Philip "Sam" Davis is pursuing a PhD in electrical engineering from New Mexico State University with a focus on signal processing, embedded programming, and machine learning. He has extensive academic and research experience in these areas, including coursework, research projects analyzing EEG signals to predict human perceptions, and internships. His skills include signal processing, machine learning, embedded systems, and software/hardware design. He is currently finishing his dissertation and has published several papers in the field.

1. Philip “Sam” Davis
17620 Wagon Wheel Dr.
El Paso, TX 79938
Cell: (801) 891-9568
psdavis1@gmail.com
Objectives:
Pursue a career in electrical engineering focusing on digital signal processing,
embedded programing, and machine learning.
Academic Experience
Graduate Education:
I am currently in my last semester of combined Masters/PhD program in Electrical Engineering
focusing on Signal Processing at New Mexico State University
GPA: 4.0
 Courses: Digital signal processing, Digital Image Processing, Machine Learning and
Pattern Recognition, Random Signal Analysis, Information Theory, Signal Detection and
Estimation Theory, Real Time DSP, Biosensor Electronics.
Undergraduate Education and Honors:
B.S. – Electrical Engineering and Supplemental Applied Mathematics – 2006, New Mexico State
University
GPA: 4.0
 Dean’s List in NMSU College of Engineering – every semester during 2002-2006
 Exchange Program at University of Utah – 2004-2005
 Courses: Intro to digital signal processing, digital communications, signals and systems,
digital design.
Concurrent Enrollment – 2001-2002, Northern Arizona University
GPA: 4.0
 Courses: Applied Statistics, Biology, Calculus I, II, and III
Online Uncredited Courses:
Machine Learning and Neural Networks for Machine Learning courses taken through the free
online website Coursera.
Research and Work Experience
New Mexico State University – August 2010 – present
 Research Assistant exploring compressive sensing topics
 Use Matlab and parallel processing toolbox to run simulations.
 Study the human perception of video quality through the use of signal processing
techniques on electroencephalograph (EEG) signals. Feature vectors from raw data are
created to perform discriminant analysis between low and high quality video. Machine
learning techniques are applied to try to predict which quality of video a user is viewing.
 Design of hardware in a FPGA to measure cross frequency coupling between low and
high brainwave frequencies in a single EEG channel.
 Run human test subjects in audio and visual trials.
Medtronic – May 2015 to August 2015
 Summer internship working on pulse oximetry.
 Machine learning algorithms applied to pulse oximetry signal.
Covidien – May 2014 to August 2014
 Summer internship working on pulse oximetry.
 Integrating and testing new sensor designs with existing technology.
 Interfacing sensors with Freescale Kinetis processor on an embedded platform.

2. Lowell Observatory – July 2007 to July 2010
 Research and development of new distributed control systems on the telescope array.
These new control systems allow for remote monitoring and mirror alignment.
 Embedded software design and development with Texas Instruments MSP430 micro-
controller, Altera’s Max II CPLD and Cyclone II FPGA.
 Testing and debugging new and existing electrical control systems
 Trouble shooting and fixing aging electronic systems on the array
RC Optical Systems – November 2009
 PCB design for new telescope focusing control unit
CERN – June to August 2006
 Nation Science Foundation Research Experience for Undergraduates through the
University of Michigan at CERN in Genève, Switzerland.
 Engineering responsibilities include circuit verification and analysis using Quartus II.
 Physics research using data generated in a Monte Carlo simulation representing data
from the new Large Hadron Collider particle accelerator to search for a theoretical
particle in a certain decay channel by suppressing background signals.
Senior Capstone Class – August 2005 to May 2006
 Worked in a team to design and create a distributed sensor array.
 Designed a Monte Carlo simulation in Matlab to determine the number of sensor nodes
and the distribution needed for a given test area.
 Data analysis of sensor nodes.
 Designed the PCB using PCB123 for the sensor nodes.
Pinnacle Mapping Technologies – January to May 2004
 Co-operative work-study program in Flagstaff, Arizona.
 Responsibilities included image analysis and rectification using ENVI and ArcView.
Professional Organizations:
 IEEE
 Mathematical Association of America
Relevant Skills
Signal Processing
 Filter design and analysis
 Fixed and floating point filter design and implementation.
 Use of FFT for signal analysis
 The use of up and down sampling signals.
 Time series analysis.
Machine Learning
 Extensive use of classifiers including Support Vector Machines (SVM), Deep Neural
Networks, Convolutional Neural Networks, Gaussian Mixture Models, and linear
discriminant analysis.
 Feature extraction and analysis.
 Use of Principle Component Analysis (PCA) for dimensionality reduction.
Embedded and Digital Design
 Design in analog and digital electronics.
 Work with Freescales Kinetis Low Power 32-bit arm MCU.
 Use ISE to design and validate hardware in a Xilinx FPGA.
 Use of Altera’s Quartus II software for programming Cyclone II FPGA’a and Max II

