Bo Li is seeking a full-time software development position starting in February 2017. He has a Master's degree in Computer Science from Stevens Institute of Technology and Master's and Bachelor's degrees in Electrical Engineering from schools in Beijing, China. He has over 4 years of experience as a Software Development Engineer developing driverless train control systems. He is proficient in programming languages like C/C++, Java, JavaScript, Python and frameworks like Flask, Hadoop, and Bootstrap. He has also completed academic projects at Stevens Institute including developing a micro Twitter and eBay server in Python/Flask and a movie recommender system using Scala on Amazon EC2 that recommends movies based on a user's preferences.

1. Bo(Frank) Li
219 Laidlaw Ave, Apt.1, Jersey City, NJ 07306 Tel: 201-683-1878 libo824@gmail.com http://primbo.net
OBJECTIVE: Seeking for a full-time Software Development position starting on February 2017
EDUCATION: Stevens Institute of Technology, Hoboken, NJ
Master of Science in Computer Science (GPA: 3.96/4.0) 09/2015 – 12/2016
Core Curriculum: Distributed System and Cloud Computing, Concurrent Programming, Introduction to
Operating Systems, Advanced Algorithm Design & Implement, Database Management System
Beijing Jiaotong University, Beijing, China
Master of Science in Electrical Engineering (GPA: 3.6/4.0) 09/2008 – 02/2011
Beijing Institute of Technology, Beijing, China
Bachelor of Science in Electrical Engineering (GPA: 3.5/4.0) 09/2004 – 06/2008
SKILLS: Programming Languages: C/C++, JAVA, JavaScript, SQL, node.js, Python, Erlang, Scala
Operating Systems: Unix/Linux, Windows, Mac
Databases: PostgreSQL, MySQL, MongoDB
Application Framework: Hadoop, Flask, CDAP, TCP/IP, RESTful, AmazonEC2, Bootstrap
EXPERIENCE: China & America Signal Corporation, Beijing, China 02/2011 – 08/2015
Software Development Engineer
Driverless train control system
• Won “Pearl River Delta Rapid Transit” automatic train operation contract from competitor by
successfully implementing best performances of driverless train control system – implementation includes
designing high performance algorithm, integrating sensors data into software, establishing failure to safety
principle into the system and shaping a RAMS(Reliability, Availability, Maintainability, and Safety) system
• Implemented algorithm to reach best automatic train operation performances in terms of control and
stopping precision.
• Acted the “moving block” principle to ensure operating headways as short as 80 seconds between two
trains in order to achieve maximum line capacity, which is using on “Line 2, Beijing subway”
Master Simulator (embedded system testing environment)
• Developed a scalable real-time distributed testing environment based on HTML/JavaScript/node.js,
handling real time and batch processing of thousands of requests and daily events
• Integrated and synchronized different kind of signals (RS232, RS485, Profibus, square signal, relay),
implemented middle layer between hardware and software
• Worked with the QA team to ensure high-quality delivery with unit and integration tests
• Designed, developed and maintained this service API based on MQTT Protocol.
• Established monitoring performance. Designed front end user interface based on Bootstrap framework
• Designed the server side database to storage static data (railway line data) and dynamic data (network
transmission data) based on MongoDB
ACADEMIC Stevens Institute of Technology, Hoboken, NJ
PROJECTS: Several web projects (Micro Twitter, Micro eBay and Email Classifier Website) 10/2016 – 11/2016
• Developed decently featured Micro Twitter server based on the Python/Flask combination; Implemented
a website to access email and filter overdue emails from Gmail through Gmail API
• Design user logins, sessions, profiles and user avatars and implemented database management
• Built Web form support, email notifications to users, full text search, email notifications to users and
pagination of long lists of items.
• Utilized caching and other performance optimizations.
• Used git revision control system to track progress and collaborate with team.
• https://github.com/libo824/2016SummerEmailClassifier
Web Crawler and Movie Recommender 05/2016 – 08/2016
• Developed a Web crawler with Bloom Filter to get 1,000,000 movies’ web pages from IMDB web site in
Python and stored these information in MySQL; Built an application to recommends movies to users using
collaborative filtering using those crawled data
• Researched distributed algorithm paper such as MapReduce, Google FS, Paxos
• Applied the ALS algorithm from Apache Spark's MLlib to train the prediction model based on Scala
• Utilized the MapReduce method, based on the prediction model to calculate the predicted scores on non-
rated movies
• Deployed the previous project on Amazon EC2
• https://github.com/libo824/MovieRecommender