Projects

Deep learning model to classify music into 10 genres using Convolutional Neural Networks (CNNs) and TensorFlow. The model analyzes mel spectrograms (visual representations of audio) to identify musical patterns unique to each genre.

ML classification model optimized for clinical screening, achieving 100% sensitivity in heart disease detection through precision threshold optimization.

Using PANDA and gene regulatory network analysis to identify sex-specific pathways in glioblastoma vs low-grade glioma progression.

Designed AI architecture to estimate geographical trends of Antimicrobial Resistance spread and predict future resistance patterns by location.

Computational analysis of liquid biopsies from 54 cancer patients, identifying 128 CHIP-derived variants.

Designed and optimized 5+ molecular models investigating emission spectra and structure-activity relationships for cytotoxicity research.

Analytical framework for methylated gene markers in cervical cancer early detection using QM-MS-PCR.

Leveraging metrics of DNA methylation-based epigenetic instability for pan-cancer early detection assay development.