Marcus Thoreson Email & Phone Number

Richmond, Virginia, United States

Richmond, Virginia, United States

Richmond, Virginia, United States

Machine Learning Specialization

- Conducted research on advanced manufacturing techniques involving computer vision.- Developed, deployed, and evaluated process-study and defect-detection software applications. - Enhanced manufacturing methods, reduced waste, and improved processes.

Fredericksburg, Virginia

- Lead Controls Engineer for project to bid on U.S. Army Squad Multipurpose Equipment Transport (SMET) program.- Responsible for designing and developing Vehicle Control Unit (VCU) software (C++). The VCU observes operator input and system state in order to maintain desired speed/heading. VCU also manages operation of primary battery and onboard diesel generator.- Utilized VCU RTOS to improve vehicle performance.- Provided advanced technical support for delivered units.

+ Master’s Thesis, “A Computer Vision Tool for Horticultural Research”- Developed software to collect visual plant data, apply image processes, and measure plant characteristics.- Enabled researchers to efficiently categorize genotypes and breed more resilient and fruitful plants.- Wrote software in C++, using OpenCV modules for edge detection, image segmentation, and machine learning.- Advanced stereo-camera rig prototype that collected visual and stereo images.+ Vegetation Detection Research- Explored techniques for detecting dead vegetation using hyperspectral data; interpreted common hyperspectral data image formats.- Investigated several spectral indices common to geospatial imaging used for detection purposes.- Contributed to the design of a vision platform for an autonomous vehicle.+ Mobile Hybrid Power Source Research- Supported the development of a hybrid power system, engineered to reduce fuel consumption and improve logistics for U.S. Marine Corp vehicles.- Developed embedded safety system to monitor DC/DC converter temperatures and system output power.- Explored control techniques for multiple power sources on a remote hybrid power system.+ Advisor, Autonomous Base Platform for Agricultural Operation- Advised and guided sub-teams while managing team resources and schedules.

Conducted static/fatigue testing on fiber optic strain gauges (FOSG). Designed, constructed demonstrations of FOSG applications for potential customers. Became experienced in MTS load frame operation, experimental design, sensitivity analysis.

Master Of Science - Ms, Computer Science, Gpa: 3.66

Specialization: Machine Learning Coursework of note includes: - Machine Learning - Reinforcement Learning - Deep Learning - Computer Vision

Master Of Science (Ms), Mechanical Engineering, Gpa: 3.47

Thesis Title: "A Computer Vision Tool for Horticultural Research" Graduate Research Assistantship: August 2013-May 2016 -Vegetation.

Bachelor Of Science (Bs), Mechanical Engineering, Gpa: 3.48

Coursework of note included Mechatronics, Advanced Instrumentation, and Digital Signals Processing. Recipient of Edward H. Cahill Memorial.