Jordan Decker

I have a strong foundation in Criminal Justice from my college studies, where I gained valuable insights into the legal and procedural aspects of the field. Additionally, my background in Robotics and Computer Programming has equipped me with a solid understanding of advanced technologies and their applications. This combination of skills enables me to approach challenges in Criminal Justice with a unique perspective, leveraging both my analytical abilities and technical expertise with the new development of Computer engineering such as AI.

• Google Cyber Security Certification
• Object Oriented Programming in Java Specialization Certification (Duke University and University of California San Diego)
• Coding for Everyone: C and C++ Specialization (University of California, Santa Cruz)
• Astronomy: Exploring Time and Space (University of Arizona)
• IBM Full Stack Software Developer Professional Certificate

Project Title: Arduino-Powered EEG Machine

Description: Created an EEG machine using Arduino, capable of reading brainwaves to determine a person's level of attention, emotional state, and potential indicators of depression. The project utilized a NeuroSky brand control board from a Mindflex EEG headset, making it more affordable and easier to understand compared to traditional EEG machines.

Key Contributions:

• Developed a cost-effective alternative to traditional EEG machines using Arduino.
• Implemented hardware modifications to the Mindflex EEG headset to enable data transmission to Arduino.
• Utilized Arduino Brain library to collect and process EEG data.
• Integrated the EEG machine with Processing software to visualize real-time brainwave data.

Skills Utilized:

• Arduino programming
• Soldering and hardware modification
• Data processing and visualization using Arduino and Processing

This project demonstrates a strong understanding of robotics and programming, as well as innovative thinking in creating a practical and accessible device for monitoring brain activity.

Project Title: Raspberry Pi-based Miniature Observatory (Pi-lomar)

Description: Developed a miniature observatory using Raspberry Pi technology, including a Raspberry Pi computer for control, a Raspberry Pi RP2040 microcontroller for movement control, and the Raspberry Pi Hi Quality camera as the telescope. The system operates in 'headless' mode, enabling remote operation over a home network. Users can select targets from a database, and Pi-lomar will locate, track, and photograph the targets, allowing for detailed image stacking.

Key Contributions:

• Designed and implemented a compact observatory system using Raspberry Pi technology.
• Developed software for target selection, tracking, and image capture.
• Integrated stepper motors, microcontrollers, and electronics for precise movement control.
• Utilized CAD development for mechanical components, including the observatory dome.

Skills Utilized:

• Raspberry Pi programming
• Electronics and microcontroller programming (RP2040)
• 3D printing and mechanical design (CAD)
• Astrophotography and telescope operation

Note: The project serves as an educational tool for understanding telescope functionality and is suitable for further development and improvement. Operating software may require adjustments for use in the Southern Hemisphere. Safety precautions are advised for outdoor use.

Upcoming Projects:

Science App

NASA Data Science Projects

AI development for Personal Works