Ryan Peach, Developer in Bowling Green, United States
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Ryan Peach

Verified Expert  in Engineering

Electrical Design Developer

Bowling Green, United States
Toptal Member Since
December 1, 2016

Ryan is an electrical engineering and computer science graduate student, who has worked for several years in R&D for various clients—in topics ranging from math and scientific testing applications, hardware and circuit design, and most recently machine learning, AI, and computer vision applications. He is a talented Python/C++/LabVIEW developer and keeps up to date on the latest cutting edge research in the field of CS.


Nasco NHK
Industrial Design, PLC, Ladder Logic
WKU Science Labs
Control Systems, C++, MATLAB, Python, Verilog, VHDL, LabVIEW, CAD
Department​ ​of​ ​Chemistry,​ ​WKU
DAQ, Solar, Oscilloscopes & Tester Equipment, LabVIEW




Preferred Environment

PCB Design, Computer Vision, Machine Learning

The most amazing...

...AI I have built was capable of solving Raven's Progressive Matrices intelligence tests at a human level using knowledge-based AI techniques.

Work Experience

Electrical Engineer, Automation

2015 - PRESENT
Nasco NHK
  • Programmed PLCs and robotics for a variety of industrial control and automation applications.
  • Designed electronics with AutoCAD, implemented hardware upgrades to equipment.
  • Diagnosed and maintained industrial electrical equipment.
  • Chose and ordered necessary parts and created budget reports.
  • Worked in teams with electrical maintenance and upper management, including Japanese engineers.
Technologies: Industrial Design, PLC, Ladder Logic

Electrical Engineer, R&D

2014 - 2015
WKU Science Labs
  • Worked with physics researchers in designing electronics for experimentation.
  • Helped design applications of Atomic Force Microscopes, Piezoelectric material, Chemical Detection, Solar Design, Motor Control, Signal Amplifiers, and Terra-hertz Lasers. Designed PCBs and programmed FPGAs.
  • Ordered parts and worked in CAD to design electronics.
  • Delivered a product from scratch independently.
  • Worked with the client directly to determine project requirements.
  • Designed measurement rigs for experimentation of project deliverables. Created scientific computing environments and software for use with the product.
Technologies: Control Systems, C++, MATLAB, Python, Verilog, VHDL, LabVIEW, CAD

Student Software Developer

2014 - 2014
Department​ ​of​ ​Chemistry,​ ​WKU
  • Designed software to control advanced multimeters via LabVIEW computer interface.
  • Created applications for graphing voltage, resistance, and currents in real-time.
  • Designed a testing platform and product enclosure for a solar array. Created the PCB design for interfacing test equipment with lab equipment.
  • Worked with international team collaboratively on research goals.
  • Created a user friendly design and instructions made for easy lab access.
Technologies: DAQ, Solar, Oscilloscopes & Tester Equipment, LabVIEW

Electrical Engineering Student

2014 - 2014
Applied Physics Institute
  • Designed PCBs, C++, and LabVIEW programming for scientific and embedded purposes.
  • Implemented machine learning algorithms for advanced mutli-chemical detection.
  • Researched and implemented new electrochemical and photovoltaic early detection units for air filtration systems.
  • Performed air current testing and designed rigs for experimentation.
  • Gave presentations and frequent project reports to supervisor. Worked in multidisciplinary team to create a consumer product worthy good.
Technologies: PCB Design, Machine Learning, LabVIEW, PCB, EAGLE, Atmel, Arduino, C++

Robotics Engineer | Teacher

2012 - 2014
Center for Gifted Studies
  • Taught Mindstorm robotics for many years at the middle school level.
  • Designed and implemented advanced programming challenges such as maze solving algorithms and synchronous dynamics.
  • Taught basic mechanical and electrical concepts.
Technologies: Robotics, Teaching, Mathematics, Physics, Electronics

DHS-STEM Student Internship

2013 - 2013
Pacific Northwest National Laboratory
  • Ran discrete-time Fourier analysis, digital filtering algorithms, and statistical analyses on large time-series datasets in Python and MATLAB.
  • Implemented machine learning spectral algorithms on large NLP datasets.
  • Attended weekly progress report meetings and presented research proposals for the future of the project.
  • Presented findings to the public both in research paper format and on-stage presentation.
  • Delivered project deliverables to DHS on the completion of the project.
Technologies: Social Media Analytics, Fourier Analysis, Data Analytics, Python, Machine Learning

Munkres' Algorithm Implementation

This code implements the Hungarian (Munkres') and Murty's algorithms in raw Python 2 and NumPy. It is written purely functionally to be easily memorized and parallelized. It is also based on research sources to be used in artificial intelligence programs that require optimal decision-making where an assignment is one of the tasks.

