Steven Lu

707-***-**** adb5r6@r.postjobfree.com

Objective Software Engineer

EDUCATION

University of California, Irvine Dec 2019

Bachelor of Computer Science (GPA: 3.45/4.00)

COURSES AND SKILLS

• Languages:Python,C#(.NET),C++,Java,SQL,Shell Script,HTML,JavaScript.

• Basic Knowledge of MS SQL Server, Oracle 11g, Linux Server 7, Git, Jenkins, Azure Pipeline, Power Shell Script, Selenium, Hibernate.

• Relevant Courses: Data Structures and Algorithm, Database Management, Operating System(XV6),Computer Networks, Cisco Network CCNA, RedHat Linux RHCE, Oracle OCP.

EXPERIENCE

Department of Cognitive Sciences, UC Irvine June 2019 -Sep 2019 Software Developer

• Developed and designed psychopathology experiments using Python(PsychoPy).

• Addressed human representation of predictive structure in the environment and how such knowledge shapes motivated behavior.

• Assisted research in the Learning and Decision Neuroscience Laboratory. PROJECTS

• Web Search Engine(Python,MongoDB, C#(.Net MVC) ) Oct 2018 Developed a search indexer that ranked information crawled from ics.uci.edu. The crawler implements lemmatization, stopwords, and collocation to parse the contents of the crawled pages, which then are stored with tf-idf index in Mongo Database to provide appropriate ranking for the searched keywords in the MVC application interface.

• Goal-Based AI Agent(C++, MySQL) Jan 2019

Implemented a goal-based AI agent for solving the Wumpus World game problem. The game environment is sequential and partially observable, and the program rules are set to be independent upon the game settings. The agent simulated 10000 randomized training instances and improved the performance measure using Bayesian network.

• 3D Model Reconstruction (Python,OpenCV, Jupyter) Apr 2019 Constructed a computer vision system building 3D model from images. It decodes a set of gray coded images into binary masks which contain reliable pixels, and then reconstructs the 3D Coordinates using triangulation. The system cleanups the constructed mesh using error detecting methods, and then smooths the point locations by mean relocation computation.