Software Engineering, Machine Learning

Yejun (John) Choi

718-***-**** ******@***.*** linkedin.com/in/jc0318 github.com/yc3582 Brooklyn, NY Education

New York University, New York, NY Sept 2022 – Dec 2024 M.S Computer Engineering

• Courses: Software Engineering, Algorithms, Data Structures, Discrete Math, Object Oriented Programming, Advanced Machine Learning, Deep Learning, Probability and Stochastic Processes, Big Data New York University, New York, NY Sept 2018 – Aug 2022 B.S Computer Science / Mechanical Engineering

Work Experience

Software Engineering Intern May 2023 – Aug 2023

Three Ducks Inc. New York, NY

• Implemented responsive video galleries and optimized web interfaces with Shopify Liquid, JavaScript, and Typescript

• Improved site UI/UX on order history pages, by refining layouts, linking products, and adding new functionalities

• Collaborated with a senior engineer to conduct unit testing on new functionality and A/B testing on the improved UI/UX, resulting in a 13% increase in user engagement

• Improved code quality by resolving 15% of the static analysis warning backlog AI Research Intern June 2021 – Aug 2021, June 2022 – Aug 2022 St. Mary’s Hospital Seoul, South Korea

• Preprocessed lumbar spinal MRI images using MATLAB and employed segmentation tools to annotate bone marrow regions

• Trained SVM and CNN model using preprocessed data, and trained a Random Forest model with radiomics features extracted from the preprocessed data using Scikit-learn and TensorFlow

• Improved model accuracy by 14% and 9% for detecting Hematologic Marrow Disease

• Led a reading group to learn recent AI trends in medicine Computer Science Tutor Jan 2020 – May 2020

New York University

• Instructed 30+ undergraduate students in groups of 1~5 on implementing algorithms using MATLAB 12hr/week

• Designed mock exams for the ‘Intro to Problem Solving’, led review sessions and presented solutions Projects Experience

AI-Generated Text Classification (Course: Big Data) April 2024 – May 2024

• Developed machine learning models in PyTorch to predict whether a text is AI-generated or not

• Leveraged Apache Spark for large-scale data processing and real-time analytics using distributed computing

• Initiated MongoDB Atlas deployment with a schema for text and metadata, ensuring global availability for high- throughput, low-latency operations

• Using BERT model, fine-tuned models via regularization, hyperparameter optimization, and adjustment to output layers, achieving 93.2% accuracy

NYC Compost (Course: Software Engineering) Jan 2023 – May 2023

• Created a Django application that connects NYC compost facilities, individual households, and bigger restaurants

• Implement features that enable real-time data sharing and integrated maps to drive efforts for reducing food waste

• Engineered API-driven data flow to optimize surplus food redistribution and minimize waste Augmented Library Jan 2023 – May 2023

• Developed backend server using Python & MySQL enabling a comprehensive augmented reality application tailored for NYU students.

• The application centralizes library resources, facilitating study room bookings and e-textbook access Skills

• Development Languages: Python Java JavaScript C/C++ TypeScript HTML/CSS SQL Unix

• Framework: Django Atlassian JIRA & Confluence Git

• Certificate: Machine Learning by Stanford University & DeepLearning.AI on Coursera (Jan 2024)

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