Advancing computational biology through AI-powered drug discovery, antimicrobial resistance prediction, and sustainable biotechnology innovation.
Our interdisciplinary team combines artificial intelligence, computational biology, and biotechnology to address critical global health challenges.
Graph neural networks and digital twin technology for predicting therapeutic candidates against drug-resistant pathogens.
Machine learning models predicting compound activity against WHO high-priority multidrug-resistant bacteria.
Advanced molecular simulation and protein-ligand interaction modeling for next-generation drug design.
Metabolic engineering and biosurfactant production for environmentally sustainable biotechnology applications.
Novel neural architectures designed specifically for biological sequence analysis and molecular property prediction.
Curated datasets and predictive dashboards for antimicrobial resistance surveillance and outbreak monitoring.
Partner with our research team to advance AI-driven drug discovery, antimicrobial resistance prediction, and sustainable biotechnology.