Welcome!

The fusion of computer science and molecular biology has opened new avenues for decoding the complex language of life. Artificial intelligence (AI) is now driving rapid advancements in the study of biological systems. Algorithms can analyze vast omic data, detect patterns, and simulate molecular interactions that once required decades of laboratory work. Machine learning models, particularly those in deep learning, can predict protein structures, identify gene-disease associations, and model the effects of genetic mutations with increasing accuracy. These AI-driven insights are particularly powerful in precision medicine, where they help tailor therapies based on an individual’s genetic makeup. By integrating domain-specific knowledge, computational models are revealing previously unknown interactions, advancing our understanding of fundamental biological mechanisms, and paving the way for novel treatments.

Fusion of Computer Science and Molecular Biology (by Copilot).

About me

I develop novel AI and ML algorithms to advance scientific discovery and understanding of biological systems. I would largely characterize my current research as AI for Molecular Biology. My recent interests hybridize concepts and ideas from machine learning, deep learning, language models, natural language processing, and bioinformatics. My research objective is to advance the language models situated in domain knowledge to leverage content, structure and organization of diverse data sources.