Dr. Meriem Romaissa Boubakeur earned her Master's-level Engineering degree in Computer Science in 2015 from the École Nationale Supérieure d'Informatique in Algiers, Algeria. She received her Ph.D. in Computer Science and Technology at Chongqing University of Posts and Telecommunications in 2021. From 2022 to 2024, she worked as R&D Manager at QuanBio, leading efforts in applying AI to enhance medical devices for cardiovascular disease prediction. Since October 2024, Dr. Boubakeur has been a Postdoctoral Fellow at CenBRAIN Neurotech.

Dr. Boubakeur’s research focuses on leveraging adaptive AI models in brain science, with a particular emphasis on EEG-based predictive tasks. She is also engaged in bio-signal processing, addressing data sparsity, and exploring robust learning techniques for medical predictions. Her work aims to improve the adaptability and generalizability of AI-driven healthcare solutions.

[1]   Boubakeur, M. R., & Wang, G. (2021). Self-relative evaluation framework for EEG-based biometric systems. Sensors, 21(6),2097.

[2]   Boubakeur, M. R., Wang, G., Liu, K., & Benatchba, K. (2019). Evaluation of Identity Information Loss in EEG-Based Biometric Systems. In Brain Informatics: 12th International Conference, BI Dec 2019, Haikou, China.