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RESEARCH & PROJECTS
RESEARCH INTERESTS
RESEARCH INTERESTS
Natural Language Processing (NLP)
Natural Language Generation (NLG), Understanding (NLU)
Machine Learning
Data Mining
Information Retrieval (IR) and Extraction (IE)
Intelligent Tutoring Systems (ITS)
Intelligent Tutoring Robots (ITR)
Human Robot Interaction (HRI)
Educational Data Mining (EDM)
Application of AI and Machine Learning in Energy Management Systems.
RESEARCH & PROJECTS
RESEARCH & PROJECTS
Infectious Disease Analysis over Social Network Data
Infectious Disease Analysis over Social Network Data
Our Project idea is to detect epidemic outbreak using social media, In terms of disease detection prior to serious issues emerging. After various research analysis we found that common traditional methods have not been able to detect potential threats quickly. With this project, we aim to explore content-based big data like Twitter's enterprise data to detect such disease outbreaks over time.
Our main goal is to utilize many NLP features like, sentiment orientation, mood, multi-lingual and/or multi-modal features, along with disease ontology, to analyze twitter data, so our system can further detect the sense of our audience in a particular location and warn any signal for potential disease outbreak before it spreads.
According to recent statistics, depression and suicide are on a rise in the United States and elsewhere. In order to resolve this issue, synonymous to various current approaches, we propose a Multi-modal Robot Interaction Framework in this paper, which will act as an extension to current HRI Systems to further identify studied signs of depression from various data-acoustic features like image, video, speech, text, and in general multi-modal data. One of the recent technology that we plan to introduce in our resolution, is the use of social-humanoid robots (in our case, Pepper by SoftBank Robotics) to detect early signs of depression via the power of Natural Language and Multi-Modal Interactions.
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