Tarek Naous

Tarek Naous
American University of Beirut | AUB · Department of Electrical and Computer Engineering

Master of Engineering in Electrical and Computer Engineering

About

12
Publications
21,892
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88
Citations
Introduction
Tarek Naous is currently pursuing an ME degree in Electrical and Computer Engineering (ECE) at the American University of Beirut (AUB). He is a Graduate Research Assistant at the Machine Intelligence Development Lab (AUB MIND LAB). His research interests include machine learning, deep learning, wireless communications, and artificial intelligence for communications.
Education
August 2020 - May 2022
American University of Beirut
Field of study
  • Electrical and Computer Engineering
August 2015 - June 2020
Beirut Arab University
Field of study
  • Communications and Electronics

Publications

Publications (12)
Preprint
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Clustering algorithms are one of the main analytical methods to detect patterns in unlabeled data. Existing clustering methods typically treat samples in a dataset as points in a metric space and compute distances to group together similar points. In this paper, we present a wholly different way of clustering points in 2-dimensional space, inspired...
Preprint
Full-text available
Enabling empathetic behavior in Arabic dialogue agents is an important aspect of building human-like conversational models. While Arabic Natural Language Processing has seen significant advances in Natural Language Understanding (NLU) with language models such as AraBERT, Natural Language Generation (NLG) remains a challenge. The shortcomings of NL...
Conference Paper
Full-text available
In a world where many overlapping 2G, 3G, and 4G electromagnetic radiation sources already exist, concerns regarding the potential increase in these radiation levels following the roll-out of 5G networks are growing. The deployment of 5G is expected to increase power density levels drastically, given the limitations of mmWave communications that im...
Article
Full-text available
With the prevalence of breast cancer among women and the shortcomings of conventional techniques in detecting breast cancer at its early stages, microwave breast imaging has been an active area of research and has gained momentum over the past few years, mainly due to the advantages and improved detection rates it has to offer. To achieve this outc...
Conference Paper
Full-text available
With the growth and wide variety of available data, advanced processing, and affordable data storage, machine learning is witnessing great attention in finding optimized solutions in various fields. Machine learning techniques are currently taking a major part of the ongoing research, and expected to be the key player in today's technologies. This...
Article
Full-text available
This paper presents the use of machine learning (ML) to facilitate the design of dielectric-filled Slotted Waveguide Antennas (SWAs) with specified sidelobe levels. Conventional design methods for air-filled SWAs require the simultaneous solving of complex equations to deduce the antenna’s design parameters, which typically requires further manual...
Article
A Recommender System (RS) is an integral part of present-day leading web services, such as YouTube, Amazon, Netflix, and many others. Modern RSs are challenged to go beyond their traditional role of predicting user preferences to efficiently provide reliable, carefully personalized, and highly accurate recommendations. This paper thoroughly explore...
Conference Paper
Full-text available
Breast Microwave Imaging (BMI) has emerged as a viable alternative to conventional breast cancer screening techniques due to its favorable features and a higher rate of detection. This paper presents a deep learning framework consisting of deep neural networks with convolutional layers to facilitate the process of tumor detection, localization, and...
Article
Full-text available
The increasing complexity of Intelligent Transportation Systems (ITS), that comprise a wide variety of applications and services, has imposed a necessity for high-performance Modern Hardware Devices (MHDs). The performance challenge has become more noticeable with the integration of Machine Learning (ML) techniques deployed in large-scale settings....
Preprint
Full-text available
The increasing complexity of Intelligent Transportation Systems (ITS), that comprise a wide variety of applications and services, has imposed a necessity for high-performance Modern Hardware Devices (MHDs). The performance challenge has become more noticeable with the integration of Machine Learning (ML) techniques deployed in large-scale settings....
Conference Paper
Full-text available
Conversational models have witnessed a significant research interest in the last few years with the advancements in sequence generation models. A challenging aspect in developing human-like conversational models is enabling the sense of empathy in bots, making them infer emotions from the person they are interacting with. By learning to develop emp...
Article
Full-text available
This paper presents a focused and comprehensive literature survey on the use of machine learning in antenna design and optimization. An overview of the conventional computational electromagnetics and numerical methods used to gain physical insight into the design of the antennas is first presented. The major aspects of machine learning are then pre...

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Projects

Projects (3)
Project
Explore developing recommender systems to benefit from recent advancements, such as Blockchain technology, and their integration within modern services in smart cities.
Project
The advancement in modern vehicular technology has enabled the emergence of a plethora of services and applications within smart cities. This project includes investigations on quality and performance aspects of Connected and Autonomous Electric Vehicles (CAEVs) and Intelligent Transportation Systems (ITS).