Biomedical data science and systems modeling 

The lab's research aims to pioneer the integration of quantitative systems models with machine learning approaches to uncover novel therapeutic strategies for cancer treatment. With a focus on deep learning techniques, we seek to seamlessly integrate large-scale single-cell datasets with patient outcome data, thereby elucidating intricate tumor dynamics and therapeutic responses. 

• Leverage innovative technologies like single-cell sequencing and machine learning
• Unravel the complexities of cancer biology and identify clinically relevant insights

We foster interdisciplinary collaboration through open communication and talent development, ensuring alignment among scientists across various fields. With a commitment to effective project management, our ultimate goal is to translate cutting-edge research findings into measurable improvements in patient outcomes, thereby advancing the forefront of cancer therapeutics.