Software Engineer Intern

Ziyu Liu

Los Angeles, CA *****

213-***-**** ********@***.***

www.linkedin.com/in/ziyu-steve415

https://github.com/Lzysteve98

EDUCATION

University of Southern California, Los Angeles, CA

● Master of Computer Science, GPA: 3.82/4.0

Columbia University in the City of New York, New York, NY

● Master of Electrical Engineering, GPA: 3.60/4.0

Nanjing University, Nanjing, China

● Bachelor of Material Physics, GPA: 4.38/5.0

Aug 2022 – Expected Dec 2024

Sep 2020 - Dec 2021

Sep 2016 - Jun 2020

TECHNICAL SKILLS

● Programming Language: Proficient: Java, Experienced: Python, JavaScript, HTML, CSS, R, C, C++, C#

● Technical Skills: Spring framework, Spring MVC, Spring Boot, Spring Cloud, MySQL, Redis, RESTful, RabbitMQ, Elasticsearch, Docker, Django, PySpark, Flask, AWS, PostgreSQL, pandas, Unity WORK EXPERIENCE

Software Engineer Intern Wuhu Automobile Advanced Technology Institute Co., Ltd., Anhui, China Jun 2022 - Aug 2022 Chery Automobile User Dashboard Backend Development in Java Spring

● Structured RESTful APIs for users to manage data from personal automobiles by Spring Boot, MySQL and RabbitMQ.

● Improved data retrieval performance by utilizing Redis as cache, reducing 0.5s latency on average.

● Boosted API efficiency by 50% for descriptive searches by creating Elasticsearch's full-text indexing.

● Supported driving data visualization and analysis from Internet of Vehicles platform by deploying RabbitMQ and integrating WebSocket with Spring Boot.

Software Engineer Intern Google Inc., Shenzhen, China Sep 2021 - Nov 2021 Microservices Development for Online Shopping Data Analytics

● Designed and executed RESTful APIs and a Microservices Pipeline using Java, Spring Boot and Spring Cloud to publish data streaming from datasets, obtained a benchmark capacity of 1200+ QPS.

● Built a data ingestion service to validate raw client input data and publish it to RabbitMQ as data buffer and decoupling.

● Developed a data processor, securely archiving analytics data via REST calls and cutting data retrieval time by 25%.

● Collaborated with a machine learning team to optimize product recommendation success rate to 95%+ in customer feedback and improved Return on Investment by 60% in simulation.

● Analyzed weekly updated datasets, visualized results with Python Seaborn script and R, and automatically generated weekly reports to communicate findings to stakeholders effectively. PROJECT EXPERIENCE

Web Gomoku Games Interface Based on AlphaZero Algorithm PostgreSQL, Flask Sep 2021 - Dec 2021

● Trained RNN and Resnet models on deep neural networks by PyTorch and Keras, implementing self-play scenarios to assess impacts of various factors on model performance and achieving a 98%+ win rate.

● Constructed a back-end database based on PostgreSQL with 100+ Gomoku opening strategies and devised a web-based Gomoku visualization interface based on Flask model auto-plays and user interaction comparisons in Gomoku. Web Applications for Online Shopping PostgreSQL, Flask Jan 2021 - Apr 2021

● Created a back-end database based on PostgreSQL with 1000+ products and used Flask to interact with front-end webs- application input and operations.

● Fulfilled different requirements on the customer and employee web interface, including quick log-in and log-out, order creation and operations (including all common functions on shopping items). End-to-End Movie Recommendation System PySpark, Django, AWS Oct 2020 - Dec 2020

● Accomplished multiple recommendation algorithms including Alternative Least Square(ALS), Graph Convolution Network(GCN), Pearson Correlation on a model based on 25M training data.

● Integrated a web-based application with the back-end recommendation system to show personalized recommendation for customers through PySpark, Django, AWS and TMDB’s API.

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