Ryan Whitty Email & Phone Number

• Working on applying computer-assisted proofs to theoretical computer science, advised by professor Venkatesan Guruswami

• Held weekly discussion sections and office hours for Berkeley’s 700-student upper-division algorithms course, teaching students advanced concepts like dynamic programming, graph theory, and reductions
• Worked with professors to design, debug, and grade course content, ensuring fairness and accuracy

• Held office hours, graded exams, and monitored EdStem online forum

• Built a full CI/CD pipeline with TypeScript and AWS CDK which allows frontend developers to release pages to amazon.com with greater reliability and lower latency, saving 10+ developer-weeks annually
• Optimized performance and scalability of content deployments by implementing a fast, Java-based data fetching service, using AWS ECS to host a caching agent and Spring MVC to manage data retrieval
• Seamlessly integrated new workflows into Amazon’s internal infrastructure, utilizing AWS AppConfig for efficient cloud-based data storage and AWS IAM for secure internal permissions management

• Developed Python software to efficiently process and validate large (10+GB) gene sequencing datasets, significantly enhancing system reliability by diagnosing critical software bugs and hardware defects
• Automated and optimized end-to-end algorithm verification processes with Jenkins and Bash scripts, reducing time spent on routine software development tasks like building and testing by up to 80%
• Aggregated gene sequencer performance metrics and test suite results into a clean, employee-friendly interface using Gherkin and Cucumber, now referenced internally by many software engineering teams

• Engineered and streamlined data pipelines encompassing patient data entry, storage, and eventual reporting, ultimately being used by hundreds of participants enrolled in studies across the country
• Worked with senior scientists to design a statistical analysis plan and wrote scripts for cleaning, analysis, and visualization of data from large-scale clinical studies in Python using NumPy, Pandas, and SciPy
• Created interactive data reports for use by patients, clinicians, and researchers in Google Data Studio

B.A., Computer Science, Senior

Activities and Societies: URAP Research Program, CS 170 Course Staff, Upsilon Pi Epsilon, EECS Honors Program, University Chorus, Bowles.

High School Diploma

Activities and Societies: Debate Team, Marching Band, Chess Club, Cross CountryGPA: 4.0