Profile Wael Ouarda

First Name
Wael

Last Name
Ouarda

Address
Menzel Chaker Road km 0.5, Sfax

Zip code
3038

Biography
Wael Ouarda is an assistant professor of computer science at the Digital Center of Research of Sfax. He received his Ph.D. degree in computer science from the National School of Engineering of Sfax in 2017. He is an active member of the Institute of Electrical and Electronics Engineers (IEEE) since 2012. Wael Ouarda is interested in intelligent systems that operate in large and known domains like Natural Language Processing (NLP), Computer Vision, and Business Intelligence. Most of his research centers around techniques for decision-making. He believes that finding good solutions to these problems requires approaches that cut across many different fields and, consequently, his research draws on areas such as artificial intelligence, decision theory, and operations research. Applications of his research focus on Smart City: Smart Life & Smart Health & Industry 4.0 & Smart Security & Smart Transportation.

Research Interests
Neural Network, Seq2Seq, Natural Language Processing (NLP), Time Series, Computer Vision
Scientific publications
Title Cited by Year
A benchmark tetra-modal biometric score database
LR Haddada, FM Rmida, W Ouarda, IK Kallel, R Maalej, S Masmoudi, ...
Biomedical Signal Processing and Control 98, 106778, 2024

4 2024
S2sdeeparr: Sequence to sequence deep learning architecture for arrhythmia detection under the inter-patient paradigm
W Midani, W Ouarda, H Ltifi, MB Ayed
Procedia Computer Science 246, 792-801, 2024

3 2024
Deciphering the Complexities of COVID‐19‐Related Cardiac Complications: Enhancing Classification Accuracy With an Advanced Deep Learning Framework
N Benameur, A Sassi, W Ouarda, R Mahmoudi, Y Arous, MA Mohammed, ...
International Journal of Imaging Systems and Technology 34 (5), e23189, 2024

1 2024
AfriDial: African Dialect Model based on Deep Learning for Sentiment Analysis
A Sassi, J Tonga, S Poaty, S Steve, DIA Adjid, M Cherif, W Ouarda
2024 International Wireless Communications and Mobile Computing (IWCMC …, 2024

0 2024
DeepArr: An investigative tool for arrhythmia detection using a contextual deep neural network from electrocardiograms (ECG) signals
W Midani, W Ouarda, MB Ayed
Biomedical Signal Processing and Control 85, 104954, 2023

70 2023