Andrew Cragg

About Me

I am an Electrical Engineer with a primary focus on Software Defined Radios. My 3 years of industry experience have exposed me to a fast-paced research and development environment where I have developed digital signal processing tools to solve problems that are becoming incredibly important as the wireless spectrum becomes more crowded and inexpensive software radios are becoming common.

Through my MSECE course work, I am thoroughly developing my knowledge of wireless communication systems and channels as well as the digital signal processing techniques needed to work on modern communications protocols and problems. This includes hardware DSP design for embedded devices such as FPGA's for high throughput and parallel systems. I am also exploring emerging areas such as Machine Learning through my personal research and special topics courses.

In my own time, I am an avid hiker/backpacker and traveller. I also enjoy playing music which is where my original interest in signal processing came from.

U.S. Citizen

Experience

LGS Labs

Electrical Engineer

Working with in the Internal Research and Development team on next generation cellular base station signal processing methods.

Georgia Tech Research Institute

CIPHER Lab Graduate Research Assistant

Working with Software Defined Radio's to reverse engineer embedded radios and develop new signal processing capabilities for existing systems. Designed a polyphase channelizer for efficient wideband spectral monitoring and demodulation using C++ and GNU Radio.

LGS Innovations

Digital Signal Processing Intern

Worked on internal research and development projects primarily related to SDR's and digital signal processing

Designed a timing recovery and QAM demodulator for the REDHAWK SDR platform using C++
Worked closley with senior engineers on the MITRE Army Signals Challenge to develop a spectrum monitoring and classification model using a combination of Machine Learning and traditional DSP techniques
Developed a new technique for spectrum monitoring that uses Convolutional Neural Networks and Cyclostationary analysis to accurately classify signals at very low SNR's.
Ported Sigplot, a web-based X-plot, to Android and integrated RTL-SDR dongle support for live, real-time spectrum visualization
Researched and implemented geo-spatial analytic techniques for visualization of large data sets

NC State Physics Department

Undergraduate Research Assistant

Worked for Dr. Daniel Dougherty as part of the 1st year Undergraduate Research Program. Assisted his resarch on surface deposition modeling by developing a C++ program to simulate his theroized models.

Education

The Georgia Institute of Technology

Aug 2018 - Dec 2019

Master of Science in Electrical and Computer Engineering

Working as a GRA at GTRI while pursuing a Master of Science degree. Academic focus on digital signal processing, wireless communications, and embedded software defined radio systems. Research focusing on applying machine learning to signal processing problems.

North Carolina State University

Aug 2014 - May 2018

Dual Bachelors of Science in Electrical and Computer Engineering

Graduated Magna Cum Laude
Lund University Exchange Program - Spring 2017
Chancelors Leadership Scholar
Gilman Scholar

Featured Projects

Open Source FMCW RADAR

Frequency Modulated Continuous Wave (FMCW) RADAR designed for the NC State 2017 senior design Project. Won 1st prize at the Fall 2017 senior design day. Designed to be a low-cost, easily assembled RADAR system for use by hobyists, educators, and students. I designed the 2.4GHz power amplifier, directional coupler, RF waveform generator and accompanying PLL, and signal processing software. We achieved a range of up to 50m while staying within the FCC power limits.

View Project Report

Machine Learning for MIMO Systems

Massive MIMO is seeing rapid deployment with the onset of 5G and the development of 802.11ax products. Existing demodulators are known to be suboptimal. I am exploring the application of Machine lerning to MIMO demodulators operating in a simulated rayleigh fading channel with noise. This project is being done as part of Georgia Tech's ECE6604 Principles of Mobile Communications taught by Dr. Gordon Stüber.

View Project Report (COMING SOON - Nov 2018)