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Manal Kalkatawi

Manal Kalkatawi completed her M.S. in 2011 and her PhD in 2017 from King Abdullah University of Science and Technology (KAUST), in Computer Science focusing on Bioinformatics, Data mining, and Machine/Deep learning.

Biography

​I am an assistant professor at King Abdulaziz University (KAU), Faculty of Computing and Information Technology, Information Technology department. I completed my M.S. in 2011 and my PhD in 2017 from King Abdullah University of Science and Technology (KAUST), in Computer Science focusing on Bioinformatics, Data mining, and Machine/Deep learning. 


I have extensive experience in genome analysis, genomic signals recognition, and genomic sequences data extraction and processing. I have been heavily involved in designing methods and supporting systems using machine/deep learning algorithms to be applied to genomic signals recognition, genome annotation, and genome assembly. I worked on human (Homo sapiens), mouse (Mus musculus), cow (Bos taurus), fruit fly (Drosophila melanogaster) and mousear cress (Arabidopsis thaliana) genomes. Moreover, I have developed and been involved in some bioinformatics tools: DeepGSR, Dragon PolyA Spotter, INDIGO, BEACON, and Omni-PolyA.


Also, I have worked on applying deep learning in Arabic sentiment analysis and recognition of breast cancer images. Details can be found at: https://scholar.google.com/citations?user=YJgNij8AAAAJ&hl=en


All sessions by Manal Kalkatawi

Contributions to Digital Health in Low and High Level
02:00 PM

Digital health (DH) is an important topic these days since it provides a lot of help to the smart world that we are approaching. This study contributes to digital health on different levels by introducing methods based on machine learning (ML).

Manal Kalkatawi

Manal Kalkatawi completed her M.S. in 2011 and her PhD in 2017 from King Abdullah University of Science and Technology (KAUST), in Computer Science focusing on Bioinformatics, Data mining, and Machine/Deep learning.

Details