zeedan.

Selected projects.

Where I’ve been.

Research labs, real-world software, and a lot of learning along the way.

  1. May – Jul 2026Dortmund, Germany

    Research Intern · DAAD RISE Fellow

    TU Dortmund

    350 fellows selected from 3,149 applicants

    • Researched LLM-guided formal verification of deep neural networks. Built a Python/LangGraph pipeline that turns natural-language requirements into VNN-LIB specifications for alpha-beta-CROWN and Marabou.
    • Designed human-in-the-loop disambiguation and audited ONNX encodings, catching three soundness-breaking errors before they reached the verifier.
  2. May – Nov 2025Starkville, MS

    Software Engineering Intern

    Taebi Lab · Mississippi State University

    70% faster real-time tracking

    • Developed an iOS app for neonatal cardiovascular monitoring with Swift, SwiftUI, and UIKit, working alongside a clinical team.
    • Accelerated QR and SCG tracking by 70% with Objective-C/OpenCV and unit-tested signal processing. Built the API and validation pipeline with AES-256 encryption, role-based access, and Firebase sync.
  3. Nov 2024 – May 2025Starkville, MS

    Undergraduate Research Assistant

    Aerospace Engineering · Mississippi State University

    1st place · ERDC Autonomous Robotic Systems competition

    • Built a hybrid ML architecture combining Koopman operator theory, GANs, and variational autoencoders, trained on 12-state flight dynamics across 500,000 trajectories.
    • Implemented attention-based graph neural networks in PyTorch for real-time trajectory state prediction.
  4. Jan 2024 – May 2025Starkville, MS

    Full Stack Intern

    Social Science Research Centre · Mississippi State University

    Research infrastructure serving all 82 Mississippi counties

    • Built distributed data-management features for TRAPS and designed API contracts and MongoDB/PostgreSQL schemas. A TypeScript refactor cut map load times by 50%.
    • Fine-tuned a PyTorch transformer for table extraction and added semantic search, accelerating ML inference by 50% and improving retrieval accuracy by 16%.

A little about me.

I’m a Computer Science student at Mississippi State University, interested in the space where machine learning, systems, and useful software meet.

My work has taken me from healthcare apps and research infrastructure in Mississippi to neural-network verification in Germany. I like understanding how things work and making them work better.

Always something new to learn.

My toolkit.

Languages
  • Python
  • C++
  • C
  • Swift
  • Objective-C
  • Java
  • JavaScript
  • TypeScript
  • C#
Apple
  • SwiftUI
  • UIKit
  • Xcode
  • CoreML
  • Combine
  • AVFoundation
  • ARKit
  • CryptoKit
  • CoreMotion
  • Swift Concurrency
ML & verification
  • PyTorch
  • LangGraph
  • ONNX
  • VNN-LIB
  • alpha-beta-CROWN
  • Marabou
  • OpenCV
  • MediaPipe
Backend & tools
  • React
  • Node.js
  • FastAPI
  • REST / WebSockets
  • MongoDB
  • PostgreSQL
  • Firebase
  • Git
  • Linux / Unix