Shunsuke Kitada
研究員 at Day1 Company
Tokyo, Japan
Summary
👤
Senior🎓
Top SchoolShunsuke Kitada is a Ph.D. research scientist based in Tokyo with 11 years of experience building and evaluating deep learning systems for image recognition, NLP, medical imaging, and multi-modal advertising. Currently working across LY Corp and the University of Electro-Communications, he focuses on automatic generation and evaluation of ad creatives and assistive technologies for multi-modal ad delivery. His doctoral work improved prediction performance and interpretability through attention mechanisms, and he has applied those skills in industry research roles at Gunosy, CyberAgent, NTT, and LINE/LY. He regularly teaches and mentors—running image-generating AI lectures for Coloso and mentoring at Tokyo Tech’s TSUBAME deep learning camp—bridging research and practical high-performance computing. Notably, he combines rigorous academic grants experience (JSPS fellowship) with hands-on product-facing research that led to KDD and industry presentations. He is open to opportunities that specify company, position, and salary (expecting 18M JPY+).
11 years of coding experience
6 years of employment as a software developer
PhD in Engineering, 応用情報工学, PhD in Engineering, 応用情報工学 at 法政大学
Github Skills (147)
hugo10
codex10
deep-learning10
squad10
wowchemy10
zshrc10
natural-language-processing10
arxiv10
machine-learning10
survey10
aesthetics9
huggingface-datasets9
starship9
claude9
huggingface-transformers9
Programming languages (12)
Github contributions (5)
shunk031/simple-aesthetics-predictor
Jul 2023 - Aug 2025
CLIP-based aesthetics predictor inspired by the interface of 🤗 huggingface transformers.
Contributions:24 PRs, 33 pushes, 25 branches in 2 years 1 month
huggingface-transformerstransformerscliphuggingfacevit
shunk031/attention-meets-perturbation
Sep 2020 - Aug 2021
📝 Official Implementation of "Attention Meets Perturbation: Robust and Interpretable Attention with Adversarial Training"
Contributions:24 commits, 24 PRs, 27 pushes in 10 months
pytorchperturbationdeep-learningadversarialadversarial-training
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