activity
20202026
most citedMulti-Dialect Arabic BERT for Country-Level Dialect Identification

46 citations · 50 across the 17 of their papers we have counts for

collaborators

18 papers

eess.SY2026

An Open Synthetic Test System for the Jordanian Transmission Grid

Muhy Eddin Zater, Bri-Mathias Hodge

Open synthetic test systems are essential for reproducible power system research, yet the available cases represent almost exclusively North American and European grids. No open tr…

eess.SY2026

Power Grid Infrastructure for AI Data Centers

Amir Sajadi, Muhy Eddin Za'ter, Maria Vabson +2

This article addresses recent advances in artificial intelligence, which have set off an astounding race among technology frontiers to build large data centers. It provides insight…

eess.SY2026

Empirical Assessment of Time-Series Foundation Models For Power System Forecasting Applications

Muhy Eddin Za'ter, Bri-Mathias Hodge

Accurate forecasting of electric load and renewable generation is essential for reliable and cost effective power system operations. Recent advances in transformer based and founda…

eess.SY2026

A Multi-Stage Warm-Start Deep Learning Framework for Unit Commitment

Muhy Eddin Za'ter, Anna Van Boven, Bri-Mathias Hodge +1

Maintaining instantaneous balance between electricity supply and demand is critical for reliability and grid instability. System operators achieve this through solving the task of…

eess.SY2026★ 1 cited

Optimal County-Level Siting of Data Centers in the United States

Maria Vabson, Muhy Eddin Zater, Amir Sajadi +2

Data centers are growing rapidly, creating the pressing need for the development of critical infrastructure build out to support these resource-intensive large loads. Their immense…

cs.LG2025

Residual Correction Models for AC Optimal Power Flow Using DC Optimal Power Flow Solutions

Muhy Eddin Za'ter, Bri-Mathias Hodge, Kyri Baker

Solving the nonlinear AC optimal power flow (AC OPF) problem remains a major computational bottleneck for real-time grid operations. In this paper, we propose a residual learning p…

cs.LG2025

Learning a Generalized Model for Substation Level Voltage Estimation in Distribution Networks

Muhy Eddin Za'ter, Bri-Mathias Hodge

Accurate voltage estimation in distribution networks is critical for real-time monitoring and increasing the reliability of the grid. As DER penetration and distribution level volt…

eess.SY2025

Leveraging Multi-Task Learning for Multi-Label Power System Security Assessment

Muhy Eddin Za'ter, Amir Sajad, Bri-Mathias Hodge

This paper introduces a novel approach to the power system security assessment using Multi-Task Learning (MTL), and reformulating the problem as a multi-label classification task.…

cs.LG2024

Semi-Supervised Multi-Task Learning Based Framework for Power System Security Assessment

Muhy Eddin Za'ter, Amirhossein Sajadi, Bri-Mathias Hodge

This paper develops a novel machine learning-based framework using Semi-Supervised Multi-Task Learning (SS-MTL) for power system dynamic security assessment that is accurate, relia…

cs.CL2024★ 1 cited

Evaluation of Semantic Search and its Role in Retrieved-Augmented-Generation (RAG) for Arabic Language

Ali Mahboub, Muhy Eddin Za'ter, Bashar Al-Rfooh +3

The latest advancements in machine learning and deep learning have brought forth the concept of semantic similarity, which has proven immensely beneficial in multiple applications…

cs.AI2024★ 1 cited

A New Benchmark for Evaluating Automatic Speech Recognition in the Arabic Call Domain

Qusai Abo Obaidah, Muhy Eddin Za'ter, Adnan Jaljuli +4

This work is an attempt to introduce a comprehensive benchmark for Arabic speech recognition, specifically tailored to address the challenges of telephone conversations in Arabic l…

eess.SY2022

Modelling of a DC-DC Buck Converter Using Long-Short-Term-Memory (LSTM)

Muhy Eddin Za'ter

Artificial neural networks make it possible to identify black-box models. Based on a recurrent nonlinear autoregressive exogenous neural network, this research provides a technique…

cs.SD2022

Arabic Text-To-Speech (TTS) Data Preparation

Hala Al Masri, Muhy Eddin Za'ter

People may be puzzled by the fact that voice over recordings data sets exist in addition to Text-to-Speech (TTS), Synthesis system advancements, albeit this is not the case. The go…

cs.CV2022★ 1 cited

Bench-Marking And Improving Arabic Automatic Image Captioning Through The Use Of Multi-Task Learning Paradigm

Muhy Eddin Za'ter, Bashar Talafha

The continuous increase in the use of social media and the visual content on the internet have accelerated the research in computer vision field in general and the image captioning…

eess.SY2022

Online Gradient Descent for Flexible Power Point Tracking Under a Highly Fluctuating Weather and Load

Muhy Eddin Za'ter, Sandy Yacoub Miguel, Majd Ghazi Batarseh

The increasing electricity demand and the need for clean and renewable energy resources to satisfy this demand in a cost-effective manner, imposes new challenges on researchers and…

cs.CL2021

sarcasm detection and quantification in arabic tweets

Bashar Talafha, Muhy Eddin Za'ter, Samer Suleiman +2

The role of predicting sarcasm in the text is known as automatic sarcasm detection. Given the prevalence and challenges of sarcasm in sentiment-bearing text, this is a critical pha…

cs.CL2020

SPARTA: Speaker Profiling for ARabic TAlk

Wael Farhan, Muhy Eddin Za'ter, Qusai Abu Obaidah +3

This paper proposes a novel approach to an automatic estimation of three speaker traits from Arabic speech: gender, emotion, and dialect. After showing promising results on differe…

cs.CL2020★ 46 cited

Multi-Dialect Arabic BERT for Country-Level Dialect Identification

Bashar Talafha, Mohammad Ali, Muhy Eddin Za'ter +5

Arabic dialect identification is a complex problem for a number of inherent properties of the language itself. In this paper, we present the experiments conducted, and the models d…