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Analle is a Machine Learning Engineer who is currently working as a research assistant in Mennella's lab. She focuses on integrating the latest AI technologies with electron microscopic data to achieve organelle segmentation.
Prior to joining Mennella's lab, Analle made significant contributions to the field of Arabic natural language processing while working at Samsung R&D. Her work resulted in the publication of three papers and three patents across multiple domains, including machine translation and chatbots. In 2019, she was awarded the Said Foundation scholarship, allowing her to pursue her master's degree at the University of Southampton in the United Kingdom.
Analle's experience is not limited to her work in Menella's lab and her contributions in Samsung. She has also led a data science team that has developed state-of-the-art artificial intelligence models to improve education and Arabic language technologies. Her team's innovative work has led to the creation of machine learning models that analyse, track, and predict students' behaviour, which has led to significant improvements in the learning process.


Research interests:

Analle's research is focused on exploring how AI and ML can enhance human-technology interaction, with a particular focus on the domains of science and natural language processing. In science, she uses AI and ML to analyze complex data, develop algorithms that segment, classify, and extract insights from imaging datasets, and help scientists make better decisions. In natural language processing, she seeks to develop techniques to process and analyze linguistic features and create tools and applications that enable people to interact with computers using natural language input, such as speech recognition systems, chatbots, and language translation software. The ultimate goal of her research is to develop practical applications that significantly improve how people engage with these fields and enhance human-technology interaction.



Key publications: 

Farhan, Wael Younis, Analle Jamal Abuammar, and Ruba Waleed Jaikat. "Electronic device and deep learning-based interactive messenger operation method." U.S. Patent Application No. 16/997,319.
Abuammar, Analle Jamal, et al. "Method and apparatus for processing language based on trained network model." U.S. Patent Application No. 15/929,824.
Farhan, W., Talafha, B., Abuammar, A., Jaikat, R., Al-Ayyoub, M., Tarakji, A. B., & Toma, A. (2020). Unsupervised dialectal neural machine translation. Information Processing & Management, 57(3), 102181.

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