Personal information
Full name: Qiuyi Yang
User name: Qiuyi
Organization memberships
Not a member of any organization.
Awards
First 1000 volunteers
Volunteer background
Education: Master's on Master of science (University of Wisconsin-Madison)
LinkedIn profile
Volunteer availability
Start date: July 9, 2020
End date: Aug. 31, 2020
Hours available per week: 10
Volunteering interests
No stated preferences.
Skills
Skill
Beginner
Intermediate
Expert
Python
Computer Science (Algorithms)
Java
Ruby
PHP
Clojure
Haskell
JavaScript
C/C++/C#
Data in Text Files
Data in Relational Databases
SQL
Data > 1TB
Text Data (NLP)
Multimedia Data (Video or Audio)
Network/Graph Data
Data from Sensors
Data Visualization
Social Science (Economics, Sociology, etc.)
Experience working on real-world problems using data
Experimental Methods (RCTs, A/B testing, etc.)
Data Analysis
Time Series Models
Decision Trees
Unsupervised models
Random Forests
SVMs
Graphical models
Causal inference
Neural Networks / Deep Learning
Semi-Supervised models
Regression Discontinuity
Instrumental Variables
Matching (e.g., Propensity Score Matching )
Stata
SAS
SPSS
R
Matlab
Julia

Volunteer projects

Project name Organization name Social impact area Project summary Task name Task status
Cloud Enabled Social Media Analytics Framework for Crisis Management Artificial Intelligence and Data Engineering (AIDE)Lab Education This project aims to develop a cloud-based computing framework that will systematically monitor, collect and integrate disaster and crisis-related data streams from diverse social network channels, and turn them into actionable intelligence in a knowledge-base for intelligent inferencing, crisis handling, and decision making. The key components of the proposed framework are three: First, the collection of multilingual and multimodal data (text, audios, videos, images, and location information or other sensor-data) and their conversion into a unified machine-understandable dynamic knowledge-base. Second, the application of Natural Language Processing (NLP), Data Mining, Machine Learning, and Artificial Intelligence techniques for automatic identification, prediction, and detection of any type of crisis or disaster using the unified knowledge-base from the previous stage. 3) Third, the development of an interactive dashboard visualization to facilitate crisis monitoring and management. Project scoping done_all Completed