It is ready to run just by calling "python assignment.py." Given a "NxN" matrix, this algorithm minimizes the sum of the values giving a unique assignment of one row per column and returning a length N vector containing the column index for each row assignment. Murty's algorithm does this multiple times in ascending order of cost by using a Python generator. This "O(n!)" algorithm is implemented in an "O(N^3)" time complexity using the latest research.

Raven's Progressive Matrices AI

In Knowledge-Based AI, an intensely project-and-research-based graduate course, we each created our own research level artificial intelligence—each of which should be capable of solving every standard set of the Raven's Progressive Matrices intelligence test, verbally at first, visually by the end of the class, and were graded on our agent's performance on these tests.

My final agent scored 19/24 on the hardest problem sets, purely via visual information. My first project reflection was selected as a top 10 best in class, and my agent overall scored very well relative to my peers. We were allowed no outside code from other students, and worked with Python using only Numpy and PIL libraries. All in all, this has been my favorite class by far overall, and it inspired much of my interests in AI going forward.

"SALSA" SociAL Sensor Analytics at PNNL

While working for PNNL, I was given the task of constructing a mathematical model to increase the detection of Twitter-traffic spikes in a large web-traffic time-series. Over the course of several months, working with a mathematician Ph.D. and 2 undergraduate students of differing specialties, I learned how to write fluently in Python—using several different mathematical and graphical libraries and wrote thousands of lines of well-documented code for every task imaginable. My primary line of research was in the area of Fast Fourier Transforms (FFT), which required a lot of rigorous mathematical study and code manipulation on my part.

I spent months writing and testing highly complex algorithms for mathematical analyses, and even more time on interpreting the data and trying to improve the graphical outputs my code would generate. In the end, the experience was highly rewarding, and it taught me how to learn and research independently, as well as how to function well in a business environment.

OpenAI Gym Projects

In my spare time, I work on reinforcement learning problems on OpenAI Gym.

The following is a sample of a Q Learner with documentation that I have recently written for the site; which has a very high ranking and quick learning time for the environment, and is highly generalizable to other problem sets.

GitHub Open Source

My entire GitHub profile is available online.

I have participated in leading edge open-source projects such as OpenNARS at Temple University and frequently submitted code snippets to scientific computing archives such as NumPy and SciPy.

Active Contributor to Sklearn-deap—a Genetic Algorithm Library for Interfacing with Sklearn

I upgraded their development tools to the most recent Sklearn standards and constantly answer issues that arise.

Kaggle Data Analysis

I did some work on data analysis after the recent election and received some much-appreciated acclaim for my post on Kaggle for using their datasets.


Python, Go, Common Lisp (CL), C++, Java, VHDL, Verilog, Python 2


OpenCV, SciPy, NumPy, Pandas, TensorFlow, Scikit-learn




Object-oriented Programming (OOP), Functional Programming, Data Science, Concurrent Programming


PLC, Allen-Bradley PLCs, PCB Design, Robotics, Electrical Design, Mathematics, Artificial Intelligence (AI), Algorithms, Deep Learning, Data Structures, Machine Learning, Neural Networks, Computer Vision, Localization, Reinforcement Learning, Ladder Logic, Industrial Design, Control Systems, Data Analytics, Fourier Analysis, Social Media Analytics, Electronics, Physics, Atmel, PCB, Oscilloscopes & Tester Equipment, Solar, DAQ, FPGA


Debian Linux, Arduino, Windows, Android

Industry Expertise


2016 - 2018

Master's Degree in Computer Science, Robotics, and AI

Georgia Tech - Atlanta, GA, USA

2013 - 2015

LabVIEW CLAD Certification in Computer Engineering

National Instruments - Bowling Green, KY, USA

2010 - 2015

Bachelor of Science in Electrical Engineering with a minor in Mathematics

Western Kentucky University - Bowling Green, KY, USA