Understanding the receptors and molecular pathways that facilitate viral entry into human cells is crucial for developing novel therapeutic approaches. Computational methods offer a powerful platform for identifying host-pathogen interactions by using sequence- and structure-based data. The major focus of the lab is to develop machine-learning models for predicting viral entry receptors and other human interactomes. Through this, the lab aims to uncover both common and virus-specific receptors, as well as the molecular pathways viruses use to invade host cells. We also interest in capturing virus-induced host responses using the data generated from advanced techniques such as high-throughput sequencing and mass spectrometry, and converting it into a public repository. Besides, the lab has a strong interest in identifying antiviral compounds through drug repurposing and AI-driven drug design, with the goal of contributing to the discovery of effective therapeutic solutions for combating viral infections