Experience

University of Chicago Department of Mathematics

• United States
• Higher Education
• 1 - 100 Employee

• Junior Tutor

  • Sep 2023 - Present

  • Conducting twice-weekly tutorial session for an introductory calculus course. • Grading homework assignments and weekly quizzes for students. • Conducting twice-weekly tutorial session for an introductory calculus course. • Grading homework assignments and weekly quizzes for students.



Vividly

• Software Development
• 1 - 100 Employee

• Engineering Intern

  • Jun 2023 - Aug 2023

  • Developed a sales forecasting model in R using historical sales data to estimate sales growth and seasonality in the consumer goods market with a goal to optimize brands’ spending on promotions. • Implemented using Python and Rust, integrated into the software’s Trade Promotion Optimization functionality. • Gained consumer goods industry knowledge by working with company domain experts, which was incorporated into model specifications and objectives. • Contributed to overall… Show more • Developed a sales forecasting model in R using historical sales data to estimate sales growth and seasonality in the consumer goods market with a goal to optimize brands’ spending on promotions. • Implemented using Python and Rust, integrated into the software’s Trade Promotion Optimization functionality. • Gained consumer goods industry knowledge by working with company domain experts, which was incorporated into model specifications and objectives. • Contributed to overall product enhancement by implementing performance improvements and resolving bugs. Show less • Developed a sales forecasting model in R using historical sales data to estimate sales growth and seasonality in the consumer goods market with a goal to optimize brands’ spending on promotions. • Implemented using Python and Rust, integrated into the software’s Trade Promotion Optimization functionality. • Gained consumer goods industry knowledge by working with company domain experts, which was incorporated into model specifications and objectives. • Contributed to overall… Show more • Developed a sales forecasting model in R using historical sales data to estimate sales growth and seasonality in the consumer goods market with a goal to optimize brands’ spending on promotions. • Implemented using Python and Rust, integrated into the software’s Trade Promotion Optimization functionality. • Gained consumer goods industry knowledge by working with company domain experts, which was incorporated into model specifications and objectives. • Contributed to overall product enhancement by implementing performance improvements and resolving bugs. Show less



University of Chicago Medicine, Rubin Lab

• Chicago, Illinois, United States

• Research Assistant

  • Jul 2022 - Apr 2023

  • Collaborated with a team to rewrite an iOS application into a Flutter-based cross-platform application. • Leveraged the phone's gyroscope and accelerometer to analyze a patient's gait, which the research uses to estimate metabolic function, an important metric for predicting patient readiness for surgery. • Collaborated with a team to rewrite an iOS application into a Flutter-based cross-platform application. • Leveraged the phone's gyroscope and accelerometer to analyze a patient's gait, which the research uses to estimate metabolic function, an important metric for predicting patient readiness for surgery.



Unify

• United Kingdom
• Software Development
• 1 - 100 Employee

• Machine Learning Research Engineer Intern

  • Aug 2022 - Sep 2022

  - Developed an inter-operativity layer between popular Python machine learning frameworks and an optimizing compiler for ML pipelines. - Part of the development effort; contributed parts of the NumPy interface and worked on optimizations for the graph compiler, allowing the conversion of complete pipelines between frameworks and into bytecode. - Code was pushed to the codebase repository for inclusion in Ivy’s next release; reviewed and edited code contributions from other team members. - Developed an inter-operativity layer between popular Python machine learning frameworks and an optimizing compiler for ML pipelines. - Part of the development effort; contributed parts of the NumPy interface and worked on optimizations for the graph compiler, allowing the conversion of complete pipelines between frameworks and into bytecode. - Code was pushed to the codebase repository for inclusion in Ivy’s next release; reviewed and edited code contributions from other team members.