Curriculum Vitae

M.Sc. Computational Neuroscience

Coursework: Models of Neural Systems, Models of Higher Brain Functions, Acquisition and Analysis of Neural Data, Machine Intelligence

B.S. Computer Science & B.S. Mathematical Sciences

Relevant coursework: Parallel & Sequential Data Structures and Algorithms, Distributed Systems, Intro to Machine Learning, Differential Equations, Real Analysis I & II, Probability Theory, Numerical Methods

Computational Neuroscientist

• Reproduced and extended findings on slow dynamics in clustered spiking networks (Litwin-Kumar & Doiron, 2012)
• Built modular simulation and analysis pipelines using Brian2, NumPy, and SciPy

Tech Lead & Staff Engineer (E6)

• Led re-architecture projects including introducing subgraphs in user workflow graph engine and re-designing core data models for connection engine performance
• Designed and managed execution of a year-long re-architecture project, delivering complex changes on time with no system downtime in mission-critical systems

Senior Software Engineer (E5)

• Helped start this team from scratch, defining charter, roadmap, and building culture
• Led project to build Remote Developer Environment with fleet of 100+ virtual machines capable of running Plaid's entire software stack

Software Engineer (E4)

• Managed container orchestration, networking, deployments, and CI systems to scale engineering from 10s to 100s of running services

Software Engineer (E3)

• Worked on real-time, in-memory database storage and query engine for structured data
• Built Spark and Hadoop pipelines to process incoming data sources