Nicholas Brent Burns - Resume.pdf

Recent Ph.D. graduate of Computer Engineering with experience in machine learning, data science, neural networks, electronics, microcontrollers, and software development. My teaching experience focused on computer/electrical engineering, embedded systems, and electronics. For research, I was the lead graduate student researcher of the SmartCare Project – a multi-discipline health technologies project involving electronics, sensing technologies, embedded programming, networking, data collection, machine learning, neural networks, and data analysis. We created a live-in health monitoring smart home for the elderly to provide 24/7 health and safety analysis for the residents, their family, and doctors. The focus of my research was our custom-built smart floor to extract gait parameters and unique person identifiers using machine learning techniques.

The University of Texas at Arlington

2013 - 2020

Ph.D. in Computer Engineering (BS to PhD)

• Dissertation: Learning Health Information From Floor Sensor Data Within A Pervasive Smart Home Environment
• Direct PDF Link | UTA Library Link
• Supervisors: Dr. Gergely Záruba and Dr. Manfred Huber

The University of Texas at Arlington

2007 - 2013

Bachelor of Science in Computer Engineering

PhD Project Researcher (UT-Arlington)

Aug 2013 - Aug 2020

Developed a novel multi-stage machine learning method to extract foot contact points from a custom-built smart floor to perform Gait Analysis and person identification.

Using this method, discovered comparable results to a high-resolution off-the-shelf walking mat.

Created an automatic calibration algorithm for a floor sensor grid in a dynamic environment.

Established a recursive clustering technique to segment individual footfalls and walking segments.

Contributed to the construction of a sensor-rich health-monitoring apartment for the elderly.

Senior Lecturer Faculty (UT-Arlington)

Aug 2016 - May 2019

Instructed two courses: Electronics for Computer Engineering and Embedded Systems 1.

Guided students in the theory and application of electronics, circuit design, and microcontrollers.

Improved course content to allow more diverse student-specific project choices.

Shifted the courses to a lab-heavy structure to give students more hands-on experience.

Graduate Teaching Assistant and Lab Instructor (UT-Arlington)

Jan 2014 - May 2020

Assisted professors in Electronics for Computer Engineering and Embedded Systems 1.

Provided in-person instruction and assistance for students performing lab work.

Responsible for grading all assignments: homework, labs, projects, and exams.

Undergraduate Research Position (UT-Arlington)

Summer 2012

Developed software and electronics for a semi-autonomous assistive wheelchair for the program Research Experiences for Undergraduates in Assistive Technologies for People with Disabilities.

Undergraduate Research Assistant (UT-Arlington)

Mar 2011 - Mar 2012

Assisted graduate students in labeling training data for an AI-driven sign language project - The Vision Learning Mining Research Lab.

An Automatic Calibration Technique for Force Sensors in a Dynamic Smart Floor Environment

Pending...

Extracting Foot Contact Points and Gait Characteristics from a Low-Resolution Smart Floor Using Convolutional Autoencoders and Hierarchical Clustering

Pending...

Learning Health Information From Floor Sensor Data Within A Pervasive Smart Home Environment

UTA 2020 (Dissertation)

While not a true publication, it is relevant to my other papers here.

Direct PDF Link | UTA Library Link

SmartCare - An Introduction

PerCom 2017

G. Záruba, M. Huber, K. Daniel, N. Burns. SmartCare – An Introduction, In IEEE International Conference on Pervasive Computing and Communication (PerCom 2017), Kona, Big Island, Hawaii, 2017.

Direct PDF Link | IEEE Link | PerCom Conference Link

PESTO: Data Integration for Visualization and Device Control in the SmartCare Project

PerCom 2016

G. Záruba, M. Huber, K. Daniel, P. Sassaman, N. Burns. PESTO: Data Integration for Visualization and Device Control in the SmartCare Project, In IEEE International Conference on Pervasive Computing and Communication (PerCom 2016), Sydney, Australia, 2016.

Direct PDF Link | IEEE Link | PerCom Conference Link