Data Engineering Lab's broad research areas are data mining and machine learning. Specifically, we works on graph (network) mining, text mining, and social network analysis. One aspect of our research is developing novel effective and efficient graph processing methods. Another aspect is to conduct biomedical knowledge mining to track public health issues in social networks. Moreover, we aim to discover significant, unprecedent knowledge from biomedical entities' interaction.
What is Network Analysis?
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Research paper accepted at REU 2021 Symposium at IEEE International Conference on Big Data We are glad to inform that our research paper with title "Drug-Drug Interaction Prediction: a Purely SMILES Based Approach" has been accepted at REU 2021 Symposium at IEEE International Conference on...
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Research Paper accepted at IEEE BigData 2021 We are glad to inform that our research paper titled "Drug Abuse Detection in Twitter-sphere: Graph-Based Approach" has been accepted at BigGraphs 2021, which will be held in conjunction with the...
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Research paper accepted at Scientific Reports We are glad to inform that our research paper titled "Identifying critical higher-order interactions in complex networks" has been accepted at Scientific Reports. Paper Link:...
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Research Paper accepted at IEEE BigData 2021 We are glad to inform that our research paper titled "DECADE - Deep Learning Based Content-hiding Application Detection System for Android" has been accepted at IEEE PSBD 2021, special session of IEEE...
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Research Paper accepted at IEEE ICMLA 2021 We are glad to inform that our research paper titled "Effects of COVID-19 on individuals in Opioid Addiction Recovery" has been accepted at IEEE ICMLA 2021.
