AI Engineer @ ZingageHi. I'm Hannah.
I build AI for medicine.
I'm an AI Engineer at Zingage and a Stanford Computer Science grad (BS Computational Biology, MS AI). I have experience in AI and full-stack engineering, but my passion lies in the intersection of AI and medicine.
- BS + MS
- Stanford CS
- Bio + AI
- Computational Biology · AI tracks
- 7
- industry & research roles
01 / About
My experience, my passions
I studied Computer Science at Stanford on the Computational Biology track for my BS and the Artificial Intelligence track for my MS. I've built computer vision models for an X-ray device, tissue segmentation tooling for digital pathology, and production LLM voice agents. I am building a career improving public health. These are my core areas of interest.
Drug discovery & protein ML
Structure prediction, generative models, and molecular simulation for finding new therapeutics.
Medical imaging & devices
Computer vision for imaging hardware, from X-ray keypoint detection to tissue segmentation.
Personalized medicine
Models that adapt to the individual: genomics, CRISPR-based and cell therapies, and precision care.
Clinical AI agents
Voice AI and recommendation systems that expand health care access for those in need of in house treatment.
02 / Experience
Experience
Zingage
New York, NYAI Engineer
- Building an in-house audio evaluation set for voice AI agents
- Owning the rollout of a new ranking/recommendation system, from design iterations and shadow runs to A/B testing and full rollout
Stanford Language Data and Reasoning Lab
Stanford, CAGraduate Research Assistant
- Built a recommendation system utilizing knowledge graphs
- Developed advanced evaluation techniques for an AI retail assistant through LLM-simulated user dialogue
Verkada
San Mateo, CASoftware Engineer Intern
- Built a voice agent on the Alarms Response team that leverages realtime LLMs for speech-to-speech capabilities using twilio, temporal, golang and openai APIs
- Created an automated workflow for Alarm License Certificate generation using Temporal
Bioinformatics Institute, A*STAR
SingaporeSIPGA Internship Awardee
- Developed a Next.js web app from scratch integrating an H&E histopathology tissue segmentation AI model for cancer cell detection with a custom visualization tool
- Integrated AWS services (Amplify, DynamoDB, S3, SageMaker) to manage hosting, the ML pipeline, and backend database operations
Dropbox
RemoteSoftware Engineer Intern
- Implemented a full-stack development project for Dropbox Enterprise, enhancing functionality by implementing bulk actions using TypeScript, React, and Python for the backend.
- Contributed to the redesign and migration of Dropbox Enterprise Members page collaborating closely with the Design team and product manager
Code in Place
Stanford, CACurriculum Designer
- Co-authored an online course reader for Stanford's global, virtual computer science class from scratch, creating original and engaging content and examples to illustrate key concepts for students worldwide.
OXOS Medical
Atlanta, GASoftware Engineer Intern
- Developed multiple computer vision models for an X-ray device using Python and TensorFlow, including key point detection and image segmentation models
- Managed the entire machine learning pipeline, from data collection and annotation to preprocessing, model construction, and research
- Conducted extensive hyperparameter tuning to optimize model performance and ensure accurate results
03 / Publications
Publications
04 / Education & Skills
Education & Skills
Stanford University
Stanford, CAMaster of Science, Computer Science (Artificial Intelligence Track)
June 2026
Bachelor of Science, Computer Science (Computational Biology Track)
June 2025
Bio/Health Coursework: Representations & Algorithms for Computational Molecular Biology, Foundations of Computational Human Genomics, Modeling Biomedical Systems, Biodesign Fundamentals, Large-Scale Neural Network Modeling for Neuroscience, Biochemistry & Molecular Biology, Genetics, Cell Biology, Physiology, Introduction to Bioengineering, Human Anatomy, Foundations of Bioethics
AI/ML Coursework: Mining Massive Datasets, AI: Principles and Techniques, NLP with Deep Learning, Deep Learning for Computer Vision, Reinforcement Learning, Deep Reinforcement Learning, Decision Making Under Uncertainty, Conversational Virtual Assistants with Deep Learning, Continuous Mathematical Methods with an Emphasis on Machine Learning
Programming Languages
Tools & Frameworks
Languages
05 / Projects
Projects
AI, ML, and Full-Stack Development
