Affan Ahmed

Cyber Applied Research Scientist at Lockheed Martin

Washington DC-Baltimore Area

About

Experience

  • Lockheed Martin (Full-time · 3 yrs 6 mos)
    • Cyber Applied Research Scientist
      Jun 2023 - Jun 2025 · 2 yrs 1 mo

    • Associate Cyber Applied Research Scientist
      Jan 2022 - Jun 2023 · 1 yr 6 mos

  • George Mason University (Fairfax, Virginia)
    • Undergraduate Teaching Assistant
      Jan 2019 - Dec 2021 · 3 yrs

      • Assist 700+ Undergraduate students with basic programming techniques through online forums and in-person lab sessions for Python, Java, and C courses • Provide technical support for lab setups and attend weekly meetings with professors to outline goals. • Develop project and testing files, hold weekly office hours, and maintain electronic discussion boards.

    • Contracted Software Engineer
      Feb 2020 - Jan 2021 · 1 yr

      • Developed a software application for the Department of Homeland Security to process terabytes of digital evidence data • Created a RESTful Python API to process and query results

  • Software Engineer/Research Scientist Intern at Lockheed Martin
    May 2021 - Aug 2021 · 4 mos

  • Software Engineer/ML Intern - Surface Transportation Division at Noblis
    Oct 2019 - Aug 2020 · 11 mos

    • Worked on two different Noblis Sponsored Research (NSR) projects. • Developing Supervised Machine Learning Models using Python, Pandas, Numpy, Scikit-Learn to predict traffic flows ahead of time. • Developing Unsupervised ML Models for intrusion detection in autonomous vehicles. Experienced in the developmental pipeline for Machine Learning including Data Preprocessing & Preparation, Model Training and Hyperparameter tuning.

  • Software Engineering Intern - Machine Learning and Cyber Defense Analytics at Noblis
    May 2019 - Aug 2019 · 4 mos

    • Developed a RESTful web API in Python using Falcon to safely and efficiently capture images of malicious websites, reducing capture time by 90%. • Trained a machine learning classification model with scikit-learn that detects malicious URLs at a 93% success rate. • Successfully integrated API into Docker container and deployed onto client servers to be used as a micro-service by all employees. • Presented project to Noblis’ executive board detailing how the application integrated various company intelligence projects and enhanced their cyber analytics mission areas.