Aarushi Ammavajjala.
Developer
Studying Computer Science @ South Forsyth High School
Contact: aaru7811 [at] gmail [dot] com
Education & Skills
South Forsyth High School
NMSQT Finalist, AP Scholar with Distinction
AUG 2021 - MAY 2025
Python
Java
Swift
SQL
Computer Vision
NLP
R
JavaScript
Recent Experiences
AI Development Intern
Georgia Institute of Technology
Computational creativity & AI-powered game generation. More coming soon.
AUG 2025
STEM@GTRI Intern
Georgia Tech Research Institute
Details coming soon.
JUNE - JULY 2025
AI Development Intern
United Nations WAY
Coordinating AI development across 140+ youth-led international NGOs.
JAN 2025 - PRESENT
AI Research Intern
Stanford Department of Anesthesiology
Predicting hypotension from arterial blood waveforms using deep learning.
JAN 2025 - PRESENT
Development Intern
Oracle
Designed and implemented a billing system using OCI, APEX, SQL, & PL/SQL; directed FIFO debt management, payment application, and error handling, with delinquency predictions.
AUG 2024 - PRESENT
AI Research Intern
Stanford Center for Artificial Intelligence in Medicine and Imaging
1 of 20 selected nationwide. Developed high-accuracy pulmonary diagnostic system. RadGraph for unsupervised radiology report classifier; ResNet ultrasound analysis model.
JUNE - JULY 2024
Development Intern
Microsoft
Utilized Swift, SQL, Dart, and JavaScript to develop JackTag, a mobile application and NFC wearable that streamlines communication of medical information between crisis victims and first responders. Presented to Microsoft/AT&T investors.
JULY 2023 - APR 2024
AI Research Intern
TSI + Cornell University
Developed a graph neural network for binary state neuroimaging recognition. Accepted to TSI (~10% of 850), matched at Cornell University. Published paper and spoke at Talaria International Conference.
JUNE - AUG 2023
AI Research Intern
Midwestern University
Developed a two-prong neural network to automate gastric point-of-care ultrasound. Segments antrum, classifies content, identifies diameters, calculates operable volume, and outputs aspiration risk.
AUG 2023 - APR 2024
Independent Projects
MediScript
A custom-built, domain-specific language designed for medical diagnostics and treatment planning, democratizing AI for healthcare professionals.
MelaninMed
A deep learning powered AI mobile application for racially equitable skin cancer detection.
POCUS-Net
A highly-accurate transformer-based classification model to reduce anesthesia-induced aspiration morbidity.
ClimiCide
A gradient boosting regressor, trained on a custom dataset, to predict increases in climate-change-induced suicides.