ML Engineer - Google Research Africa• Lead ML operations to build an agriculture foundation model to accelerate the development of new climate-resilient crops• Conduct data analysis to inform the development of predictive models for food security and anticipatory aid distributionFullstack Software Engineer - Google Scholar• Launched first generative AI/LLM features in Google Scholar, leading the full product lifecycle from research to production, resulting in 40%+ increase in user engagement.• Optimized search and ranking for review-seeking and short queries, impacting over 50% of user searches, and designed a user interface for a review filter, improving user research efficiency.• Automated article link management, reducing maximum broken link resolution times by 90% and expanding user link quality monitoring coverage to 98+%.

• Assisted in teaching 6 undergraduate and graduate courses ranging in size from 10-600 students• Led weekly student discussion sections, developed course materials, graded student assignments,held regular office hours• Supported Courses: CS231N (Convolutional Neural Networks), CS224N (Natural Language Processing), CS224U (Natural LanguageUnderstanding), BIOE131 (Bioengineering Ethics), CS109 (Introduction to Probability for Computer Scientists) CS106A/B (Programming Methodology/Abstractions)

• Performed research as part of the Stanford Vision Lab, Computational Neuroscience laboratory (CNS), Hazy Lab and Center of AI in Medicine and Imaging (AIMI)• Selected projects: 1. Created an automatic vision-based system to evaluate Parkinson’s disease on the standardMDS-UPDRS scale using a combination of vision techniques including 3D pose estimation 2. Investigated abnormality detection in lower body radiographs with deep neural models andtheir potential for clinical application 3. Used weak supervision via SNORKEL and deep covariance resolution to perform textclassification on medical device reports from the FDA

• Investigated improvements to an extension of Google’s Knowledge Graph• Built parallel data processing pipelines using Flume to extract data from billions of web documents• Designed and trained several TFX model pipelines within the Google ecosystem

-Implementing an API to manage medical labeling databases for automated invoicing-Identifying physician bias when labeling retina lesions

-Developing algorithms for video analysis that use machine learning.-Prototyping for macOS and iOS

• Built new backend for VIC image processing stage in Tegra’s camera drivers to support deep color for the Jetson embedded AI computing device. • Designed and implemented comprehensive functional testing for Tegra camera core in GTEST framework• Found and helped resolve some preexisting software and hardware bugs with new tests

• Developed android and IOS prototypes for user-testing and executive presentations for the NCAA March Madness Live(MML) sports-streaming application with over 82 million streams per year• Conducted statistical assessment of large-scale marketing database of push notification user behavior in MML to inform 2016 marketing strategy• Led a project to document and integrate hundreds of JSON feeds across multiple platforms for MML

• Worked with graduate students to develop technology for smart-cars to diagnose driver fatigue• Developed algorithms to filter real-time ECG signals and calculate heart rate variability to assess heart health and wrote them up with Java• Implemented my program in an android application using Java and XML and integrated my project with the Bluetooth-enabled Shimmer wearable ECG-sensing device codebase