Python, SQL, R

Kaiwen Liu

Email: ******@********.*** linkedIn: www.linkedin.com/in/kaiwen-h-liu

Summary

* ***** ** ********** ** python for data analytics and data science. Equipped with data manipulation, statistics, machine learning related technical skills. Experienced in building a recommendation system and database application. Looking for summer internship in data/business analytics in the United States. Education

Columbia University GPA: 3.6/4.0 Aug.2019-Dec.2020(exp)

M.S. Electrical Engineering

Related course: Machine Learning, Database, Algorithm, Data Processing, Big Data Analytics Beihang University (BUAA) GPA: 3.6/4.0 Sept.2015-Jun.2019

Bachelor of Engineering in Automation Science

Key Skills

Programming Language: Python, SQL, R

Analytical skills: Data Manipulation (Numpy, Pandas), Machine Learning, Deep Learning, A/B testing, Visualization, Tableau

Projects

Movie recommendation system on MovieLens dataset Oct,2019-Dec,2019 Summary: Developed a movie recommendation system using Spark and Python featuring collaborative filtering algorithm.

• Imported data which contains 10,000 ratings and 1683 movies, created 943 virtual users using pandas for test.

• Used Alternative Least Square algorithm to train the model and achieved 0.95 RMSE compared with 3.5 at the beginning.

• Set up a database on Google Cloud Platform, used SQL to interact with users’ request.

• Designed and implemented a web application where users can sign in, sign up, rate movie and see recommendation results using Flask, CSS, HTML.

Heart Disease Prediction on UCI dataset Nov,2019-Dec,2019 Summary: Set up Machine Learning models to predict heart disease.

• Removed duplicates and missing values dataset which contains 304 instances and did feature selection using p value.

• Trained the Logistic Regression, Neural Network, K Nearest Neighbors (KNN) models and did model selection using cross validation with R.

• Achieved 0.828 accuracy and 0.845 recall rate of best performance on KNN binary classification which could help medical institutes improve diagnosis performance. Flight tickets purchase system Oct,2019-Nov,2019

Summary: Built a flight tickets query and purchase web application system.

• Collected airlines, flights, aircrafts, airports, cities datasets and generated partially virtual datasets including users, tickets, purchase record and departure-arrival according to schema.

• Imported datasets to GCP BigQuery and connected the project to GCP.

• Designed website application with Flask, CSS, HTML. Used SQL to implement users’ interaction with database in real time.

Experience

BUAA Digital Navigation Center

Lab intern Nov.2018-Jun.2019

Carried out computer vision project of multi-class meters detection and readings recognition using convolutional neural network and OpenCV and built graphic user interface using Pyqt5.

• Gained images by taking more than 1200 photos, performed image enhancement by rotating and modifying brightness to more than 3000 photos, labeled images with bounding box and generated training reference files.

• Trained the model with Faster R-CNN and YOLO separately and tested with images and video.

• Achieved 0.9453 mean average precision of detection and 0.833 percentage of reading predictions within 3 scale divisions error in a certain scenario.

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