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Meet the Team

Joseph Gaut, MD, PhD – Founder

Joseph Gaut, MD, PhD – Founder

Dr. Gaut is an expert renal pathologist with decades of contribution to national and international efforts to improve biopsy evaluation. Dr. Gaut leads the ongoing clinical development and validation of Trusted Kidney’s deep learning algorithm. At Washington University School of Medicine in St. Louis, he is the Ladenson Professor of Pathology and Immunology, as well as Division Chief of Anatomic and Molecular Pathology and Section Head of Renal Pathology, Donor Organ Evaluation, and Genitourinary Pathology. Dr. Gaut’s group was the first to develop a deep learning method to segment and quantify percent global glomerulosclerosis on donor kidney biopsy frozen section whole slide images.

S. Joshua Swamidass, MD, PhD – Founder

S. Joshua Swamidass, MD, PhD – Founder

Dr. Swamidass is an Associate Professor of Pathology and Immunology at Washington University in St. Louis. He is a leader in deep learning and computational approaches to solve problems at the intersection of chemistry, biology and medicine. His computational group designed and developed Trusted Kidney’s deep learning approach to whole slide images for donor kidney biopsy. 

 Victoria Swamidass, MBA – CEO

Victoria Swamidass, MBA – CEO

Ms. Swamidass leads the development of Trusted Kidney for commercial use. Since 2018, she has led the engineering effort to create an intuitive, powerful application for pathologists to access the deep learning approach to kidney biopsy. Ms. Swamidass holds 18 years of experience in healthcare technology, with deep expertise in physician engagement. In past roles, she was responsible for the product development and market launch of multi-million dollar healthcare programs.

 Mike Blackford, Director of Experience

Mike Blackford, Director of Experience

Mr. Blackford designs each component of Trusted Kidney’s user interface (UI)
with the pathologist in mind. He holds nearly two decades of UI experience,
creating intuitive interfaces for complex, data-driven platforms and applications. He manages highly technical design needs while empathizing with the user to create cutting-edge interactions for complex data solutions. With both design and technical skills, Mike holds a BFA and senior level experience with several billion-dollar corporations including digital marketing, design, product development, and creation of fully accessible WCAG AA websites.

© 2025 by Trusted Kidney

Info@trustedkidney.com • BioGenerator Labs, Suite 300 - 4340 Duncan Avenue • St Louis, MO 63110

Trusted Kidney is for Research Use Only and is not for use in diagnostic procedures.

1 Mohan S., et al. “Factors leading to the discard of deceased donor kidneys in the United States.” Kidney Int. 2018:94:187-198.

​2  Azancot MA, Moreso F, Salcedo M, Cantarell C, Perello M, Torres IB, et al.: The reproducibility and predictive value on outcome of renal biopsies from expanded criteria donors. Kidney Int, 85: 1161-1168, 2014 10.1038/ki.2013.461
3  Marsh JN, Liu TC, Wilson PC, Swamidass SJ, Gaut JP. “Development and validation of a deep learning model to quantify glomerulosclerosis in kidney biopsy specimens.” JAMA Netw Open. 2021:4(1):e2030939.
 

SOURCES:

Deep Learning Global Glomerulosclerosis in Transplant Kidney Frozen Sections”, Marsh JN, Matlock MK, Kudose S, Liu TC, Stappenbeck TS, Gaut JP, Swamidass SJ., IEEE Trans Med Imaging. 2018 Dec;37(12):2718-2728. doi: 10.1109/TMI.2018.2851150

Gaut J, Marsh J, Blackford M, Swamidass V, Berry R, Swamidass S. Deployment of a Deep Learning Model to Assist Pathologists with Donor Kidney Biopsy Evaluation. 2021. Poster presented at the Digital Pathology Association annual conference.

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