Esra Akbas
Associate Professor Computer Science- Education
B.S., Computer Science, Tobb University Of Economics And Technology, 2010
M.S., Computer Science, Bilkent University, 2012
Ph.D., Computer Science, Florida State University, 2017
- Specializations
Data mining, Graph mining, Social Network Analysis, Information Networks, Machine learning
- Biography
Esra Akbas is an assistant professor in the department of the Computer Science at Oklahoma State University. She received her Ph.D. in computer science from Florida State University. Her broad research interest is the development of algorithms for, mining and analyzing large-scale data with particular emphasis on text and graph-structured data. She mainly focuses on social networks and health data as the application area. She received 2 NSF funding for her research. She has published and reviewed numerous referenced papers in international conferences and journals. She has been supervising many high school, undergraduate, and graduate students in her DELab. She is also the recipient of the Junior faculty award in the Natural Sciences piler at OSU.
- Publications
M. E. Aktas, Thu Nguyen, Sidra Jawaid, Rakin Bin Riza, Esra Akbas, ”Identifying critical higher-order interactions in complex networks”, Nature Scientific Reports, 11, 21288, https://doi.org/10.1038/s41598- 021-00017-y, 2021
Farhan Tanvir*, Muhammad Ifte Islam*, and Esra Akbas. ”Predicting Drug-Drug Interactions Using Meta-path Based Similarities”, 18th IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), 2021, pp. 1-8, doi: 10.1109/CIBCB49929.2021.9562802.
Khaled Mohammed Saifuddin*, Muhammad Ifte Islam*, Esra Akbas ”Drug Abuse Detection in Twitter- sphere: Graph-Based Approach” IEEE International Conference on Big Data, Accepted, 2021.
Mingming Peng, Max Khanov***, Saikeerthi Reddy Madireddy*, Hongmei Chi, Esra Akbas, Gokila Do- rai, ”DECADE – Deep Learning Based Content-hiding Application Detection System for Android”, IEEE International Conference on Big Data, Accepted, 2021.
Khaled Mohammed Saifuddin*, Max Kahanov***, Esra Akbas, Jason Beaman, ”Effects of COVID-19 on individuals in Opioid Addiction Recovery”, 19th IEEE International Conference on Machine Learning and Applications (ICMLA), Accepted, 2021
Bri Bumgardner**, Farhan Tanvir*, Khaled Mohammed Saifuddin*, Esra Akbas ”Drug-Drug Interaction Prediction: a Purely SMILES Based Approach”, IEEE International Conference on Big Data, Accepted, 2021.
Mehmet Emin Aktas, Sidra Jawaid, Ebony Harrington, Esra Akbas ”Influential nodes detection in complex networks via diffusion Fr ́echet function” , 19th IEEE International Conference on Machine Learning and Applications (ICMLA), Accepted, 2021
Mehmet Aktas, Thu Nguyen, Esra Akbas, ”Homology Preserving Graph Compression”, 19th IEEE Inter- national Conference on Machine Learning and Applications (ICMLA), Accepted, 2021.
Mehmet Aktas, Esra Akbas, ”Graph Classification via Heat Diffusion on Simplicial Complexes,” in IEEE Access, vol. 9, pp. 12291-12300, 2021, doi: 10.1109/ACCESS.2021.3050662.