Evan Juras
Computer Vision Engineer at EJ Technology Consultants
Bozeman, Montana, United States
Summary
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Rockstar🎓
Top SchoolEvan Juras is a computer vision engineer and founder with nine years of experience building embedded ML systems and end-to-end vision applications. He blends a rigorous hardware background—analog and mixed-signal design, EMC compliance, and PCB layout—with hands-on Python and C++ development to ship production-ready solutions from edge devices to cloud-adjacent systems. As founder of EJ Technology Consultants he has designed camera selection and system architecture for real-world projects including card-tracking gaming tables and field-deployed risk-mitigation cameras, and he selects and trains lightweight detection models for constrained processors. His open-source work and tutorials on TensorFlow and TensorFlow Lite demonstrate practical expertise in model quantization, Edge TPU support, and Raspberry Pi/Android deployment, helping others bridge research to applied products. Based in Bozeman, Montana, he pairs technical leadership and mentoring with business-building experience, and maintains an active public portfolio and popular electronics YouTube channel that reflect a knack for clear technical communication.
9 years of coding experience
8 years of employment as a software developer
Bachelor’s Degree, Electrical, Electronics and Communications Engineering, GPA: 3.97 / 4.0, Bachelor’s Degree, Electrical, Electronics and Communications Engineering, GPA: 3.97 / 4.0 at Montana Tech of the University of MontanaMaster’s Degree, Electrical, Electronics and Communications Engineering, GPA: 3.73 / 4.0, Master’s Degree, Electrical, Electronics and Communications Engineering, GPA: 3.73 / 4.0 at Washington State University
Stackoverflow
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Github Skills (13)
object-detection10
computer-vision10
opencv10
machine-learning10
tensorflow-lite10
raspberry-pi10
tensorflow10
python10
image-processing10
quants9
quantization9
deep-learning8
github3
Programming languages (7)
Github contributions (5)
EdjeElectronics/TensorFlow-Lite-Object-Detection-on-Android-and-Raspberry-Pi
Sep 2019 - Jan 2023
A tutorial showing how to train, convert, and run TensorFlow Lite object detection models on Android devices, the Raspberry Pi, and more!
Role in this project:
ML Engineer
ML EngineerContributions:4 reviews, 303 commits, 17 PRs in 3 years 4 months
Contributions summary:Evan primarily contributed to the development of object detection models within the repository. Their commits showcase the implementation of scripts for object detection using TensorFlow Lite, including webcam, video, and image-based detection functionalities. The user also added features to save detection results and handle models for the Edge TPU. Furthermore, they demonstrated an understanding of model quantization and evaluation by integrating a script to calculate mAP scores.
raspberry-piandroid-devicesraspberryobject-detectionandroid
EdjeElectronics/TensorFlow-Object-Detection-API-Tutorial-Train-Multiple-Objects-Windows-10
Feb 2018 - Dec 2020
How to train a TensorFlow Object Detection Classifier for multiple object detection on Windows
Role in this project:ML Engineer
ML EngineerContributions:135 commits, 16 PRs, 130 pushes in 2 years 10 months
Contributions summary:Evan focused on developing and modifying object detection models within the TensorFlow framework. They contributed to multiple Python scripts related to object detection, including image and video processing implementations. The user made adjustments to the model's performance by tuning parameters like the `min_score_thresh`. Furthermore, the user added compatibility for TF2.
classifierwindowsdetectiontensorflow-object-detectionobject-detection
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