Kotaro Kikuchi
Researcher at CyberAgent, Inc.
Chiyoda, Japan
Summary
👤
Senior🎓
Top SchoolKotaro Kikuchi is a research scientist at CyberAgent AI Lab with a decade of experience applying machine learning and optimization to graphic design and creative workflows. He holds a PhD in Computer Science from Waseda University and has shaped his research through internships at Microsoft Research Asia and CyberAgent, blending academic rigor with industry-facing problems. His work focuses on practical ML methods that help automate and enhance visual design tasks, bridging algorithmic innovation and designer needs. Having progressed from research assistant to full researcher, he brings both hands-on prototyping experience and publication-grade research skills. Based in Chiyoda, Tokyo, he pairs deep technical expertise with a curiosity for human-centered tools that make creative processes more efficient. Check his website for detailed publications and project demos that reflect a strong emphasis on usable research outcomes.
10 years of coding experience
2 years of employment as a software developer
Exchange Program, Exchange Program at University of California, DavisDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Waseda UniversityMaster of Engineering - MEng, Computer Science and Engineering, Master of Engineering - MEng, Computer Science and Engineering at 早稲田大学 WASEDA University
Github Skills (27)
generative-adversarial-network10
data-science9
lifecycle9
artificial-intelligence9
lightning9
pytorch9
scaling9
python9
machine-learning9
ai9
deep-learning9
speech9
nlp8
multiclass-classification8
cost-management8
Programming languages (1)
Github contributions (5)
ktrk115/web_layout
Sep 2021 - Oct 2022
Contributions:15 commits, 6 pushes in 1 year 1 month
ktrk115/const_layout
Jul 2021 - Oct 2022
Official implementation of the MM'21 paper "Constrained Graphic Layout Generation via Latent Optimization" (LayoutGAN++, CLG-LO, and Layout evaluation)
Contributions:16 commits, 25 pushes, 21 comments in 1 year 2 months
augmented-lagrangian-methodcma-esgenerative-adversarial-networklatent-spacelayoutgan
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