RESEARCH
Her research centers on single-cell perturbation analysis and the development of context-specific biological networks to advance drug discovery applications. Reem Alsulami is particularly interested in graph-based machine learning approaches that integrate biological structure and dynamics to model cellular responses to genetic and chemical perturbations. Her work aims to enhance both the interpretability and predictive performance of computational models in systems biology and precision drug development.

BIOGRAPHY
Reem Alsulami earned her Bachelor’s degree in Computer Science from King Abdulaziz University in Jeddah, Saudi Arabia, with a minor in the Intelligent Systems track. She then pursued a Master’s degree at King Abdullah University of Science and Technology (KAUST), where she conducted research under the supervision of Professor Xin Gao in the Structural and Functional Bioinformatics Group. Her thesis, titled “Deconfounding and Generating Embeddings of Drug-Induced Gene Expression Profiles Using Deep Learning for Drug Repositioning Applications,” focused on developing deep learning frameworks to model transcriptional responses for drug discovery. Building on this foundation, she is currently a Ph.D. student in the Living Systems Laboratory at KAUST, working under the supervision of Professor Jesper Tegnér.