Ahmed Elbasty is a researcher and innovator with experience in computational biology, AI/Ml and biomedical research. His research interests focus on applying machine learning and computational methods to complex biological and medical challenges. As principal investigator, he leads the lab's research direction, oversees ongoing projects, and works to advance the field of Computational Biology.

Saket is a researcher and developer with experience in AI/Ml, machine learning, JavaScript programming, and Arduino-based systems. His technical background spans software development, intelligent algorithms, and hardware integration, allowing him to approach complex challenges from multiple perspectives.

Develops pipelines for analyzing large sequencing datasets and is especially curious about how small genetic differences add up to big biological effects.

Designs machine-learning methods for genomic data and makes sure every model the lab trains is reproducible, well-tested and honestly evaluated.

Studies how networks of genes and proteins interact, using mathematical models to predict how cells respond when those networks are disturbed.

Explores how clinical and molecular data can be combined to better understand disease, with an eye toward tools that could one day help patients.

Assists with protein structure analysis and visualization, and is learning the full research cycle from literature review to presenting results.