Bin Jie Lu
480-***-**** • ******.**@***.*** • linkedin.com/in/binjie-lu-43829292
SUMMARY
BSE Electrical Engineering (Electrical Power and Energy System) and MSE Electrical Engineering with focus in Signal Processing and Computer Vision.
EDUCATION
B.S.E., Electrical Engineering (Electrical Power and Energy System) Graduated May 2015
Arizona State University, Tempe, AZ 3.32 GPA
M.S.E., Electrical Engineering (Signal Processing and Computer vision) Graduating May 2019
Arizona State University, Tempe, AZ 3.52 GPA
TECHNICAL SKILLS
Data Analysis and Statistics: R-Studio
Design and Applications: MATLAB
Programming: Python, Java, C++
Other: Microsoft Excel, PowerPoint, Word, Project
Certifications: NCEES FE Certificate: The Fundamentals of Engineering (FE)
PROFESSIONAL EXPERIENCE
PCT International Inc, Mesa, AZ: Radio Frequency (RF) Engineering Technician 9/2016 – 12/2017
Tested new RF product with new procedure increased time efficiency by 22%
Developed and Updated the Industrial benchmarked test procedure
Increased data analysis of testing result accuracy and efficiency by 10% and 20% respectively by creating new template and method
Researched and Developed testing fixture for new test requirement for customers (COMCAST, Time Warner, etc.)
ACADEMIC PROJECTS
ASU, Senior Capstone Design Project Spring 2015
Collaborated in a team of three to design and develop Automated Vent for AC unit
Accomplished cost estimation and time arrangement milestones using Microsoft Excel
Developed automated Vent System to equalize the temperature throughout the house in C language, increased energy efficiency of the house by 15%
Created detailed project report in MS Word
ASU, Application of Object Detection in Video Fall 2018
Led team of two to design and develop an algorithm to assist the campus traffic
Utilized the Convolutional Neural Network technique with TensorFlow to detect the object (student) and optical flow to tracking object
Designed an algorithm that will detect, count and track the object within the vision region
ASU, Application of Panorama Fall 2018
Developed an algorithm to do image stitching in Python with OpenCV
Utilized the SIFT, FAST and LUCID to extract local features and feature descriptor
Designed an algorithm will do multi-image stitching and smoothing which is the fundamental of Panorama.
ASU, Application of Deep Learning in Media Processing Spring 2019
Implement the basic machine learning data fitting (training) with Least Square Fitting, K-Nearest neighbors (KNN), Logistic Regression and Support Vector Machine (SVM)
Understand the fundamental behind every method and design the algorithm with forward function, loss function, gradient loss function with respect to weights and bias, fit function and predict function.
Implement 5-layer NN (including Fully Connected Layer, Relu layer, Softmax Layer and Cross Entropy Layer) with CIFAR100 dataset, established the data training and weights optimization
OTHER WORK EXPERIENCE
South Mountain Community College, Phoenix, AZ: Math and Science Tutor 9/2010 – 9/2011
Tutor community college students in math and engineering subjects