My primary domains of work/interest include Natural Language Processing, Information Retrieval and Machine Learning. I am a professional devoted towards research, with the motivation to contribute to a future with better technology.
Personal information
Full name: Kanav Mehra
User name: kanav-mehra
Organization memberships
Not a member of any organization.
Awards
First 1000 volunteers
1+ task completed
Volunteer background
Volunteer availability
Start date: None
End date: None
Hours available per week: None
Volunteering interests
No stated preferences.
Skills
Skill
Beginner
Intermediate
Expert
Python
C/C++/C#
Computer Science (Algorithms)
SQL
Data in Text Files
Data in Relational Databases
Text Data (NLP)
Data Visualization
Experience working on real-world problems using data
Data Analysis
Neural Networks / Deep Learning
Semi-Supervised models
Random Forests
SVMs
Decision Trees
Volunteer projects
| Project name | Organization name | Social impact area | Project summary | Task name | Task status |
|---|---|---|---|---|---|
| GraphLab and IDDP Mapping the Spread | The George Washington University School of Engineering and Applied Science | Education | Dr. Howie Huang’s GraphLab, together with Dr. David Broniatowski and IDDP (Institute for Data, Democracy, and Politics) researchers, is working to map the prevalence and spread of attitudes towards COVID-19 on online social media platforms. They are examining repositories of social media data related to the epidemic, starting as early as January 2020, to map the spread of discussion, information, and attitudes towards the disease and the public health response to the outbreak. | Project scoping | Pending review |
| Amphan: analyzing experiences of extreme weather events using online data | International Water Management Institute | Education | Cyclone Amphan made landfall in South Asia on May 20, 2020. It was the most damaging storm in the history of the Indian Ocean, rendering hundreds of thousands of people homeless, ravaging agricultural lands and causing billions of dollars in damage. How were people affected by the storm? What were the responses of individuals, governments, corporates and NGOs? How was it covered by local, national and international media, as opposed to individuals' accounts? Who has created the dominant narratives of Cyclone Amphan; and whose voices go unheard? We aim to use online data -- such as Twitter posts, news headlines and research publications -- to analyze people's experiences of Cyclone Amphan. | Text Analysis | done_all Completed |