After KAUST Academy
Waleed works at HUMAIN and represented HUMAIN at LEAP26. Earlier, Waleed placed third at the HPC/AI hackathon run by King Khalid University and the National Center of Meteorology in September 2024 and published a paper on Arabic sentiment analysis at ICNLP 2025.
Summer project
Bioinformatics Specialization · Cohort 2024
Development of Deep Learning Solutions for 4D Image Segmentation of Spatial Omics Data
Understanding the intricate dynamics of chromosomal organization within multicellular systems is critical for advancements in medical and biological sciences. Our research focuses on the development and deployment of high-precision deep learning models for 4D image segmentation, aimed at unveiling genomic architecture over developmental periods in model organisms such as C. elegans. By integrating advanced convolutional neural networks (CNNs) and transformers, we significantly improve the accuracy and efficiency of segmentation tasks, particularly through the utilization of Micro-SAM. In our study, we compare the performance of Micro-SAM with traditional segmentation methods and alternative deep learning models like Med-SAM. Preliminary results demonstrate substantial enhancements in 3D segmentation accuracy and computational efficiency with Micro-SAM, surpassing traditional techniques. These improvements facilitate a deeper understanding of cellular, nuclear, and chromosomal structures, providing valuable insights into their development. Our findings underscore the impact of deep learning in precise data analysis, highlighting the importance of high-resolution datasets for accurate model performance.
With KAUST Academy
- Cohort 2024
University of Toronto · Bioinformatics Summer Program
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