I'm Scott, a Bay Area native, tea connoisseur, and turtle enthusiast. Currently, I'm a software engineer at Lyft, returning after completing my M.S. at UC Berkeley. In the past, I've also had the pleasure of working at other amazing companies like Rubrik and Brilliant.
I'm passionate about designing thoughtful solutions to complex problems. My academic and industry interests include artificial intelligence (machine learning, computer vision), business intelligence (marketing technology, business infrastructure, large-scale logistics), and intersecting technology and education. I fill my free hours by sipping tea, enjoying unique video games, climbing rocks, and trying new restaurants.
Computer Vision
Machine Learning
AI in Natural Language Processing
AI in Robotics
AI in Healthcare & Medicine
Algorithms & Complexity
Probability & Random Processes
Convex Optimization
Theoretical Statistics
Linear Modeling
Financial Engineering
Software Engineer (Growth Platforms)
• Redesigned two major components in existing infrastructure for automated driver acquisition, efficiently scaling up marketing spend from COVID-shutdown to $5MM+/month marketing spend across three paid media channels.
• Drove multi-quarter, mission-critical initiatives directly impacting key team OKRs, partnering with numerous other engineers and scientists in a highly cross-functional environment.
• Leveraged and augmented team’s core database of ~30 tables in actively planning the team’s short-term strategy as well as long-term team roadmapping (annual planning & long-term vision).
Graduate Researcher
• Computer Vision (Explainability, Few-Shot)
• Medical Imaging (EKG)
Software Engineering Intern (Marketplace)
• Dual project between infrastructure (generalized pricing API) and modeling (new surge pricing model).
• Conducted extensive data analysis and feature engineering, created dynamic endpoints to fetch features, and owned several pricing experiments.
Software Engineering Intern (Office 365 Backup)
• Designed and implemented an integral component of the first product launch of Office 365 Backup (Rubrik’s first SaaS product): a robust cloud database and datastore system flexibly compatible with AWS, Azure, and GCP.
A Slackbot packed with features to assist teaching staff members, including roster lookup, Piazza paging, and groupshouts.
An augmented course catalog used by over 30,000 UC Berkeley students that provides data on courses, enrollment trends, grade distributions, and more.
Improving explainability for deep learning image classification using a decision tree-based structure.
A general method for altering algorithms for edge detection in order to produce edge mappings that focus on one or few individual objects in an image.