Marcus Schulze

An accomplished engineer offering proven success in the design and testing of new products across a range of technologies and applications. Collaborate effectively with colleagues, mentors, and key stakeholders on the development of innovative solutions that enhance product features and functionality. Excel in communicating and presenting on product use in various scenarios.

Presenter for CITS2025 at Texas State University (2025-07 – 2025-07)

Presented research paper on image restoration techniques at the CITS 2025 conference for publication.

• Presented paper IMAGE RESTORATION WITH VARIATIONAL DYNAMIC MEMORY NET, U-NET AND LNNS at CITS 2025 for publication

TexPREP Instructor at Delmar College (2025-01 – Present)

Instructing students in a 7-week program through their labs and presentations.

• Instructed students during their 7week program through their labs and presentations

Game Development Quality Assurance Specialist at Freelance Client (2023-01 – 2024-12)

Assisted in testing functionality and development of a third-person shooter game in Unreal Engine.

• Assisted in testing functionality and running a third-person shooter game being developed in Unreal Engine

Graduate Student at Texas State University (2019-01 – 2024-12)

Completed Master's degree in Electrical Engineering with advanced coursework and thesis preparation.

• Completed classes for a Master's degree in Electrical Engineering, including Computer Architecture & Design, Antenna Engineering, Power Electronics, Electrical Properties of Materials, Electronic Motor Drives, and Digital Signal Processing
• Prepared thesis for publication titled Image Restoration with Variational Dynamic Memory Net, U-Net, and LNNs

AI Researcher at VizDoom (2017-01 – 2018-12)

Designed and developed new methods for deep reinforcement learning and conducted competitive testing of alternative DRL methods.

• Designed and developed a new method for deep reinforcement learning (DRL), including performing competitive testing of alternative DRL methods in VizDoom, an innovative 3D research platform
• Developed the DRL method for use in advancing general artificial intelligence (AI) research as well as autonomous search-and-rescue vehicles and supplemental guide and transport machines for disabled individuals
• Contributed to a paper published to the arXiv subject class cs.AI (Computer Science, Artificial Intelligence) and presented at the Intelligent Systems Conference (IntelliSys) in 2018

Entrepreneur Researcher at PVBATT (2016-01 – 2017-12)

Developed a low-cost solar charger prototype with microcontroller integration.

• Developed a low-cost solar charger that offered ease of use and storage
• Utilized an msp430 microcontroller for prototyping with various converter models

Capstone Project & Full-Time Student at Texas A&M University (2014-01 – 2015-12)

Completed capstone project on a Deployable Smart Antenna Fence as part of a four-member team.

• Served as part of a four-member team, completing a Deployable Smart Antenna Fence as a Capstone Project
• Managed power systems for a project dedicated to creating a wireless detection system using spherically inverted F antennas; leveraged solar cells to extend the functionality of antennas between charges

Wireless Communications Researcher at Texas A&M University (2014-01 – 2014-12)

Contributed to development and testing of antenna arrays under faculty supervision.

• Contributed to the development and testing of a randomized 3-D monopole antenna array
• Worked under Professor Huff, soldering antennas and acquiring field patterns in the anechoic chamber

MS in Electrical Engineering – Texas State University (2019-01 – 2024-12)

BS in Electrical Engineering – Texas A&M University (2011-01 – 2015-05)