Malek Swilam

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Incoming Computer Engineering student at George Mason University's Honors College with a passion for machine learning, computer vision, and robotics.

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About

Hey, I'm Malek Swilam, and I'm starting at George Mason University's Honors College for Computer Engineering this fall.

I did ML research at GMU, co-built OCRadar, an AI app that screens for oral cancer with 98% accuracy, and led software development for an FTC robotics team.

Outside of tech, I'm an Eagle Scout, where I built leadership, community service, and a love for the outdoors.

Experience

Jun 2026 – Present Remote
  • Contributing to Yanez Compliance's decentralized AI platform for sanctions screening and fraud detection.
Generative AI Compliance Tech

Engineering Intern

Alarm.com ↗
May 2026 · 1 mo Tysons Corner, VA · On-site
  • Performed hands-on hardware lab work including soldering buck converters and embedded boards, bringing up low-level power circuits and embedded components
  • Assembled RJ45 Ethernet cables and provisioned Raspberry Pi units, building out the physical test automation infrastructure used across the hardware QA team
  • Configured and integrated home security devices (locks, contact/tilt sensors, lighting, cameras, thermostats, doorbells, and Flex I/O) into automated testing workflows across hardware QA cycles
  • Built an internal software tool for lab device management, streamlining device tracking and provisioning for the hardware QA team
Hardware QA Embedded Systems IoT Soldering Raspberry Pi AI Tooling Python

Machine Learning Research Intern

George Mason University — ASSIP ↗
Jun – Sep 2025 · 4 mos Fairfax, VA · Hybrid
  • Built a full ML pipeline (data preprocessing, training, evaluation) for short-term rainfall forecasting, implementing and comparing LSTM, XGBoost, and ensemble models evaluated via MAE, RMSE, and R²
  • Improved rainfall prediction accuracy by 12–15% over individual models by combining LSTM and XGBoost into an ensemble, achieving 96%+ of predictions within ±1 mm of actual
Python PyTorch LSTM XGBoost ML Pipelines
View Abstract ↗
2023 – 2026 · 2 Seasons Vienna, VA
  • Led all robot software development in Java across two varsity seasons; mentored junior programmers in Java, Git, and FTC SDK over summer offseason
  • Built autonomous localization pipeline fusing wheel odometry with IMU for pose estimation; integrated AprilTag detection for field-relative pose correction; implemented motion profiling and trajectory planning via Road Runner
  • Developed a multi-mode vision targeting system using a Limelight camera backed by a finite state machine; implemented a PD controller on angular error for closed-loop real-time turret aiming
  • Designed multi-subsystem PIDF control: turret with adaptive static friction and velocity feedforward; flywheel velocity controller with piecewise-linear distance-regression model for range compensation
  • Implemented a 3-DOF PD controller with field-to-body-frame error projection for pose stabilization during shooting; tuned all PID coefficients
  • Qualified for State Championship both seasons and World Championship one season (ranked 8th seed captain in division)
Java Computer Vision PIDF Control Sensor Fusion Localization & Path Planning Road Runner Git / GitHub
DECODE Season Code ↗

Projects
GitHub Demo

Voice-Controlled Robotics Agent ↗

A voice-controlled robotic manipulation agent built in MuJoCo physics simulation. Natural-language commands are interpreted and executed by a Franka Panda arm in real time. An LLM breaks down commands into ordered sub-goals using chain-of-thought reasoning, detects mid-task failures, and replans autonomously to recover. Audio is handled end-to-end with speech-to-text and text-to-speech APIs. A separate LLM call verifies the live scene against the goal state before reporting success. Robot motion is solved with inverse kinematics via the mink library, and the simulation streams live through a FastAPI WebSocket portal.

Python MuJoCo Voice Control Agentic AI Embodied AI Claude API LLM Planning FastAPI
OCRadar logo
GitHub Visit Site

OCRadar ↗

Cross-platform iOS, Android, and web app for early oral cancer screening. Uses CNN-based computer vision to classify mouth images against thousands of labeled healthy, benign, and malignant samples, achieving 98% accuracy with Azure AI Vision. Featured by WTOP News, Korea Times, and FCPS News.

Python Computer Vision Azure AI Vision Flutter Dart
View All on GitHub

Skills

Languages
Java Python Dart JavaScript HTML / CSS
Frameworks
PyTorch OpenCV XGBoost NumPy Flutter MuJoCo
Tools
Git / GitHub JetBrains IDEs Azure AI VS Code FTC SDK Anthropic API
Focus
Machine Learning Computer Vision Robotics IoT Systems Control Systems

Honors & Awards

⚜️
Eagle Scout Boy Scouts of America · highest rank attainable
Oakton Cougar Robotics
FTC World Championships 8th seed captain in Division · 2025
🎖️
T.R. Cook Award of Excellence in Technology Optimist Club of Greater Vienna · 2025

Education

Incoming Fall 2026

George Mason University ↗

Honors College

B.S. Computer Engineering

Expected May 2030 · Fairfax, VA

Oakton High School ↗

Advanced Studies Diploma

Aug 2022 – Jun 2026 · Vienna, VA

AP Computer Science A · AP Computer Science Principles · Advanced Data Structures & Algorithms · AP Calculus BC · AP Statistics · AP Physics 1 · AP Physics C: Mechanics · AP Physics C: Electricity & Magnetism · STEM Engineering · AP Macroeconomics · AP Microeconomics

Northern Virginia Community College ↗

Non-Degree Seeking · Dual Enrollment

GPA 4.0

Aug 2024 – 2026 · Annandale, VA

Dual Enrollment English 12 · Dual Enrollment Entrepreneurship

Contact

Open to opportunities, projects, or just reaching out.

Say Hello
LinkedIn GitHub