Yohei KIKUTA, PhD
Tokyo, Japan
diracdiego[at]gmail.com
- AI/ML expert with over 11 years of experience in both academic research and real-world applications
- Proven track record of solving business-critical problems in image recognition, recommendation systems, NLP, and more
- Published peer-reviewed papers in deep learning and recommender systems
- Experienced in team leadership and organizational development
- Delivered numerous public talks and authored a wide range of technical articles
Amazon Web Services Japan (202510 - Present)
- Senior Specialist Solution Architects AI/ML (October 2025 - Present)
- To Be Written.
Self-employment (202409 - 202509)
- Research and Development Project (October 2024 - March 2025)
- Participated in a national research initiative focused on evaluating LLMs.
- Conducted comprehensive assessments of domain-specific and general-purpose Japanese LLMs.
- AI-Driven Software Development Improvement Project (November 2024 - July 2025)
- Investigated cutting-edge paradigms in declarative AI development, utilizing tools such as Cursor, Devin, and MCP servers.
- Regularly engaged in strategic discussions with executive leadership regarding the adoption of emerging AI technologies.
- Technical Advisor (October 2024 - Present)
- Acted as a strategic technical partner on topics spanning machine learning, generative AI, and organizational development.
- Provided strategic and hands-on support in validating AI-related ideas, leading to PoC implementations such as image retrieval.
- Book Writing Project – Theoretical Foundations of Generative AI (published August 18, 2025)
- Authored a book providing a deep, research-oriented understanding of generative AI by tracing its theoretical underpinnings back to the original foundational papers.
Ubie, Inc (202004 - 202408)
- Position: Vice President of Engineering (VPoE) (April 2023 - August 2024)
- Led engineering strategy and organizational development initiatives.
- Drove productivity improvements in software development processes.
- Position: Machine Learning Engineer (April 2020 - March 2023)
- Designed and deployed machine learning solutions.
- Maintained production ML systems and operational stability.
- Led data-driven initiatives to inform product and business strategy.
- Championed agile practices and improved internal communication, scaling Scrum methodologies across teams.
Self-employment (201902 - 202003)
- Contract Research Project
- Conducted literature reviews and implementation analyses on adversarial examples (50+ papers), using PyTorch for experimentation.
- Self-Directed Learning
- Studied machine learning theory (e.g., information theory), implemented research papers, developed Android apps, and explored competitive programming.
- Deepened understanding of computer science fundamentals: CPU architectures, operating systems, compiler/interpreter internals, etc.
Cookpad Inc. (201612 - 201901) position: machine learning engineer
- Developed ML-powered services for food image recognition: classification, object detection, and aesthetic scoring.
- Participated in leading conferences such as PAKDD, IJCAI, and NIPS (selected as a top conference reporter by JSAI, 2017).
- Spearheaded the company’s involvement in academic events and industry exhibitions.
- Led hiring and technical interviews for global ML talent and drove communication strategy for team building.
Deloitte (201404 - 201611) position: data scientist/machine learning engineer
- Applied state-of-the-art ML techniques to business problems: deep learning, recommendation, time series forecasting, and optimization.
- Delivered client-facing projects, including an on-site recommender system using XGBoost and Factorization Machines.
- Performed advanced analytics on topics such as ROI optimization and brand reputation using PLSA and Bayesian networks.
- Engaged in joint research projects exploring commercial applications of deep learning.
- SRGAN for Super-Resolving Low-Resolution Food Images (conference link)
- IJCAI-ECAI2018 WS CEA2018, poster, 20180715
- Improving SRGAN for Super-Resolving Low-Resolution Food Images (link)
- JSAI2018, in Japanese, 20180607
- ClassSim: Similarity between Classes Defined by Misclassification Ratios of Trained Classifiers (link)
- Approaches to Food/Non-food image classification using Deep Learning on cookpad (link)
- IJCAI2017 WS39 CEA2017, poster, 20170820
- Cookpad Image Dataset: An Image Collection as Infrastructure for Food Research (link)
- SIGIR2017, resource paper, 20170807
- Web-Scale Personalized Real-Time Recommender System on Suumo (link)
- PAKDD2017, long paper, 20170525
- Approaches to Food/Non-food image classification using Deep Learning on cookpad (link)
- JSAI2017, in Japanese, 20170523
- Proposing automated region extraction techniques from image data (link)
- JSAI2016, in Japanese, 20160606
- Inappropriate image detection based on Deep Learning (link)
- JSAI2016, in Japanese, 20160606
- Exploiting the Hidden Layer Information Toward the Understanding and Utilization of Feature Representations Obtained from Deep Learning (link)
- JSAI2015, in Japanese, 20150531
- Physics papers during my Ph.D. student years (link)
- Books
- Articles
- Blogs
- 原理的には可能 (In Japanese)
- Zenn (in Japanese)
- Ubie Blog (in Japanese)
- cookpad Developers Blog (in Japanese)
- 20181204, BERT with SentencePiece で日本語専用の pre-trained モデルを学習し、それを基にタスクを解く (link)
- 20180831, Cookpad Summer Internship 2018 5 DAY R&D を開催しました (link)
- 20180705, Firebase ML Kitで自作のカスタムモデルを使って料理・非料理画像を判定できるようにした (link)
- 20180328, 人工知能学会のトップカンファレンス派遣レポータとして NIPS2017 に参加しました (link)
- 20170914, 料理きろくにおける料理/非料理判別モデルの詳細 (link)
- 20170809, 2nd Hackarade: Machine Learning Challenge (link)
- Interviews
- Full list
- Speaker Deck
- Many presentations in private study groups
- Pattern Recognition and Machine Learning, Deep Learning, Python Machine Learning, Deep Learning with python, Information Theory Inference and Learning Algorithms, Categories types and structures, 深層学習, はじめてのパターン認識, 詳解ディープラーニング, 経済・ファイナンスデータの計量時系列分析, データ解析のための統計モデリング入門, etc
- hikifune.fm (in Japanese)
- Graduate University for Advanced Studies (200904 - 201403)
- Doctor of Philosophy (Ph.D.) in Elementary Particle Physics
- Ph.D. thesis: Higgs interactions in physics beyond the standard model
- JSPS Research Fellowship for Young Scientists (DC2)
- Tohoku University (200504 - 200903)
- Bachelor's degree in Physics