Education

Carnegie Mellon University

2015 Sept. - 2016 Dec.(Expected)
Master of Science (M.S.) in Intelligent Information System

Fudan University

2011 Sept. - 2015 Jun.
Bachelor of Science (B.S.) in Computer Science and Technology
  • GPA: 3.62/4.00
  • Core Courses: Operating Systems (A),DataStructure (B+), Introduction to Database Systems (A), Compilers (A-), Software Engineering (A-), Introduction to Artificial Intelligence (A)

Work Experience

Software Development Engineer Intern

2016 May. - 2016 Aug.
Riverbed Technology, Sunnyvale
  • Intern Project:
    • Designed and developed Access-Pattern-Driven Disk-Level Block-Based Prefetch System as project leader
    • Constructed adaptive prediction model with weighted correlation network
    • Increased cache hit rate from 5% to 90%, and decreased remote system booting time from 8 min to 4 min
    • Patent application is submitted by Riverbed Tehcnology
  • Manager: Joshua Berry

Summer Analyst Intern

2014 Jun. - 2014 Aug.
Morgan Stanley, Shanghai
  • Intern Project:
    • Designed and developed Data Distribution Network Visualization and Configuration Tool as project leader
    • Parsed and formatted about 3,000 hand-written configuration files with flexible grammar
    • Developed a GUI tool to generate the configuration files in uniform format
    • Visualized data distribution network with D3JS, detected configuration errors including loops, undefined parameters and setting inconsistency
    • Won Most Innovative Project among 57 Intern Projects
  • Manager: Junjie(James) Qu

Research Experience

Peloton Database Management System

2015 Sept. - 2016 Jun.
  • Description: Supported SQL expression system and made some detective work on concurrent B-Tree, and wrote a part of automatic benchmarking scripts
  • Supervisors: Anthony Tomasic, Andy Pavlo
  • Description:
    • Collected about 1,000 hand-written symbol forms, wrote a script to extract all individual symbols, and trained a mathematical symbol recognition model
    • Developed a formula recognition algorithm by aggregating pixel blocks into mathematical symbols and parsing the formula structure with relative positions of symbols
    • Developed an algorithm to correct recognition errors according to context
    • Reached over 90% recognition accuracy in hand-written mathematical symbol recognition
  • Supervisor: Deva Ramanan

In-Class student Behavior Analysis

2014 Jun. - 2015 Jun.
  • Description: Developed an algorithm to detect spam users and reduce their impact to rating scores
  • Supervisor: Chaofeng Sha

Skills & Proficiency

C / C++

Python & Django

Matlab

HTML5 & CSS

Javascript & jQuery