Research interests

My research interests focus on developing and applying computational methods in healthcare and mental health, with an emphasis on:

• Biomedical Signal Analysis: Utilizing EEG and ECG data for early detection and prediction of neurological and cardiac conditions.
• Synthetic Data Generation: Employing generative models to augment limited datasets, improving machine learning applications in medical research.
• Explainable AI in Clinical Decision Support: Enhancing transparency and trust in systems that assist healthcare providers in disease detection and patient care.
• Emotion and Sentiment Recognition: Applying natural language processing to analyze patient feedback and social media data, providing insights into patient experiences and mental health.

By concentrating on these areas, I aim to contribute to the development of transparent and effective computational tools that address critical challenges in healthcare and mental health.

Publications

1. Henni, K., Mezghani, N., Mitiche, A., L. Abou-Abbas, & Yahia, A. B. B. (2025). An Effective Deep Neural Network Architecture for EEG-based recognition of emotions. IEEE Access.
2. L. Abou-Abbas, Henni, K., Jemal, I., & Mezghani, N. (2024). Generative AI with WGAN-GP for boosting seizure detection accuracy. Frontiers in Artificial Intelligence, 7, 1437315.
3. L. Abou-Abbas, Hagemeister, N., Ouakrim, Y., Cagnin, A., Laundry, P., Richardson, G., … & Mezghani, N. (2024). Unveiling distinct kinematic profiles among total knee arthroplasty candidates through clustering technique. Journal of Orthopaedic Surgery and Research, 19(1), 479.
4. Henni, K., L. Abou-Abbas, Jemal, I., Mitiche, A., & Mezghani, N. (2024). Imbalance-aware Machine Learning for Epileptic Seizure Detection. In 2024 IEEE 12th International Symposium on Signal, Image, Video and Communications (ISIVC) (pp. 1-5). IEEE.
5. Jemal, I., L. Abou-Abbas, Henni, K., Mitiche, A., & Mezghani, N. (2024). Domain adaptation for EEG-based, cross-subject epileptic seizure prediction. Frontiers in Neuroinformatics, 18, 1303380.
6. L. Abou-Abbas, K. Henni, I. Jemal, A. Mitiche & N. Mezghani (2023). Patient-independent epileptic seizure detection by stable feature selection. Expert Systems with Applications, 232, 120585.
7. L. Abou-Abbas, K. Henni, I. Djemal, & N. Mezghani. (2023, December). Analyzing US Airline Customer Sentiment on Twitter using Multinomial Logistic Regression and Feature Reduction. In 2023 7th IEEE Congress on Information Science and Technology (CiSt) (pp. 265-270). IEEE.
8. L. Abou-Abbas, Jemal, I., Henni, K., Ouakrim, Y., Mitiche, A., & Mezghani, N. (2022). EEG Oscillatory  Power and Complexity for Epileptic Seizure Detection. Applied Sciences, 12(9), 4181.
9. Jemal, I., Abou-Abbas, L., Mitiche, A., & Mezghani, N. (2022). « An Explainable Deep Learning Model for Epileptic Seizure Prediction using EEG Signals ». IEEE Access (2022).
10. L. Abou-Abbas, van Noordt S., Elsabbagh M. (2021). Event Related Potential Analysis Using Machine Learning to Predict Diagnostic Outcome of Autism Spectrum Disorder. Lecture Notes in Computer Science. BIOMESIP 2021, Gran Canaria, Espagne.
11. L. Abou-Abbas, Jemal I., Henni K., Mitiche A., Mezghani N. (2021). Focal and Generalized Seizures Distinction by Rebalancing Class Data and Random Forest Classification. Lecture Notes in Computer Science. BIOMESIP 2021, Gran Canaria, Espagne.
12. L. Abou-Abbas, J.Desjardins, and M. Elsabbagh (2021) “Use of Empirical Mode Decomposition in ERP Analysis to Classify Familial Risk and Diagnostic Outcomes for Autism Spectrum Disorder”. Brain Sciences- March 2021.
13. Jemal, I., Mitiche, A., Abou-Abbas, L., Henni, K., & Mezghani, N. (2021). An Effective Deep Neural Network Architecture for Cross-Subject Epileptic Seizure Detection in EEG Data ; Proceedings of CECNet 2021.  
14. van Noordt, S.J.R., Desjardins, J.A., Huberty, S., Abou-Abbas, L., Webb, S.J., Levin, A., Segalowitz, S.J., Evans, A.C., The BASIS Team, & Elsabbagh, M. (2020) EEG-IP: An international infant EEG data integration platform for the study of risk and resilience in autism and related conditions. Molecular Medicine. 
15. L. Abou-Abbas, C. Tadj, and H. Fersaie Alaie, “A Fully Automated Approach for Babies’ Cry Sounds Segmentation in a Realistic Clinical Environment and Boundary Detection of Corresponding Expiratory and Inspiratory Episodes” -Journal of Acoustical Society of America-2017. 
16. L. Abou-Abbas, C. Tadj, C. Gargour, L. M. Jouibari “Expiratory and Inspiratory Cries Detection using different Signals’ Decomposition Techniques” -JVOICE Journal-2016.
17. H. F. Alaie, L. Abou-Abbas, C. Tadj ” Cry-Based Infant Pathology Classification Using GMMs” -Speech Communication-2016.
18. L. Abou-Abbas, H. Fersaie Alaie, and C. Tadj, “Automatic Detection of the Expiratory and Inspiratory Phases in Newborn Cry Signals,- Biomedical Signal Processing and Control-2015.
19. L. Abou-Abbas, L. M. Jouibari, C. Gargour, C. Tadj “On the use of EMD for Automatic Newborn Cry Segmentation,” in third international conference on advances in biomedical engineering (ICABME15)- Sep 2015.
20. L. Abou-Abbas, H. F. Alaei, and C. Tadj, “Segmentation of Voiced Newborns’ Cry Sounds using Wavelet Packet Based Features,” in Electrical and Computer Engineering (CCECE), 2015 IEEE 28th Canadian Conference, Halifax, Canada on May 2015, pp. 796-800.
21. L. A- Abbas, Zeina Nasser, Pascale Salameh, Zeinab Mansour, L. Abou-Abbas, Lamis Abou Abbas, Youssef Fares, Isabelle Godin “Body Image Dissatisfaction and Psychological Distress among Adults with Excessive Body Weight” International Journal of Health Sciences & Research (www.ijhsr.org) Vol.8; Issue: 4; April 2018. 

