Shamsuddeen Adamu

Multi-task adversarial autoencoder for functional genomic element generation with preserved biophysical properties

The Multi-Task Adversarial Autoencoder (MT-AAE) is introduced, a hybrid generative framework that integrates adversarial regularization with auxiliary functional and biophysical objectives to enforce structured latent representations and position MT-AAE as an effective framework for biologically constrained genomic seq...

FIFT: Feature Importance-Guided Fairness Testing for machine learning software

Results indicate that global feature importance, used as an active search signal rather than a post-hoc diagnostic, improves both the effectiveness and the efficiency of individual fairness testing.

An explainable generative AI framework for detecting low-rate API-based DDoS attacks in cloud environments