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Engineering Electrical

Jamaica Plain, MA
March 14, 2020

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Minghui Ji

Phone: 864-***-****


Available: May-Dec 2020


Northeastern University, Boston, MA, USA Expected 2021 Master of Science: Computer Engineering

Clemson University, Clemson, SC, USA 2017-2019

Bachelor of Science: Electrical Engineering

Beihang University, Beijing, China 2015-2017

Bachelor of Science: Electrical Engineering

Technical Skills

Programming Languages: Java, C/C++, Python, HTML, CSS, JavaScript, Matlab, R, SQL Frameworks: Bootstrap, Angular 8, React.js, Node.js, Spring Boot, Tools: MySQL, MongoDB, Postman, Hibernate, AWS, Linux Work Experiences

Software Engineering Intern, Chengdu, China Sep. 2019 – Dec. 2019 CORPRO Technology, Inc

Used Angular framework with related programming languages to design and build the web page.

Utilized MongoDB cluster to address the issue of large-scale datasets and high throughout operations with the team. Project Experience

Job Finding Web Application, Northeastern University Sep. 2019 – Dec. 2019

Used Bootstrap and Angular 8 to design a responsive front-end web page to display related job data.

Implemented MySQL database System using Hibernate(JPA) with Spring Boot for the back-end data flows.

Used Spring Security to implement user management, authentication, and session management.

Built server-side RESTful APIs based on Spring Framework to implement register, create, update etc. Online Shopping Recommendation System, Northeastern University Mar. 2019 – Aug. 2019

Adopted React and Node.js to build a single-page web application for user to get an interactive shopping experience.

Implemented a data pipeline using MongoDB, and Redis to scrape the product information.

Used Tensorflow to design and build a training pipeline for product classification with accuracy of 79.8%.

Utlized NLP Model to analyze user search information and match them with the database.

Implemented a click event to collect user clicks and built a Recommendation Engine to show the users’ preference. Contextual Outlier Detection with Metric Learning, Clemson University Jan. 2019 – Mar. 2019

Implemented a contextual outlier detection model in a pipeline with Python, Pandas, and Scikit-learn.

Trained the geographical datasets with Machine Learning algorithms including Metric Learning and KNN regression to detect the outlier.

Deployed PySpark to accelerate the process of hyper parameter tuning using GridSearchCV with the True Positive Rate reaching 95%.

Evaluated and Visualized the data preprocessing and training outcome with Seaborn and Bokeh. New York City Airbnb Price Prediction, Clemson University Aug. 2018 – Dec. 2018

Implemented a New York City Airbnb price prediction model in R with the emphasis of the impact of crime rate.

Explored and preprocessed the datasets with ggplot2, ggmap and dplyr.

Trained and cross-validated three Machine Learning Algorithms, Logistic Regression, Random Forest, and KNN.

Visualized and interpreted the correlation and causation for the underlying features.

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