Selected roles across AI research, healthcare, and industry engineering.
Amazon
Owning development of a production proxy service enabling migration of a notification platform serving 43M+ daily push notifications to 11M+ customers. Designing a multi-endpoint REST API supporting localization, personalization, and real-time segmentation, cutting campaign launch time in half. Building end-to-end security across 3 layers, plus field-level hybrid encryption, holding sub-300ms p99 latency.
JUNE 2026 - PRESENT
Mayo Clinic
Accepted to 2026 Mayo Clinic AI Research Summit and 2026 Pathology Visions Conference. Built large-scale data pipeline processing 9,000+ DICOM medical imaging slides; optimized MIL (Multiple Instance Learning) system architecture for breast cancer biomarker prediction deployed at clinical scale. Engineered scalable inference pipeline for UNI foundation model generating survival outcome predictions with attention-based interpretability.
OCT 2025 - JUNE 2026
Georgia Tech — Entertainment Intelligence
“Counterfactual Explanations for Agentic Workflows” accepted to HCXAI @ CHI 2026 (Poster Spotlight). Designed interactive interface and LLM-based assistant to visualize execution traces, generate counterfactuals, and explain workflow behavior, improving interpretability of complex multi-step systems.
JUNE 2025 - PRESENT
Stanford Department of Anesthesiology
Built scalable data processing infrastructure on GCP/BigQuery for 4,100+ patient records with 50+ clinical covariates; secured $5,000 in research funding supporting a surgical risk prediction system. Designed and implemented a regression modeling pipeline using SQL, Python, and R for multi-dimensional clinical data analysis, enabling data-driven protocol improvements.
DEC 2024 - JAN 2026
Georgia Tech Research Institute — Sensors & Electromagnetic Applications
Designed and implemented a novel Python-based inversion adaptive noise cancellation system and GUI with a 48% SNR improvement (p = 9e-22) despite non-stationary noise. Developed a real-time digital signal processing pipeline leveraging RF lab equipment: signal generators, attenuators, noise amplifiers, and tunable band-pass filters.
JUNE - JULY 2025
Oracle
Led a 4-person team building a full-stack debt management system using Oracle APEX, SQL, and Java with a modular, object-oriented architecture; optimized FIFO data structures, reducing average days-to-payment by 18%. Implemented per-account FIFO priority queues with modular components for delinquency payment processing; improved system transparency and scalability across billing operations.
AUG 2024 - MAY 2025
United Nations World Assembly of Youth
Led end-to-end planning and moderation of the UN's largest global hackathon, attracting 1,700+ participants from 90+ countries, securing $10,000+ in prizes, and engaging UN Ambassadors and Directors.
JAN 2025 - DEC 2025
Microsoft and Women of AT&T
Prototyped an iOS app and NFC wearable to securely transfer HIPAA-protected medical data in emergencies. Directed a 6-person cross-functional team in Scrum-based development, including daily stand-ups and UX design, to enable faster, safer care during critical incidents; pitched to Microsoft and AT&T executives.
JULY 2023 - JAN 2024
Stanford Center for Artificial Intelligence in Medicine and Imaging
Selected as 1 of 20 nationwide. Trained a ResNet-101 image classifier on weak labels extracted from radiology reports via rule-based NLP using SpaCy and RadGraph. Built a custom dataset with transformation pipelines to reduce label bias and eliminate overrepresentation. Achieved 89% classification accuracy on pulmonary ultrasound data and placed 2nd in the program challenge.
JUNE - JULY 2024
Midwestern University
Engineered POCUS-Net, a novel transformer-based model to automate gastric ultrasound analysis. Classified gastric contents (liquid, solid, air) and segmented diameters to estimate operable volume. Achieved ~87% accuracy and integrated volume-based decision weighting to output aspiration risk.
AUG 2023 - APR 2024
TSI + Cornell University
Selected as top 10% of ~1,000. Adapted a Brain Network Transformer using Python GNNs for multi-state neuroimaging recognition. Published findings in the Talaria Journal and presented at the Talaria 2023 International Conference.
JUNE - AUG 2023