Michal A. Mankowski

Michal A. Mankowski, PhD, is an Assistant Professor in the Department of Surgery at NYU Grossman School of Medicine, where he conducts impactful research in transplantation medicine. His work bridges clinical needs with data science and policy innovation, focusing on improving equity and efficiency in organ allocation systems.

His research interests center on transplantation bioinformatics, HLA immunogenetics, and health equity, with a strong emphasis on kidney and liver allocation. He investigates how electronic health records and large language models can be leveraged—and secured—within clinical transplant settings. His work also explores the impact of patient comorbidities, such as delirium, on transplant access and outcomes.

Recent publications reveal a strong trend toward integrating data science, machine learning, and policy modeling in organ transplantation. His research spans technical immunogenetic analysis (e.g., eplet mismatch) to ethical and operational challenges in national allocation systems. He frequently collaborates with leaders in transplant epidemiology and bioinformatics, contributing to high-impact journals such as American Journal of Transplantation and Nature Medicine.

Scientific Awards:
No awards are listed in the provided text.

Advising and Grants:
While no specific students or grants are listed, his role as an Assistant Professor and active publication record suggest involvement in mentoring graduate or medical students and securing research funding in transplantation informatics and policy. His collaborations indicate participation in multi-institutional research teams and likely grant-funded projects related to organ allocation and AI in medicine.

Labs and Teams:
Dr. Mankowski is part of a robust transplant research ecosystem at NYU Grossman School of Medicine, collaborating extensively with teams focused on transplant outcomes, immunogenetics, and health services research. He contributes to projects involving large databases such as the Scientific Registry of Transplant Recipients (SRTR) and Epic Cosmos, suggesting integration within data-driven clinical research networks.