
Dr. Abdelkader Baggag
Senior Scientist
Associate Professor
Dr. Abdelkader Baggag
Senior Scientist
Associate Professor
Educational Qualifications
PhD in Computer Science
MSc in Applied Mathematics
Entity
Qatar Computing Research Institute
College of Science and Engineering
Divison
Information & Computing Technology
Biography
Dr. Abdelkader Baggag is a Senior Scientist at Qatar Computing Research Institute and an Associate Professor in the ICT Division of the College of Science and Engineering, where he teaches Generative AI Foundations. Dr. Baggag is an expert in Machine Learning and holds a PhD in Computer Science from the University of Minnesota, USA. Before joining QCRI, he was at McGill University and then a tenured Associate Professor at Laval University in Canada.
Dr. Baggag worked at leading HPC research centers in the USA, e.g., CRI at Purdue, ICASE at NASA Langley Research Center in VA, and MSI in Minnesota. Dr. Baggag’s research is in AI and RL, focusing on multimodal LLMs. He has worked on AI and ML applications that include AI for wearable data analytics, traffic prediction and missing data imputation, and AI for resilient smart cities.
PhD in Computer Science
University of Minnesota, United States
2003
MSc in Applied Mathematics
Ecole Polytechnique of Montreal, Canada
1993
Ingenieur d'Etat (Bachelor of Engineering)
Ecole Nationale Polytechnique of Algiers, Algeria
1990
- Image understanding in LLMs
- Mass fact editing in LLMs
- Watermarking of LLMs
- Multimodal fusion for heterogeneous biomedical data
AI Senior Scientist
Qatar Computing Research Institute, Hamad Bin Khalifa University
2014 - Present
Associate Professor
College of Science and Engineering, Hamad Bin Khalifa University
2017 - Present
Associate Professor
Computing and Engineering, Laval University, Quebec, Canada
2010 - 2017
Associate Professor
Computer Science, Louisiana Tech University, United States
2008 - 2010
Assistant Professor
Computing and Engineering, McGill University, Quebec, Canada
2005 - 2008
Senior High-Performance Computing Analyst
Consortium CLUMEQ on High-Performance Computing, McGill University, Quebec, Canada
2003 - 2008
Visiting Scholar
Computing Research Institute, Purdue University, United States
2001- 2003
Assistant Professor
Computer Science, Hampton University, United States
2000 - 2001
Research Fellow
Institute for Computer Applications in Science and Engineering (ICASE), NASA Langley Research Center, United States
1995 - 2001
Baggag, A., & Saad, Y. (2025). Deep learning, transformers, and graph neural networks: A linear algebra perspective. Numerical Algorithms Journal.
Abdelaal, Y., Aupetit, M., Baggag, A., & Al Thani, D. (2024). Exploring the applications of explainability in wearable data analytics: A systematic literature review. Journal of Medical Internet Research (JMIR).
Abdelaal, Y., Aupetit, M., Baggag, A., Bashir, M., & Al-Thani, D. (2024). How much wearable data is enough for the utility and trust of augmented artificial intelligence systems? A scenario-based interview with medical professionals. International Journal of Human-Computer Interaction.
Salkovic, E., Baggag, A., Salem, A. G. R., & Bensmail, H. (2023). OutSingle: A novel method of detecting RNA-seq aberrant genes using the optimal hard threshold for singular values. Bioinformatics, 39(4).
Coskun, M., Baggag, A., & Koyuturk, M. (2021). Fast computation of Katz index for efficient processing of link prediction queries. Data Mining and Knowledge Discovery.
- Ministère de l’Éducation, du Loisir et du Sport, Quebec – Scholarships program in Science and Engineering: only 8 professors were recruited under this program. Dr. Baggag was one of them.
- Scholarship from the Ministry of Higher Education of Algeria to pursue graduate studies in Canada, 1990 – This scholarship is awarded to the top 20 from the École Nationale Polytechnique. Dr. Baggag was ranked first in the exam nationwide.
- Ranked first nationwide in the “Examen du Baccalauréat” section mathematics, 1985.
- Received by the (late) President of Algeria, Chadli Bendjedid, and awarded a scholarship.