3. CPLD’s using Verilog HDL.
 Use of Altera’s TimeQuest Analyzer to verify FPGA timing requirements
 Work with Mentor Graphics Modelsim to verify FPGA design functionality and timing
 Implementation of Nios II processor on Altera FPGA’s
 Extensive use of Texas Instruments Code Composer V3 to program and test their 16
bit MSP430 microcontroller.
 Assembly programming with the Freescale DSP56302 DSP
 Fixed point implementation of signal processing algorithms in real time using Texas
Instruments TMS320C6416 DSP
 Embedded Hardware design of 16 bit CPU’s. Embedded software design using
professional development and debugging environments and modern software
architectures.
 Use of JTAG for programming and debugging software
 Communication Protocols and Busses: RS232, Ethernet, SPI, and I2C
 Programming in C and C++, work with wrappers and DLL’s in C/C++/C#, object
oriented design patters.
 Designing, testing, and debugging prototype control systems with embedded CPU’s
and digital and analog components.
Software and Other Skills
 Use of Matlab for data analysis, communication protocol simulation, and Monte Carlo
simulations.
 Troubleshooting analog, digital, and communication signals using oscilloscopes and
other various lab equipment.
 System design from concept to development.
 Work with DC and Stepper motors. Use of Stepper motor controllers with micro
stepping capability for accurate positioning of devices. Use of PWM with DC motor
controllers for speed and resolution control.
 Environments: Window and Linux (Fedora and Ubuntu)
 Other Software: Multisim, PSpice, Microsoft Visual Studio, MPLab.
 Multilayer, high-density PCB design using Cadsoft’s Eagle.
 Surface mount soldering
 Multi-Platform GUI design using QT4
 Adept at reading schematics and data sheets
 RTD/PT100 temperature sensors
Publications
 P. Davis, C. Creusere, and J. Kroger. Assessing Cross Frequency Coupling in EEG Collected
from Subjects Viewing Video using a Modified Metric. Southwest Symposium on Image Analysis
and Interpretation. IEEE, 2016
 P. Davis, C. Creusere, and W. Tang. Window length effect on cross frequency coupling in an
EEG processing circuit. 58th International Midwest Symposium on Circuits and Systems
(MWSCAS). IEEE, 2015
 P. Davis, C. Creusere, and J. Kroger. Subject Identification Based on EEG Responses to Video
Stimuli. International Conference on Image Processing. IEEE, 2015
 P. Davis, C. Creusere, and J. Kroger. Classification of Human Viewers Using High-Resolution
EEG with SVM. IEEE Conference Record of the Forty Eighth Asilomar Conference on Signals,
Systems and Computers (ASILOMAR). IEEE, 2014
 P. Davis, C. Creusere, and W. Tang. ASIC Implementation of the Cross Frequency Coupling
Algorithm for EEG Signal Processing. 14th International Symposium on Integrated Circuits
(ISIC). 2014
 P. Davis, C. Creusere, and J. Kroger. EEG and the human perception of video quality: Impact of
channel selection on discrimination. In 1st IEEE Global Conference on Signal and Information
Processing. IEEE, 2013.

4. References
References available upon request.