Hey, I'm Sujin Lee

Software Engineer

👋 Welcome! I'm always open to feedback, collaboration, or a quick chat—feel free to get in touch or schedule a time to connect.

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About Me

Hello, I'm Sujin Lee

I'm studying Computer Science and Applied Math & Stats at Johns Hopkins University. I like building things that solve real problems, whether that’s through software, data, or a mix of both.I've worked on projects that range from job tracking tools to battery prediction models, and I enjoy working across the stack. I’m especially interested in how machine learning can be used in practical, everyday systems.Outside of school and code, I love puzzles, exploring new ideas, and learning from the people around me. Feel free to reach out — happy to chat!

Experience

Aug 2025 - TBD

Incoming Tech Program Intern - Akuna Capital

TBD

May 2025 - Aug 2025

Incoming Software Engineering Intern - Meta

AI Knowledge Integration Team

Aug 2023 - Present

Teaching Assistant - Johns Hopkins University

Probability (EN.553.420/620), led a TA section, grading, instruction, 1:1 help, and provided office hours every week as a sophomore for upper-level course for 120+ students.

Nov 2022 - Jan 2025

Website Organizer - Hophacks

Organized an annual 36-hour hackathon at Johns Hopkins University for 400+ students. Implemented a SAML-based authentication system to streamline and secure access for over 1,000+ users, enhancing both authentication and authorization processes

May 2024 - Aug 2024

Software Engineering Intern - Samsung SDI

Developed and improved a battery capacity prediction model at Samsung SDI, utilizing pandas, NumPy, Scikit-Learn, and XGBoost. Enhanced accuracy by 15% through feature engineering techniques like binning and PCA. Analyzed correlations using Pearson coefficients to optimize model input.

Aug 2023 - Jan 2024

Algorithm Developer - JHU Delineo Disease Modeling

COVID-19 Modeling Project, mainly focused on household generation and developing algorithms to model distinct movement patterns. Used geospatial data and real-world maps. Applied agent-based modeling(ABM)and GIS to model dynamic behaviors and predict population shifts

Projects

Summit AI - Powered Job Tracker

A full-stack job tracking tool built with Django, React, and Celery. It integrates with the Gmail API for real-time sync and smart email parsing, classifies application status, detects duplicates, manages cycle data, and syncs key events to Google Calendar.

Prostate Cancer Detection

Two-Stage Deep Learning Pipeline for Prostate and Lesion Segmentation in MRI Scans. A pipeline of data processing and two U-Net transformer models that can output prostate and legion segmentation.

Smart Knee Brace Diagnostic Device

Developed a knee mobility measurement device using C++ and Arduino. Collected and analyzed data from 8 diverse participants, applying PCA and Fourier transform to correlate joint range of motion with medical conditions.