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README.md

Yohei KIKUTA, PhD
Tokyo, Japan
diracdiego[at]gmail.com

Summary

  • Expert at machine learning, 4+ years experience in both research and practical application
  • Solved data analysis problems for business purpose: image recognition, recommendation, text analysis, and so forth
  • Published achademic papers about deep learning and recommendation
  • Made many external presentations about machine learning
  • Contributed article to NikkeiBP and JSAI, and wrote book for beginners of machine learning
  • Core competencies: Machine learning theory and implementation, image analysis, recommendation, Python, R

Skills

Machine Learning

  • Deep theoretical understanding of machine learning
  • Image recognition, recommender system, text analysis, marketing ROI optimization, time series analysis
  • TensorFlow, Keras, scikit-learn, gensim, and so many more

DevOps

  • Basic knowledge of Linux (Ubuntu), Git (GitHub) and Docker (Docker Hub)
  • AWS, GCP

Language

  • Japanese (native), English (business)
  • Python, R

Experience

Self-employement (201902 - Present)

Cookpad Inc. (201612 - 201901)

  • Research and Development
    • Created new service using machine learning
      Image recognition using deep learning: classification, object detection, attactiveness estimation, etc
    • Attended machine learning conference
      PAKDD, IJCAI, NIPS (as a top conference reportoer of JSAI in 2017), ...
  • Sponsoring conference and organizing event
    • Led company's exhibition, chaired a session of IPSJ, is one of committee members of CEA
    • Organized various events, see connpass page
  • Hiring and team building
    • Conducted interview with candidate for machine learning position in domestic and global
    • Contributed team building and communiation strategy

Deloitte (201404 - 201611)

  • Research and Development
    • Investigated business application by means of cutting edge technologies and wrote papers 
      Image recognition using deep learning, recommendation
  • Data analysis service to a client (onsite project at a client's office)
    • Built machine learning module for a recommender system
      Learning to rank, Xgboost, Factorization Machines, Spark, Hive, AWS
    • Analyzed various topics: ROI optimization, time series analysis for the budget planning, etc
      ARIMA, price elasticity analysis, linear programming, genetic algorithm
  • Characteristic analysis of tourist spots and brand reputation analysis of a company
    • Analyzed for reporting to clients
      Text data processing, topic model (PLSA), bayesian network
  • Joint research about business applications using deep learning

Publications

Papers

  • 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 (conference 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, Interviews

  • Books & Articles
    • フリーライブラリで学ぶ機械学習入門 (link)
      • 20170321, 秀和システム, in Japanse
      • Contribution to chapters 1,6 and 8.
    • Web articles
      • 20180515, 機械学習を用いた画像分類における「未解決問題」を解くためにやったこと(link), in Japanese
      • 20180620, GeekOutナイト(link1,link2,link3,link4), in Japanese
    • 人工知能学会誌寄稿
      • 201805, 会議報告「The Thirty-first Annual Conference on Neural Information Processing Systems(NIPS 2017)」 (link), in Japanese
      • 201809, 「AI トレンド・トップカンファレンス NIPS 2017」報告会 (link), in Japanese
    • この1冊でまるごとわかる! 人工知能ビジネス (link)
      • 20150829, 日経BP, in Japanse
      • Contribution to the article of p.86-87.
  • Blogs
    • COOKPAD Engineer's 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
    • 「機械学習で食生活を豊かにする」ことに挑む物理学博士が思い描く研究とサービスの良い関係 (前編, 後編)
      • 20180807, 20180810, forkwell press, in Japanese
    • クックパッドにおける料理きろくサービスと研究開発 (link)  
      • 20171223, 日刊工業新聞, in Japanese

Presentations

  • Full list
  • Speaker Deck
  • Many presentations in private study groups  - Pattern Recognition and Machine Learning, Deep Learning, Python Machine Learning, Deep Learning with python, 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

Education

  • Graduate University for Advanced Studies (200904 - 201403)
    • Doctor of Philosophy (Ph.D.) of 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 of Physics

Ohters

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