Hi, my name is Yunong. I work for Centiment.io as a data scientist since Oct 2016 after graduating from NYU Center for Urban Science + Progress. I am interested and specialized in data cleaning, mungling, modeling and visualization over spatial-temporal data.

Techinical Skills:

• Data Mining: Python, R, C++
• Web Development: HTML, CSS, Bootstrap, d3.js, leaflet.js, Flask
• Big Data: Hadoop, Spark
• Cloud Computing: AWS EC2
• GIS: ArcGIS
• SQL: PostegreSQL, MySQL
• Others: MATLAB, OpenRefine, AWS SQS, LaTeX, Microsoft Office Applications

Working Experience:

Research Assistant, NYU mHealth MapCorps

• Assisted 7 research scientists and 4 engineers to conduct mobile Health project
• Set up working environment (LAMP, GIT, R) in AWS EC2 instances for the team
• Fetched data from AWS SQS queue and updated them to PostreSQL database
• Translated the research volunteer recruiting program into Python from R
• Stitched pictures to make panoramic photographs by Python and Shell scripts
• Blurred human faces in panoramic photographs with OpenCV

Projects:

WiFind

• Developed a system for collecting, analyzing and visualizing WiFi signal data with team of 6
• Rendered raster map tiles of WiFi signals on server using Django framework
• Detected blind spots of WiFi signal for Red Hook Initiative using our system
• Designed and coded a mobile-friendly website to introduce the project and accommodate the map UI with Bootstrap, AngularJS and Leaflet.js

Twitter Primary

• Made a web app for analyzing realtime tweets about 2016 poll candidates
• Extracted keywords and sentiment of real-time tweets via Python NLTK
• Croned analysis program and fed analysis result on Heroku using Flask
• Connected and visualized raw data and analysis result on a dashboard by d3.js

Explore Empty Taxis Problem in NYC

• Filtered all trip records of empty taxis from TLC Taxi Trip Data (20GB) by Spark
• Estimated the routes of empty taxis’ trips through R-tree by Hadoop
• Deduced the taxi zones with most empty taxis for different hours in a day and different days of a week
• Visualized empty taxis’ distribution using choropleth map via CartoDB

Evaluate the Sentiment Intensity of Words Used on Yelp’s Review

• Cleaned and munged Yelp’s business information and customer review data
• Implemented and optimized Pegasos algorithm for sentiment analysis in Python
• Designed an algorithm to evaluate the intensity level of popular words used to express sentiments for different types of restaurants
• Concluded the most notable customer concerns for each type of restaurant based on the sentiment score of reviews

Other Experiences:

Process Engineer Internship, DuPont

• Collaborated with 5 engineers in team to identify the risks in production process
• Conducted calculations referring to mass transfer and fluid mechanics problems
• Researched technical information on heat exchangers, flow meters and pumps
• Studied DuPont standard operation process and SHE management
• Edited the high risk activities managing process of the plant

Education Backgound:

New York University:

• M.S. in Applied Urban Informatics

University at Buffalo, The State University of New York:

• B.S. in Chemical Engineering
• B.A. in Mathematics