resume

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Contact Information

Name Jihyeon Lee
Professional Title Researcher / Software Engineer
Email jihyeon@cs.stanford.edu

Professional Summary

Researcher at Google Research, Stanford CS Alum. Building AI for social good and robust decision-making.

Experience

  • 2020 - Present

    Mountain View, CA

    Software Engineer
    Google Research
    Building SKAI, an AI system for detecting damage after natural disasters for humanitarian organizations.
    • Collaborating with United Nations World Food Programme and GiveDirectly.
  • 2019 - 2019

    Mountain View, CA

    Software Engineering Intern
    Google, Geo Insights Team
    Designed and built pipeline to perform weakly supervised segmentation on aerial imagery, including training model and evaluating predictions. Developed novel method that soft-labels masks by synthesizing data augmentations.
    • TensorFlow, Apache Beam, OpenCV, Python imaging libraries, machine learning at scale
  • 2018 - 2019

    Stanford, CA

    Researcher
    Stanford Sustain Lab
    Developed a weakly supervised geovisual search pipeline that learns how to perform detection from classification labels and uses data augmentation + human-in-the-loop data distillation. Applied to locate brick kilns in Bangladesh to monitor environmental regulations.
    • Advised by Stefano Ermon, David Lobell, Marshall Burke, Steve Luby Mentored by Nina Brooks
    • Received Firestone Medal (only 1 in CS Department)
  • 2018 - 2018

    San Francisco, CA

    Software Engineering Intern
    Pinterest, Visual Search Team
    Implemented data distillation to automatically augment training datasets from billions of unlabeled, user-generated imagery at little to no cost. Expanded dataset size by 200% and showed newly trained model performs better.
    • Kleiner-Perkins Engineering Fellow
    • TensorFlow, Hadoop/SQL, Pandas, Python imaging libraries
  • 2017 - 2019

    Stanford, CA

    Researcher
    Stanford Vision & Learning Lab
    Investigated an active learning system that generates questions about images on social media and asks them to users to automatically collect data. Created a sequential attention-based model to handle noisy responses.
    • Advised by Fei-Fei Li, Michael Bernstein Mentored by Ranjay Krishna
    • Gave spotlight talk at CS 231N (Spring 2017)
    • Presented at Stanford Human-Centered AI Symposium (Spring 2019)
  • 2017 - 2017

    Sunnyvale, CA

    Computer Vision Software Intern
    Matterport
    Developed algorithm that creates 3D point cloud models from real-time scanning that is robust to color balance and lighting changes within a single scene.
    • C++, OpenGL, OpenCV, Android
  • 2016 - 2017

    Stanford, CA

    Researcher
    Stanford HCI Lab
    Developed a system that uncovers insights for creative experts (journalists, podcasters) from large amounts of unstructured visual and language data. Created an interactive archive for Douglas Engelbart’s work.
    • Advised by Maneesh Agrawala Mentored by Mitchell Gordon, Juho Kim
    • {“Publication”=>”UIST ‘17 (30th Annual ACM Symposium on User Interface Software and Technology)”}

Education

  • 2019 - 2020

    Stanford, CA

    M.S.
    Stanford University
    Computer Science (AI & HCI Specializations)
    • Siebel Scholar (full merit-based scholarship)
    • {“Advisers”=>”Maneesh Agrawala and Stefano Ermon”}
  • 2015 - 2019

    Stanford, CA

    B.S. with Honors
    Stanford University
    Computer Science (AI Specialization), Minor in Feminist, Gender, & Sexuality Studies
    • Firestone Medal for Excellence in Undergraduate Research (top 10% of theses)