NIAID Emerging Leaders in Data Science Fellows

Current Fellows

Fausto Andres Bustos Carrillo

Fausto received both a PhD in Epidemiology and an MA in Biostatistics from the University of California, Berkeley; an MS in Epidemiology from Harvard University; and a dual Bachelor’s degree in Political Science and Human Biology from Stanford University.

Fausto started his fellowship with the Office of Data Science and Emerging Technologies (ODSET) where he used PubMed to understand the depth, usage, and gaps of data science methods across NIAID priority topics. For his second rotation, Fausto worked with the Epidemiology and Population Studies Unit and the Epidemiology and Data Management Unit in the Division of Intramural Research (DIR) to analyze immunological, serological, and epidemiological data for immunodeficient and healthy participants before and after being vaccinated against SARS-CoV-2 to understand the duration and effect of vaccination on individuals with immunodeficiencies. Fausto is currently working on co-authoring multiple manuscripts related to this study. For his third rotation, he worked with the Parasitology and International Programs Branch (PIPB) in the Division of Microbiology and Infectious Diseases (DMID) to identify which datasets relevant to climate change and health were curated by different governmental and non-governmental agencies, as well as what privacy or other concerns limited their use for climate change research.

Linh Shinguyen

Linh received his MS in Data Science from Vanderbilt University and his Bachelor’s degree in Health Promotion from the University of Georgia.

His first rotation was with the Division of Allergy, Immunology, and Transplantation (DAIT) during which he developed a natural language processing pipeline to collect and mine text data from research performance progress reports. Linh then worked with the Bioinformatics Research Branch (BRB) in the Division of Clinical Research (DCR) to characterize differences between individuals who developed post-acute sequalae of SARS-CoV-2 (PASC) and those who did not among persons infected with COVID-19 and developed a predictive model to distinguish characteristics between COVID-infected individuals who developed PASC and those that did not. For his third rotation, Linh is working with the Laboratory of Clinical Immunology and Microbiology (LCIM) in the Division of Intramural Research (DIR) to explore a novel methodology of combing different data modalities to characterize individuals with multiple sclerosis (MS).

Rahul Subramanian

Rahul received his PhD in Ecology and Evolution from the University of Chicago and his Bachelor’s degree in Electrical Engineering from Princeton University.

Rahul worked with the Epidemiology Branch in the Division of AIDS (DAIDS) for his first rotation, during which he characterized the DAIDS data landscape by examining what types of data variables are measured by cohort study networks, clinical trial networks, and electronic medical record systems and assessing the accessibility of each network. For his second rotation, Rahul investigated to what extend individuals with multiple exposures to COVID-19 develop immunity against other strains of COVID-19 and quantified the breadth of this immunity using antigenic cartography and antibody landscapes with the Viral Epidemiology and Immunity Unit in the Division of Intramural Research (DIR), resulting in a co-authored manuscript. Rahul then rotated with the Human Immunology Section of the Vaccine Research Center (VRC) where he analyzed Phage-Immunoprecication sequencing data to quantify individuals’ prior exposure to monkeypox infection and/or smallpox vaccine.

Diego Seira

Diego completed his MS in Statistics, graduate certificates in Big Data Analysis and Applied and Computational Mathematics, and his Bachelor’s in Mathematics with an Actuarial Concentration and a minor in Spanish at the University of Texas at El Paso.

He expanded an existing Python package for survival analysis to address time-varying ROC curves and Schoenfeld residuals for Cox Regression and the weighted mean rank method for estimating incident/dynamic AUC during his first rotation with the Biostatistics Research Branch (BRB) in the Division of Clinical Research (DCR). After his time with the BRB, Diego worked with the Therapeutics Research Program (TRP) in the Division of AIDS (DAIDS) to assess COVID-19 hospitalization rates and risk factors with the aim of optimizing the clinical trial design for a new COVID-19 outpatient treatment. For Diego’s third rotation, he is analyzing how persons with immune deficiencies respond to COVID-19 vaccines with the Epidemiology and Population Studies Unit and the Epidemiology and Data Management Unit  in the Division of Intramural Research (DIR).

Previous Fellows

  • Chris Barousse (Previously: Shin)
  • Kelly Carey
  • Sydney Foote
  • Byron Gaskin
  • Meghan Hartwick
  • Sara Jones
  • Camille Lake
  • Lisa Mayer
  • Leo Meister
  • Komi Messan
  • Niamh Mulrooney
  • Jennifer Rokhsar
  • Mark Rustad
  • Kyle Webb
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