOS Development, Foundations of AI Engineering, Intermediate Technical Interview Prep