Raiyan Ali

Analyzed microbiome, resistome and phage–bacteria dynamics to correlate with disease severity and developed pipelines for resistome profiling; processed single-cell datasets from demultiplexing to downstream inference.

Maintained trained AI models and ML processes for clinical decision support (charak-1), annotated tumor images and curated patient data to support database development and clinical workflows.

Developed an AI model for diagnosis and classification of ovarian cancer and implemented a consensus algorithm that improved XGBoost performance by ~3% through combined feature selection.

Integrated RNA-Seq with machine learning to predict SARS-CoV-2 infection by preprocessing raw data, identifying biomarkers and building models using Random Forest, logistic regression and neural networks.

Grade: 9.48 CGPA

Activities and societies: E-Cell club member; attended workshops and conferences on cancer research and computational methods.

Completed an M.Sc. in Bioinformatics with coursework and projects in sequencing data analysis, multi-omics integration, and machine learning for clinical applications.

Grade: 55.4%

Completed a B.Sc. (Hons.) in Chemistry with foundational coursework supporting later specialization in bioinformatics.

Grade: 7.6

Completed diploma programs in Computer Science Applications, Business Accounting and DTP with multilingual training.

Grade: 59.4%

Completed higher secondary education with focus on Physics, Chemistry, and Biology.

Grade: 9.2 CGPA

Completed secondary school education.