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.
|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.||Named Entity Recognition||Started|
|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||Started|
|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|