GUANGYU HAN

Boston, MA 614-***-**** adu0c6@r.postjobfree.com linkedin.com/in/guangyu-han-16a7a812b/ EDUCATION

Northeastern University Boston, MA

Master of Data Analyst Engineering (GPA: 3.87) Expected May 2023 Relevant Coursework: Data Mining, Machine Learning, Simulation Analysis, Neural Networks & Deep Learning, Data Management for Analytics, Foundations of Data Analytics, Computation and Visualization Ohio State University Columbus, OH

B.S. in Mathematics (Financial Math) with Statistics Minor May 2020 SKILLS

Programming Languages: Python3, R, Oracle, MySQL

Analysis Tools: R Studio, Tableau, Excel, Lingo, Python-based Machine Learning and Data Analysis Package PROFESSIONAL EXPERIENCE

NORTHEASTERN UNIVERSITY Boston, MA, United States

Data Mining Course Teaching Assistant Jan 2023 - Present

● Reinforced students learning of Python Basics, Data Pre-processing, Data Visualization, Regression Models, Classification Models (KNN, NaiveBayes, CART, Logistic Regression, etc.), and Neural Network Model

● Graded 50 group’s assignments and quizzes, track their project milestones, and provide feedback to students regularly

● Recorded lecture attendance, assisted professor’s teaching in class, and held 3-hour office hour each week CHINA UNICOM SMART CONNECTION CO., LTD Beijing, China Big Data Research Intern June 2019 - Aug 2019

● Analyze the data of Unicom's Internet of Vehicles Businesses, e.g 3G, Jasper and B side, to forecast the Users Online Behaviors based on their users info, distributions, and connections

● Established 6 self-perpetuating plot sheets of Unicom’s Businesses, and supported team with ad-hoc Analysis employing Yonghong BI in SQL language to show the annual and monthly usage trend of each Business

● Trained new interns on the use of BI and handovered them BI related tasks

● Collaborated with 2 colleagues to build 2018-2019 Vehicle Internet Insight Report in Powerpoint PROJECT EXPERIENCE

Human Memory and Cognition Models Using Python - Northeastern University Jan 2022 - May 2022

● Perform data wrangling, get_dummies, standardization, and reconstruction by using pandas, numpy and sklearn

● Built 9 machine learning classification models like classification tree, random forest, and neural net etc., and compared their performance based on lift charts and accuracy, and finalized on neural net model

● Fine tuned the model to predict the stress level of participants with 51.56% accuracy, by 8 predict variables California Census Data and Housing Price Using Python - Northeastern University Apr 2022 - May 2022

● Initial data wrangling, standardization, and visualizations are done using pandas, numpy, sklearn, and matplotlib

● Built linear regression and polynomial regression models, and then use cross-validations, such as lassocv and ridgecv, to further improve the polynomial regression model’s performance

● Predict California Housing Price with 68266 RMSE by 8 determinant variables Forum Website Database Management System - Northeastern University Sep 2022 - Dec 2022

● Built both Relational and NonRelational databases that store data of account, ads, post etc. with 7 relation entities

● Accessed database in Python to visualize data distribution under 7 different business conditions

● Loaded and extracted data from MongoDB by NoSQL query, and Neo4J by Cypher query

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