Zixin(Grace) Kong

413-***-**** ac7ijy@r.postjobfree.com Git: https://github.com/ZixinKong

EDUCATION

University of Massachusetts Amherst

M.S(expected) in Computer Science GPA: 3.60 Sep 2016-Feb 2019 Relevant coursework: Neural Networks, Machine Learning, Nature Language Processing, Algorithms for Data Science, Advanced Software Engineering, Distributed & Operating Systems, Database Design & Implementation, Human Computer Interaction Central China Normal University Wuhan, China

B.E in Electrical and Computer Engineering GPA: 3.50 June 2016 Relevant coursework: C Language Programming, Data Structure, Object-Oriented Programming Honors: China National Computer Rank Examination Certificate of Level 2 -- C language SKILLS

● Programming Languages: Python, Java, JavaScript, SQL, HTML/CSS, C++, Matlab, R

● Tools: Node.js, AngularJS, MySQL, GitHub

● Operating Systems: Linux, Windows, OSX

PROFESSIONAL EXPERIENCE

GEETEST Network Technology Co., Ltd Wuhan, China

Web Application Developer Intern at DeepKnow Dept. May 2017-Aug 2017

● Contributed to backend server using Node.js and MySQL database

● Responsible for designing ‘event’ module on demand, which identifies type of fraud detection online

● Cooperated with front-end team for the performance of user APIs and tuning the UX/UI design

● Data collecting, cleaning & Provided data to data analysis team as database for further machine learning techniques

● Provided real-time support to clients and troubleshooting PROJECTS

Distracted Driver Detection using Deep learning methods Jan 2018-May 2018 Final project for Neural Network class

● Applied transfer learning to solve image classification problem

● Used 3 pre-trained models: VGG 16, Xception, Inception V3 as fixed feature extractor in the baseline; fine-tuning these 3 pre- trained model and a mix model for performance optimization; tested over 50 times for each model

● Data augmentation and specific train-validation set split in the data preprocessing step, CAM visualization and hard negative analysis in the evaluation part

Evaluation of Discrimination Measurements using Themis-ml Jan 2018-May 2018 Final project for Advanced Software Engineering class

● Extended and used “themis-ml”, an existing open-source fairness-aware machine learning Python library

● Implemented 3 discrimination measurements: impact ratio, e-lift ratio and odds ratio

● Measured and mitigated discriminatory patterns in machine learning algorithms, specifically decision making system Breast cancer prescreen test web application (https://app.breastcancer.top/home) Jan 2018-May 2018 Final project for Human Computer Interaction class

● Negotiated and cooperated to design the web application

● Contributed in building web backend using NET Core, creating backend database using SQL server NLP

● Completed front-end user interface by AngularJS