Jiani Liu
***** ******* **** **, *******, TX ****5 +1-626-***-**** ******@*.****.***
SUMMARY
Looking for Software Engineer Position. Inquisitive, highly enthusiastic in developing and designing scalable applications, proficient with Java in programming, with a strong multidisciplinary background in computer science, mathematics, and statistics.
SKILLS
Language: Java, HTML/CSS/Javascript/Ajax, React JS, SQL, Shell, Go Database: MySQL, MongoDB, BigTable, BigQuery, Dataflow, Google Firebase Tools: Google Cloud, Android Studio, Maven, Git, Gradle, ElasticSearch, Amazon EC2, Apache Tomcat, JUnit, JMeter, Google AdMob, Tensorflow
EDUCATION
University of California, Los Angeles (UCLA) March 2018 Bachelor of Science in Financial Actuarial Mathematics Computer Science Courses: Computer Algorithms, Data Structure, Programming Languages (Java), System Design, OOD, Database, Cloud Computing, Web Development, Mobile Development (Android), Big Data/Machine Learning PROJECTS
Image Recognition based Social Network (Go, React JS) April 2018 – Sep 2018 l Established scalable web service in Go to handle posts and search, and deployed to Google Cloud (GAE) for better scaling.
l Installed ElasticSearch in Google Cloud (GCE) to provide geo-location based search within a certain distance. l Utilized BigTable to save real time users data, and used Google Dataflow to implement a daily dump of users' posts from BigTable to BigQuery for further analysis.
l Used Google Cloud ML API and Tensorflow to train a face detection model and integrate with the Go service. l Connected backend with React JS, and created some features such as “Create Image/video Post”, “Search Nearby Post As Gallery”, and “Filter Face Image” with Ant Design (React UI framework) and Google Map API. l Implemented basic token based registration/login/logout flow with React Router v4 and server-side user authentication with JSON Web Tokens (JWT).
l Enhanced web service scalability using Google Cloud that cover over 90% users around the world to post and to search images/videos.
Android App for Tourists and Local Resident (Java) April 2018 - Sep 2018 l Designed a LBS based Android App for users to report and search events based on current location and keywords. l Created a connection to Google Firebase (Database and Storage) to store all events and manage user-created content including geo-locations, comments, likes, images, descriptions, title, and event release date. l Integrated Google Map API to display nearby hot events according to user's current location and navigate to the event. l Deployed in-app advertising (Google AdMob) to the list of events and display Google advertisers for every three events. l Used Firebase Cloud Messaging (FCM) as app servers to send messages to a group of devices that are subscribed to a topic, such as notifications.
l Empowered users to post and to search their favorite events on mobile devices according to their current locations. Event Recommendation System (Java, JavaScript) April 2018 - Sep 2018 l Built a personalized web page for users to search nearby events based on their preferences and browsing history. l Designed an interactive web page utilizing AJAX technology with HTML, CSS, and JavaScript for users to search nearby events, update their favorites, and view recommended events. l Established relational databases MySQL and non-relational database MongoDB to store data that captured real events data from TicketMaster API.
l Designed content-based recommendation algorithms to implement events recommendation. l Analyzed users' behaviors based on their locations, demographics by using ELK stack (ElasticSearch, Logstash, Kibana), and used MapReduce in MongoDB to find peak periods. l Improved precision of recommended events based on distance, stars, and matched categories, and deployed server side to Amazon EC2 to handle 180 requests per second tested by Apache JMeter. NBA Player Strength Visualization (React JS) April 2018 - Sep 2018 l Developed a dashboard to visualize NBA players' shot data, including shot chart, their statistics, for users to search. l Used d3-shotchart library to implement linked highlighting among all charts, and provided a field goal percentage filter for users to see more detailed visualization with each player's shots.