Personal information
Full name: Shreya Kaushik
User name: shreya.kaushik
Organization memberships
Not a member of any organization.
Awards
No awards received yet.
Volunteer background
Education: Bachelor's on Computer Science (None)
LinkedIn profile
Volunteer availability
Start date: None
End date: None
Hours available per week: 6
Volunteering interests
No stated preferences.
Skills
Skill
Beginner
Intermediate
Expert
Python
SQL
Data in Text Files
Data in Relational Databases
Data > 1TB
Data Visualization
Experience working on real-world problems using data
Data Analysis

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)Research Center 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. Text Preprocessing Started
Cloud Enabled Social Media Analytics Framework for Crisis Management Artificial Intelligence and Data Engineering (AIDE)Research Center 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 Started