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 |
|---|---|---|
Motion and torso-guided frame distillation for optimized learning-based fall detection: K. Guemri et al.K Guemri, W Ouarda, K BoukadiThe Visual Computer 42 (6), 236, 2026 |
0 | 2026 |
Improving Arabic sentiment analysis across context-aware attention deep model based on natural language processingAH Ombabi, W Ouarda, AM AlimiLanguage Resources and Evaluation 59 (2), 639-663, 2025 |
11 | 2025 |
Robust assessment Fall Detection Architecture: Intra/Inter-Subject and Cross-Dataset EvaluationK Guemri, Y Chasseray, I Megdiche, W Ouarda, K Boukadi, E Lamine2025 IEEE/ACS 22nd International Conference on Computer Systems and …, 2025 |
0 | 2025 |
DEES-breast: deep end-to-end system for an early breast cancer classificationI Ben Ahmed, W Ouarda, C Ben Amar, K BoukadiEvolving Systems 15 (5), 1845-1863, 2024 |
15 | 2024 |
Age-API: are landmarks-based features still distinctive for invariant facial age recognition?A Abbes, W Ouarda, YB AyedMultimedia Tools and Applications 83 (26), 67599-67625, 2024 |
7 | 2024 |
