Mondal Lab


About the Lab


The Mondal Lab was established in 2019 as a human subject basic science research laboratory. It focuses on a precision medicine approach to biomarker discovery using human biospecimens collected from heart failure, heart transplantation, mechanical circulatory support, and other cardiac surgery patients, including minimally invasive robotic-assisted cardiac surgeries as well as conventional bypass graft surgeries. The Mondal Lab is dedicated to advancing the understanding of cardiovascular diseases through innovative research. Another exciting research focuses on molecular insight into the current heart transplantation in the United States through a strategy to extend the current warm ischemic limit through pharmacological reconditioning of brain death and circulatory death donor hearts. 

The Mondal Lab is home to the largest biorepository core within the Division of Cardiothoracic Transplantation and Circulatory Support, containing thousands of biospecimens such as blood, urine, and tissue collected from patients over time. The research team consists of a postdoctoral associate, a clinical resident, and several undergraduate, graduate, postgraduate, Ph.D. and medical students. The lab has proactively sought collaborations with top-notch professionals from various fields, including physicians, biomedical engineers, computer scientists, and machine learning specialists. 

The lab places a high value on fostering and contributing to an inclusive, safe, and diverse environment within a highly diverse institution that caters to a major metropolitan area, known to be one of the most diverse in the nation. The Mondal lab is currently enrolling medical students through the SOAR and SMAR program. The students will have the opportunity to be involved with cutting-edge wet laboratory molecular biology experiments, gain knowledge through weekly educational lectures by Dr. Mondal on human subject research, brainstorm on innovative projects, and have opportunities to take part in multi-omics data analysis, clinical data curation and analysis, bioinformatics analysis, and modern multi-modal machine learning analysis.