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Computer Vision Engineer at Meta Reality Labs (2022-present) | ex-RS at kakaobrain (2021-2022) | ex-SWE at NAVER (2017-2021)
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Meta Reality Labs
Data Scientist
June 23, 2026 – Present
rtic-gcn-pytorch
September 3, 2021 – October 26, 2021
Official PyTorch Implementation of RITC
View ProjectFashionIQChallenge2020
June 12, 2020 – May 1, 2023
2nd Place Team's Solution for Fashion IQ Challenge 2020
View ProjectDeLF-pytorch
January 26, 2019 – February 1, 2021
PyTorch Implementation of "Large-Scale Image Retrieval with Attentive Deep Local Features"
View Projectpixel-dt-gan-pytorch
June 10, 2018 – June 10, 2018
Pytorch implementation of pixel level domain transfer
View Projectpggan-pytorch
November 13, 2017 – November 22, 2022
:fire::fire: PyTorch implementation of "Progressive growing of GANs (PGGAN)" :fire::fire:
View Projectprogressive-growing-torch
October 30, 2017 – November 15, 2017
Torch implementation of "PROGRESSIVE GROWING OF GANS FOR IMPROVED QUALITY, STABILITY, AND VARIATION"
View Projectgans-awesome-applications
October 12, 2017 – Present
Curated list of awesome GAN applications and demo
View Projecttext2image-benchmark
October 11, 2017 – October 25, 2017
Performance comparison of existing GAN based Text To Image algorithms. (GAN-CLS, StackGAN, TAC-GAN)
View Projectgans-collection.torch
September 13, 2017 – October 14, 2017
Torch implementation of various types of GAN (e.g. DCGAN, ALI, Context-encoder, DiscoGAN, CycleGAN, EBGAN, LSGAN)
View Projectdense-equi-torch
September 6, 2017 – November 16, 2017
Torch7 implementation of Unsupervised object learning from dense equivariant image labelling
View ProjectCultural Fit Analysis
The candidate's project portfolio is heavily focused on personal research and development in GANs and deep learning, primarily using Python and Lua. While this demonstrates strong technical interest and initiative, the lack of diverse project types (e.g., business intelligence, A/B testing, traditional machine learning, data engineering) and limited information on collaborative work or broader industry applications suggests a potentially narrow focus. The single listed professional experience as a Data Scientist at Meta Reality Labs is current, but no details are provided regarding responsibilities or contributions, making it difficult to assess alignment with a typical Data Scientist role beyond deep learning research. The candidate's experience level is listed as 0, which contradicts the current role at Meta Reality Labs, indicating a data inconsistency that limits cultural fit assessment.
Soft Skills & Operational Fit
The provided data does not contain sufficient information to assess soft skills or operational fit. The candidate's extensive personal projects suggest self-motivation and a strong interest in deep learning research and application.