Nizhum Rahman is an applied mathematician whose research combines mathematical modeling, computer simulation, and data science to better understand complex biomedical systems. His work focuses on questions such as how cancer cells interact with one another and with immune cells, why tumors respond differently to treatment, and how biological materials are transported within cells. He develops models that connect processes occurring at the level of individual cells with larger patterns of disease progression and treatment response.
A central goal of his research is to create computational models that are both biologically grounded and capable of producing useful, testable predictions. He combines differential-equation models and agent-based simulations with interpretable machine learning, which can identify important patterns in complex data while helping researchers understand why a prediction is made. His recent work examines therapy response in HER2-heterogeneous breast cancer, including how cellular diversity, changes in cancer-cell behavior, and treatment sequencing influence therapeutic outcomes. He has also developed mathematical models of axonal transport to study mechanisms related to the movement of large cargo within nerve cells.
Through MIDAS, Nizhum aims to strengthen his expertise in interpretable machine learning, scientific AI, uncertainty quantification, biomedical data analysis, and reproducible computational research. He also hopes to build collaborations across mathematics, data science, medicine, biology, and engineering. His long-term objective is to develop data-informed mathematical tools that improve understanding of disease, support the design of more effective therapies, and contribute to more personalized approaches to treatment.