Tarek Naous

Machine Learning PhD Student
Graduate Research Assistant
Georgia Institute of Technology, Atlanta, Georgia, United States

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I'm a first-year PhD student in Machine Learning at Georgia Tech working on multilingual natural language processing under the supervision of Prof. Wei Xu. Previously, I was a visiting researcher at Qatar University. I did my Master's degree in Electrical and Computer Engineering (ECE) at the American University of Beirut (AUB) where I worked as a graduate research assistant with the Machine Intelligence Development Lab (AUB MIND LAB). I received a BE in Communications and Electronics Engineering from Beirut Arab University (BAU) in Jun 2020.

Research Interests:

In general, my areas of research are machine learning and natural language processing. More specifically, I am interested in the following topics:

  • Learning with limited data

  • Multilingual learning

  • Neural text generation and decoding

  • Open-domain dialog systems

  • Clustering algorithms

Previously, I've worked on applied machine learning to problems in wireless communication technology, healthcare, and other fields.

Selected Papers:
(Full list in Publications page)


Clustering Plotted Data by Image Segmentation
Tarek Naous, Srinjay Sarkar, Abubakar Abid, James Zou
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), New Orleans, USA, Jun. 2022
[The CVF] [arXiv]


Machine Learning-Aided Design of Dielectric-Filled Slotted Waveguide Antennas with Specified Sidelobe Levels
Tarek Naous, Amen Al Merie , Salwa K. Al Khatib, Mohammed Al Husseini, Raed M. Shubair, Hilal M. El Misilmani
IEEE Access, Mar. 2022
[IEEE Xplore] [PDF]



Radiation Analysis in a Gradual 5G Network Deployment Strategy

Ahmad M. El Hajj, Tarek Naous

IEEE 5G World Forum (5GWF), Bangalore, India, Sep. 2020
[IEEE Xplore] [PDF] [Press Article] [Press Video]

A Survey on Antenna Designs for Breast Cancer Detection Using Microwave Imaging
Hilal M. El Misilmani, Tarek Naous, Salwa K. Al Khatib, and Karim Y. Kabalan
IEEE Access, vol. 8, pp. 102570-102594, 2020
[IEEE Xplore] [PDF]