Rate My Professor Fatima Merchant

Fatima Merchant is a Research Professor and Department Chair in the Department of Engineering Technology at the University of Houston, with affiliations in Biomedical Engineering and Electrical and Computer Engineering. She founded and directs the Computational Biology and Medicine Laboratory (CBML) in 2008, an interdisciplinary group advancing engineering applications in medicine and biology. Her research encompasses computational medicine, quantitative biology, multidimensional image acquisition, and tissue engineering. In computational medicine, the laboratory utilizes 3D stereophotogrammetric imaging for breast shape analysis to support surgical planning and outcome assessment in breast reconstruction. The quantitative biology efforts involve digital image analysis and 3D modeling to study nuclear localization of genomic components. Tissue engineering initiatives develop biomaterials that promote cell adhesion and aggregation without requiring complex biochemical modifications. CBML collaborates with MD Anderson Cancer Center and the University of Texas at Austin on these projects.

Merchant's professional experience includes serving as Professor in the Department of Engineering Technology since 2020 and previously as Assistant Professor. She has secured major funding from the National Institutes of Health, acting as Principal Investigator on R01CA286648 for clinical decision-support algorithms enabling interactive design of patient-specific breast molds (2024–2028) and R41CA272122 for 3D image analysis software in breast reconstruction surgical planning (2022–2025). She served as Co-Principal Investigator on R01CA203984 for 3D modeling-based decision support to optimize quality of life post-breast reconstruction (2016–2021). Key publications include the book 'Microscope Image Processing' (2022, co-authored with Kenneth Castleman); 'Exosc9 Initiates SUMO-Dependent lncRNA TERRA Degradation to Impact Telomeric Integrity in Endocrine Therapy Insensitive Hormone Receptor-Positive Breast Cancer' (2023); 'Impact of Implant-Based Breast Reconstruction on Bra Fit' (2023); 'Objective Analysis of Breast Symmetry in Female Patients Undergoing Breast Reconstruction After Total Mastectomy' (2023); 'Review of Quantitative Imaging for Objective Assessment of Fat Grafting Outcomes in Breast Surgery' (2021); and 'High-Performance Computing for SARS-CoV-2 RNAs Clustering: A Data Science-Based Genomics Approach' (2021). Her work influences advancements in breast cancer reconstruction, quantitative imaging, and bioinformatics, enhancing clinical decision-making and patient outcomes.