It is our pleasure to inform you that Dr. Esra Akbas is the recipient of Junior faculty Award in the Natural Science pillar. It was awarded by College of Arts and Science at Oklahoma State University. The Junior Faculty Mentor award goes to a faculty member who has inspired the less-experienced around them by passing on their accumulated knowledge and experience.
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 Big Data.
Paper Link: https://ieeexplore.ieee.org/document/9671766
Presentations slides for this publication: SP06209_Presentation.pptx
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 2021 IEEE International Conference on Big Data (IEEE BigData 2021).
Paper Link: https://ieeexplore.ieee.org/document/9671532
Presentations slides for this publication: BigD626.pptx
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: https://www.nature.com/articles/s41598-021-00017-y
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 Big Data 2021.
Paper Link: https://ieeexplore.ieee.org/document/9671842
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.
Paper Link: https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9679951
Presentations slides for this publication:520.pptx
We are glad to inform that our research paper titled "Predicting Drug-Drug Interactions Using Meta-path Based Similarities" has been accepted at IEEE CIBCB 2021.
Paper Link: https://ieeexplore.ieee.org/document/9562802
Presentations slides for this publication:CIBCB_slide.pptx
Dr. Esra Akbas, Director of DELab, has been awarded a $174K National Science Foundation (NSF) grant to carry on fundamental research for the project entitled “Structure-aware Graph Compressing: From Algorithms to Applications”.This project aims at developing novel graph compression (summarization) methodologies that facilitate efficient analysis of large graphs and advancing a wide spectrum of graph-related applications. This project will: 1) explore the spatial locality property of graphs by taking the structural information from different aspects, including similarity of nodes and cohesiveness of subgraphs; 2) develop the corresponding novel structure-aware compression methods to tackle the challenges brought by large real-world networks; and 3) build more tailored architectures with proposed compression methods for various problems, including network embedding and community search and evaluate them on real-world applications such as link prediction, node classification, anomaly detection, and community detection. Its outcomes will be disseminated through publications, tutorials, workshops, as well as open-source tools, code, and datasets.
We are glad to inform that our research paper titled "Proximity-Based Compression for Network Embedding" has been accepted at Frontiers in Big data.
Paper Link: https://www.frontiersin.org/articles/10.3389/fdata.2020.608043/full
Presentations slides for this publication:Frontiers_Network_Embedding.pptx
