Lalitha Pranathi Pulavarthy is a master's student in Health Informatics and a Graduate
Research Assistant. A dental surgeon by training, she transitioned into informatics to focus
on Electronic Health Records and data analytics. Her work in EHR systems includes developing
SMART on FHIR applications to support interoperability and workflow improvement, as well as
gaining hands-on experience with OpenEMR through installation and deployment. She is
interested in and works with FHIR, HL7, SNOMED CT, and RxNorm to design data pipelines and
support efficient clinical data use.
Her research background includes usability and human-centered studies through IRB-approved
protocols, survey design, and qualitative and quantitative analysis. She has worked with EEG
systems for neurophysiological data collection, including electrode setup, monitoring, and
data quality checks. Her data analytics projects span imaging and predictive modeling. She
contributed to research on breast cancer risk prediction using medical imaging, a project
that received second prize at the Emory Datathon, and has also developed predictive models
for health outcomes such as heart attack risk. Her experience includes applying statistical
methods and machine learning techniques, including logistic regression, random forest, and
XGBoost.
In addition to her research, Pranathi serves as a Teaching Assistant for INFO-I 501:
Introduction to Informatics, mentoring graduate students in SQL, Python, and machine
learning, and served as a Teaching Assistant for INFO-B 406: Biomedical Informatics, where
she supported undergraduate students in biostatistics, data visualization, and health data
analysis with Python and R.