C++, Java, Python, JavaScript, MySQL, MongoDB

Hao Huang

551-***-**** ******@***.***

*** ********** ****, ****** ****, NJ 07310

New York University, Courant Institute - New York, NY May. 2019 Master of Science, Computer Science, Overall GPA: 4.0/4.0 Coursework: Operating System, Fundamental Algorithm, Programming Language, Database Sun Yat-sen University - Guangzhou, China July. 2017 Bachelor of Engineering, Electronic Information Science and Technology, Overall GPA: 3.76/4.0 Honors: 2 consecutive years of SYSU Outstanding Scholarship SKILLS

Programming: C++, Java, Python, JavaScript, MySQL, MongoDB Web Development: node.js, Django, React, Bootstrap, jQuery, Vue.js, HTML5, CSS3 Frameworks & Tools: Git, Hadoop, Spark, MapReduce, TensorFlow PROJECTS

Weather Forecast Browser – React, Redux, Sparklines March. 2018 - April. 2018

Built web application displays weather forecast of given cities with React and Redux

Developed Ajax based frontend with Webpack, React and Redux for middleware and reducers

Utilized Sparklines to display the weather information and GoogleMap API to show the location of each city Node.js based Chat Room – node.js, socket.io, jQuery, MongoDB Feb. 2018 - March. 2018

Implemented web server with JavaScript, node.js and MongoDB for online chat room

Developed frontend view with jQuery and mustache, MVC backend with node.js, and stored data into MongoDB database

Utilized socket.io to achieve real-time communication and deployed on Heroku Text Mining in Java – Java, NLP, TF-IDF, k-means Jan. 2018 – Feb. 2018

Tokenize, stemming and lemmatize words in articles utilized Stanford CoreNLP library

Built TF-IDF vector for each article using NER and sliding windows to merge words that are of same meaning

Implemented k-means and k-means++ algorithms in Java to clusterize articles and visualized result using Python matplotlib Content Management System – Python, MySQL, Jinja2, Vue.js, AWS Nov. 2017 – Jan. 2018

Developed async web framework using Python aiohttp that support user authentication, articles and comments publication

Built ORM using metaclass and utilized aiomysql to achieved async connection with MySQL database

Implemented MVC backend with Jinja2, frontend view with Vue.js and UIkit, and deployed on AWS with Nginx Recurrent Models of Visual Attention – Tensorflow, Neural Network, LSTM March. 2017 – May. 2017

Developed novel recurrent neural network that capable of selecting and processing important regions with high resolution

Achieved non-differentiable model training using reinforcement learning method to learn the task-specific policy

Examined the model on MNIST and transformed MNIST databases and achieved over 98% accuracy WORK EXPERIENCE

Intelligence Science and System Lab (iSEE) – Guangzhou, China Aug. 2015 – May. 2017 Research Assistant

Assisted in a team of medical image processing doing image classification using machine learning algorithms

Developed system to segment the single cells in a large image of each specimen for further analysis

Designed Deep Convolutional Neural Networks (CNNs) to classify the Human epithelial type 2 (HEp-2) cells

Improved classification performance by identifying faults in samples and using similar images from other datasets

Analyzed report of each experiment and trained network to achieve 87% accuracy PUBLICATION

HEp-2 Specimen Classification via Deep CNNs and Pattern Histogram Hongwei Li, Hao Huang, Wei-Shi Zheng, Xiaohua Xie, Jianguo Zhang International Conference on Pattern Recognition 2016 (ICPR2016)

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