Yidong Fang

Yidong Fang

Software Engineer

Bloomberg L.P.

Biography

I am currently a full-stack expierenced software engineer at Bloomberg, with experience in event-driven micro-service architecture design, CI/CD pipeline optimization, containrization and data streaming.

Interests
  • Software Development
  • Infrastucture Engineering
  • Computer Vision
  • Information Security
Education
  • M.S. in Computer Sciences, 2019-2021

    University of Wisconsin–Madison

  • CSST Summer Research Program, 2018

    University of California, Los Angeles

  • B.E. in Computer Science and Technology, 2015-2019

    Southern University of Science and Technology

Experience

 
 
 
 
 
Software Engineer
Bloomberg L.P.
Feb 2021 – Present NYC, United States
 
 
 
 
 
Software Engineer Intern
Jun 2020 – Jul 2020 Remote, United States

Responsibilities include:

  • Research on the state-of-the-art model for Visual Question Answering Problem
  • Built the end-to-end pipeline based on Kubeflow from data collection, model training, testing to deployment
  • Deployed the model on KFServing, which is based on KNative and provide auto-scaling
  • Developed an Web application for Demo, using React as front end, Django as backend and PostgresSQL as database, which shows the idea that the serving data can also be collected and used for training after reviewing
  • Leader: Ed Henary, Distinguished Member of Technical Staff
 
 
 
 
 
Research Engineer Intern
Oct 2018 – May 2019 Shezhen, P.R.China

Responsibilities include:

  • Done research on the Heterogeneous Face Recognition utilizing adversarial learning and correlation analysis
  • Wrote automatic tools for efficient traning data prepration and easy-to-configure data loaders
  • Repruduced latest algorithms in ICCV/CVPR papers
  • Advicer: Dr. Zhifeng Li, Principal Researcher and Dr. Dihong GONG, Senior Researcher
 
 
 
 
 
Research Assistant Intern
Jul 2018 – Sep 2018 Los Angeles, CA, U.S.

Joining the Lab as a CSST (the Cross-disciplinary Scholars in Science and Technology) program member, my responsibilities include:

  • Proposed a new neural network structure which introduced the concept of a segmentation template to better segment the brain structure of 3D MRI compared to some state-of-the-art neural networks such as 3D-UNet and DeepMedical
  • Our model outperformed existing models with respect to the model size and the prediction accuracy, and thereby was better capable of assisting doctors when they are diagnosing brain images
  • Advicer: Dr. Lei He, Professor

Teaching

Course List

  • CS639 Building User Interfaces (Grader, UW-Madison)
  • CS552 Intro to Computer Architecture (Grader, UW-Madison)
  • CS758 Advanced Topics in Computer Architecture (Grader, UW-Madison)
  • CS302 Artificial Intelligence (2018 Fall, Grader/Developer, SUSTech)
    • Developed an online judge system specialized for some NP-hard problems and operated it for over 150 students. You can find the project details in the #Project Section.
  • CS208 Algorithm Design and Analysis (2018 Spring, Grader/Developer, SUSTech)
    • Developed a online judge program based on VijOS) and operated it.
  • CS302 Operating System (2017 Fall, Peer Mentor, SUSTech)
  • CS202 Data Structure and Algorithm Analysis (2017 Fall, Peer Mentor/Grader, SUSTech)
  • CS205 C/C++ Program Design (2017 Summer, Peer Mentor, SUSTech)
  • GE105 Basic Program Design (2016 Fall, Peer Mentor/Grader, SUSTech)

Responsibilities

  • UW-Madison
    • Grading Students' homework/in-class exercieses (writing scripts or manually) and giving feedback
  • SUSTech
    • Served as a peer mentor during the lab session
    • Scoring the assignments of lowerclassmen manually or with my own automatic scripts
    • Checking assignment plagiarisms by utlizing the Stanford MOSS tools and converting the results into tables or graphs that Teaching Assistants or Professors are easy to understand
    • Sharing my experience on the problems that I solved when I was taking the courses

Projects

Airbnb House Data Analysis

Airbnb House Data Analysis

In this project, I use some classical data analysis methods to analyze the housing data from Airbnb New York. The methods includes Principal component analysis (PCA), K-Means, Self-orgnizaing Map and so on. Please read the report for detailed information.

CARP Online Judge System

CARP Online Judge System

A online platform for student to to submit there code for NP problems and get the solutions judged online

CompareNet

CompareNet

New Deep Neural Network stucture for 3D Medical Image Segmentation

RobotX

RobotX

A Turtlebot robot that can automaticlly explore the space and escape from maze using Simultaneous localization and mapping (SLAM)

Monte Carlo Ray Tracing

Monte Carlo Ray Tracing

A small course project of CS312 Computer Graphics

SNA4Slack

SNA4Slack

A course project of CS304 Object Oriented Design, a webapplication for users to analyze the social networks in chat channels

Meta-Heuristic Algorithm for Capacitated Arc Routing Problem

Meta-Heuristic Algorithm for Capacitated Arc Routing Problem

A course project of CS302 Artificial Intelligence to solve CARP

GNU Privacy Guard based Instant Message Client

GNU Privacy Guard based Instant Message Client

A JavaFX based instant message client using GPG encription standard to send and receive message via SMTP/IMAP protocol

Visible Light Positioning

Visible Light Positioning

A visual light positioning system using three LED lights in a one-meter cube.

Smart Controlled Car

Smart Controlled Car

A smart car with an integration of face tracking, controlled by a bluetooth gravity sensing remote

Contact