Diversity in Life Sciences

Initiatives to Enhance Diversity, Equity & Inclusion in Science

 

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Ivana Parker, PhD
Assistant Professor
University of Florida

Dr. Ivana Parker is a Fulbright Scholar, and Assistant Professor in the J Crayton Pruitt Family Department of Biomedical Engineering at the University of Florida. With over a decade of experience in HIV research spanning prevention, comorbidities, and diagnostics,  her work has had global impact within Africa, Asia, and the Americas. Recognized by receipt of the NIH DP-1 Director’s Pioneer Award, her lab at the University of Florida explores questions at the intersection of global health, immunology, and women’ s health and aims to identify novel therapeutic targets to decrease HIV risk. Dr. Parker aims to improve health outcomes for underserved and vulnerable communities through research and advocacy. This impact is amplified by educating and empowering the next generation (or students) to create change through their own innovation and research.

Before coming to UF, Dr. Parker was awarded a Fulbright to the University of Cape Town in South Africa, where she investigated mechanisms of maternal to child transmission of HIV. For her postdoctoral work, Dr. Parker received an ASM/CDC postdoctoral fellowship in Infectious Disease Microbiology and Public Health.  At the CDC, she evaluated the impact of HIV prevention techniques on diagnostic assay accuracy and identified trends to optimize assay design. Dr. Parker received her PhD in Bioengineering from Georgia Tech, and she received numerous awards while there, including the NSF graduate research fellowship and the NIH Cell and Tissue Engineering Trainee. She also received a Whitaker Grant to develop artificial aortic valves in Cape Town, South Africa and facilitated set-up of a lab in Addis Ababa, Ethiopia. Dr. Parker earned her BS in mechanical engineering from the University of Florida in 2009.

Research Area(s):

Bioengineering
Infectious Disease

Research Keywords:

# Vaginal Microbiome
# HIV Prevention
# Host-Pathogen Interactions
# Bacterial Vaginosis
# Machine Learning

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