Connor Mccurley, Phd Email & Phone Number

Philadelphia, PA, US

Miami, Florida, United States

• Develop machine learning approaches for satellite-based hyperspectral data, including: geo-referencing, co-registration, atmospheric correction, target detection, outlier rejection, and more
• Architect and implement MLOps infrastructure for internal use and customer facing deployment using tools like AWS, Docker, and ClearML
• Actively contribute to deployment-ready GitLab code base, keeping in line with company coding and documentation standards
• Implement and rigorously compare current state of the art approaches in HSI
• Deploy algorithms for real-world use through proprietary data pipeline
• Disseminate scientific findings through publications, academic conference presentations, and blog posts

Gainesville, Florida, United States

• Project: Discriminative Feature Learning with Imprecise, Uncertain, and Ambiguous Data
• Defined methods for weakly-supervised semantic segmentation using deep learning
• Developed approaches for model understanding and fusion using weakly-labeled groundtruth
• Preformed rigorous evaluation of methods, comparing to the state-of-the-art
• Applied developments to a variety of remotely-sensed data, including infrared, visual spectrum, RGB, hyperspectral and sonar imagery

• Advised 7 undergraduate and 1 M.S. student on research project
• Contributed to students’ understanding of the academic research process
• Guided students in data annotation, coding of machine learning algorithms,experimental design and result dissemination

• Project: Superpixel Segmentation and Texture Feature Learning for Multi-Aspect Underwater Scene Understanding
• Constructed machine learning algorithms for underwater scene understanding using SONAR
• Investigated approaches for semantic segmentation and multi-scale feature learning using weakly-labeled groundtruth
• Presented findings to Naval officers and civilians from multiple Naval Warfare Research Centers

• Project: Aided Target Recognition using Imprecise and Uncertain Data
• Formulated machine learning methods for target detection in infrared and visual spectrum imagery
• Investigated approaches for target detection and semantic segmentation using weakly-labeled groundtruth
• Communicated findings at various levels of technical expertise through publications and conference presentations
• Packaged and shared models with collaborators through Docker containers

• Project: Multi-sensor Fusion for Buried Object Detection
• Developed algorithms deployed on US Army hand-held metal detectors
• Performed experimental and theoretical studies in explosive hazard detection
• Furthered approaches for soil interference removal and target detection using weakly-labeled groundtruth
• Effectively articulated findings to experienced researchers and U.S. Army representatives

• Course: Graduate Fundamentals of Machine Learning
• Assisted in teaching over 180 students in graduate-level machine learning course
• Provided three lectures on Linear Discriminant Analysis and backpropagation in artificial neural networks
• Wrote custom Python scripts to aid with grading homework and tests
• Managed git repository for class assignment submissionsCourse: Undergraduate Fundamentals of Machine Learning
• Assisted in teaching over 25 students in undergraduate-level machine learning course

Oklahoma City, Oklahoma Area

• Completed over 20 System Protection designs to be implemented in the field
• Experience with protective relaying, breakers, load tap changers, integrated volt-VAR controllers, and other power circuit protection technologies
• Responsible for interpreting and drafting CAD drawings of protection and control schematics
• Aided in design and calculations regarding solar shading, inverters, panels, layout, and land selection for 25 MW solar farm
• Connected SCADA communication network for remote access to protective equipment
• Utilized strong communication skills for final project presentation to executives and co-workers

Oklahoma City, Oklahoma Area

• Practiced and developed workplace safety concepts
• Completed over 15 distribution designs totaling $690,000
• Experience in identification and selection of components to meet desired goals
• Determined distribution designs based on cost, reliability, and maintainability
• Produced work in a timely manner
• Utilized communication and teamwork skills when collaborating with fellow employees

Doctor Of Philosophy - Phd, Electrical Engineering, Machine Learning And Pattern Recognition

Bachelor Of Science In Electrical Engineering, Electrical Engineering And Computer Science, Senior

Activities and Societies: Institute of Electrical and Electronic Engineers, Tau Sigma Honor Society, Tau Beta Pi Engineering Honor.

Electrical Engineering And Computer Science

Activities and Societies: -Sigma Phi Epsilon Fraternity, Institute of Electrical and Electronic Engineers, IEEE Robotics Team, IEEE.