Congratulations to Ph.D. student Daniel Rodriguez who was awarded a Fellowship from NIH Type 1 Diabetes T32 Training Grant under the supervision of Dr. Ruogu Fang.

Daniel’s research employs cutting-edge machine learning and artificial intelligence (AI) techniques to delve into the intricate relationship between Type 1 Diabetes (T1D) and Alzheimer’s Disease and related dementia (ADRD). Leveraging invaluable data from the UK Biobank and Clinical Trial data, Daniel aims to uncover critical insights in this area. In this study, Daniel will analyze the association between T1D and the incidence of ADRD, as well as the conversion rate from cognitive normalcy to mild cognitive impairment (MCI) and dementia. Furthermore, Daniel’s research will extend to investigating the influence of T1D on the outcomes of transcranial Direct Current Stimulation (tDCS)-paired cognitive training as a means to enhance cognitive abilities in older adults.

Trainees appointed to the T1D T32 will be immersed in laboratory investigational experiences and non-laboratory research related to the study of T1D. Trainees will select one mentor from the College of Medicine and one mentor from the College of Engineering, and will benefit from the trans-disciplinary cross-fertilization provided by faculty with basic science, translational investigation, and clinical training backgrounds. The T1D T32 involves four research clusters which will inform trainees’ understanding of T1D: Immunology & Genetics, Stem Cell Biology & Therapeutics, Clinical & Translational Research, and Biomedical Engineering. Once a trainee has established their mentor relationships, they will draft their Individual Training Plan (ITP) with their mentors’ input and the oversight of the T32 Executive Committee and the T32 Program Directors. The ITP must outline the trainee’s career goals, coursework, and training related activities.