Academic degrees

Ph.D. in engineering, Signal Processing and Machine Learning, Ecole de Technologie Supérieure-Montreal, Canada, 2016
M.S., Network of Telecommunication, Ecole de Technologie Supérieure, Montreal, Canada, 2012 (Fast-Track Transition from Master to PhD)
M.S., Network of Telecommunication, Lebanese University and St-Joseph University, Lebanon, 2008
B.E., Electrical and Electronic Engineering- Section: Communication and Computer Engineering, Lebanese University, Lebanon, 2005

Postdoctoral Experience

Postdoctoral Fellowship, Neurology and Neurosurgery department at McGill University and Montreal Neurological Institute, Canada, January 2017 to April 2020
Postdoctoral Fellowship, Science and Technology department at TELUQ University and The University of Montreal Hospital Research Center (CRCHUM), Canada, September 2020 to October 2023

Grants

1. June 2024-September 2024- Fonds de recherche du Québec: Quebec-Lebanon Scientific Research Collaboration (Scientific Mission).
2. June 2022-October 2023 - Mitacs Acceleration grant for the project “Development of a decision-making tool for knee arthroplasty planning using AI methods incorporating functional measures of gait”
3. April 2019 - Transforming Autism Care Consortium (TACC) Quebec Autism Research Training (QART) 
4. Program grant for the project “EEG markers for risk and diagnosis of autism spectrum disorder” - (Declined due to accumulation of other funding) 
5. September 2018-April 2022 - Postdoctoral research grants (B3X) - Quebec Research Fund - Nature and Technologies (FRQNT) for the project “EEG biomarker for risk and diagnosis of autism spectrum disorders”
6. January 2013-December 2016 - Bill and Melinda Gates Foundation grant as part of the Grand Challenges Exploration program for the project “Acoustic analysis of newborn cries to detect serious medical conditions such as heart defects and infections.”