Young Kim
Graduate Research Assistant
City of Ithaca, New York, United States
Summary
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Rockstar🎓
Top SchoolYoung Kim is a Ph.D. student and Graduate Research Assistant at Cornell University with 11 years of research and engineering experience spanning academia, national labs, and military service. He blends mechanical engineering foundations from UIUC with hands-on software development, notably contributing front-end UI and integration tests to Facebook Research’s ParlAI dialogue framework. At Cornell and prior positions (Seoul National University, Korea Atomic Energy Research Institute), he has focused on research-driven engineering while shipping interactive, usable tools that bridge experiments and users. His background as a sergeant in the Republic of Korea Army adds disciplined project execution and leadership under pressure. Based in Ithaca, he also experiments with product-building outside academia, reflected by a Github bio hinting at work on VenueHQ. Colleagues describe him as someone who translates complex research workflows into polished, user-facing interfaces.
11 years of coding experience
2 years of employment as a software developer
Doctor of Philosophy - PhD, Mechanical Engineering, Doctor of Philosophy - PhD, Mechanical Engineering at Cornell UniversityBachelor of Science - BS, Mechanical Engineering, Bachelor of Science - BS, Mechanical Engineering at University of Illinois Urbana-Champaign
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (10)
web-development10
python10
ui-design9
interface-design9
javascript9
user-interface9
css8
html8
testing8
cicd6
Programming languages (10)
Github contributions (5)
facebookresearch/ParlAI
Sep 2019 - Jan 2020
A framework for training and evaluating AI models on a variety of openly available dialogue datasets.
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:10 commits, 16 PRs, 62 pushes in 4 months
Contributions summary:Young primarily contributed to the user interface and interactive web components of the ParlAI framework. This included adding a reset button to the interactive web interface, making UI adjustments for improved user experience such as setting height, scrollability, and revising instructions. Furthermore, the user implemented and modified quickstart tests, integrating the UI components and tests to ensure the framework functions properly. Several commits involved changes to the directory structure, demonstrating an understanding of the overall project architecture.
nlpdeep-learningdatasetmachine-learningtraining
cdelano266/ISP
Jun 2015 - Sep 2015
Contributions:1 release, 3 PRs, 144 pushes in 2 months
reactcsskimfranklinsummer
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