Anthony Mayo

Dr. Anthony Mayo is a Senior Grant Facilitator in the Office of Research and Sponsored Programs and an Instructor of Biostatistics and Computer Methodology in the Department of Cell Biology. Dr. Mayo began his career at the University of Medicine and Dentistry of New Jersey (UMDNJ), overseeing post-award grants and contract operations for the New Brunswick, Camden, and Stratford campuses. Anthony served as Director of Administration for Digital Media and Special Projects at the Health Science Libraries during the institutional merger between UMDNJ and Rutgers, the State University of New Jersey. 

He earned his PhD in Biomedical Informatics from Rutgers, The State University of New Jersey, and has accumulated extensive experience employing technology to establish structural and compliance controls that enhance operational efficiency and departmental success. As Director of Faculty Affairs at Rutgers New Jersey Medical School, Dr. Mayo was the chief architect on the development of the Faculty Affairs Toolbox System (FACTS), a faculty information system that tracks and manages the lifecycle of faculty employed within the New Jersey Medical School System. The FACTS system and its modules are currently in use at Rutgers New Jersey Medical School, School of Dental Medicine, and School of Nursing.

Dr. Mayo was recognized by the Veterans Affairs as an “Innovator and Subject Matter Expert” for the development of a “Beta Project” that was used for the Veterans Affairs’ national billing templates for their work with other national Academic Institutions. Dr. Mayo authored “Trends in Substance-Related Emergency Department Visits and Treatment Outcomes in Individuals with Substance Use Disorders in the United States,” a biomedical informatics study employing survival analysis in clinical evaluation and treatment assessment for patients living within various phases of addiction. The approach provides an extensive examination of the application of Kaplan–Meier plots and Cox regression to model relapse in addiction, relapse risk, treatment dropout, and incorporates repeated measures to handle multiple, time-varying events.