Research outputs per year
Research outputs per year
Personal profile
Summary
A passionate and driven PhD student in artificial intelligence and deep learning, with a strong background in computer science and mathematics. My research focuses on developing novel and efficient algorithms for solving complex and real-world problems, such as image recognition, natural language processing, and recommendation systems. Eager to apply my skills and knowledge to new challenges and opportunities in the field of AI.
Education/Academic qualification
Master of Science, Dual Degree: M.Sc. in Internet of Things, Université de Franche-Comté
Sept 2020 → Jul 2021
Award Date: 31 Jul 2021
MEng, M.Sc. in Engineering - Computer Science Major, Université catholique de Lille
Sept 2018 → Jul 2021
Award Date: 31 Jul 2021
External positions
Deep Learning Research Assistant, Faculty of Law
Jan 2023 → Jul 2023
Natural Language Processing Research Assistant, Faculty of Business
Jan 2022 → Jul 2022
Research Internship: IRM denoising, Femto-ST
May 2021 → Aug 2021
Internship: iOS App Development, DPointGroup
May 2020 → Sept 2020
Keywords
- Q Science (General)
- Artificial Intelligence
- Deep Learning
- Machine Learning
- Natural Language Processing
Research output
- 1 Conference contribution
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A comparative analysis of GPT-3 and BERT models for text-based emotion recognition: performance, efficiency, and robustness
Boitel, E., Mohasseb, A. & Haig, E., 1 Feb 2024, Advances in Computational Intelligence Systems: Contributions Presented at the 22nd UK Workshop on Computational Intelligence (UKCI 2023), September 6–8, 2023, Birmingham, UK. Naik, N., Jenkins, P., Grace, P., Yang, L. & Prajapat, S. (eds.). Springer, p. 567–579 (Advances in Intelligent Systems and Computing; vol. 1453).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Open Access
Prizes
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Best Paper Award
Boitel, Enguerrand (Recipient), Mohasseb, Alaa (Recipient) & Haig, Ella (Recipient), Sept 2023
Prize: Prize (including medals and awards)