研究概要のページ

Research achievements

東北大学・未踏スケールデータアナリティクスセンター・教授

Professor, Unprecedented-scale Data Analytics Center, Tohoku University

東北大学・情報科学研究科・教授

Professor, Graduate School of Information Sciences, Tohoku University

産業技術総合研究所・人工知能研究センター・客員研究員

Visiting Researcher, Artificial Intelligence Research Center, National Institute of Advanced Industrial Science and Technology

人工知能と意識 / 文脈情報処理のためのニューラルネットワークと対話エージェント / テレビゲームとエンターテイメント

Strong AI and machine consciousness / neural network for sequence processing and dialogue agent / video game and entertainment

    Peer-reviewed Papers

  1. Maas A, Yamada KD, Nagahama T, Kawada T, Horita T, Question generation for English reading comprehension exercises using Transformers, Letters on Informatics and Interdisciplinary Research, 5, 2024
  2. Lin F, Yue Y, Zhang Z, Hou S, Yamada KD, Kolachalama VB, Saligrama V, InfoCD: A contrastive chamfer distance loss for point cloud completion, Advances in Neural Information Processing Systems, 2023
  3. Lin F, Yue Y, Hou S, Yu X, Xu Y, Yamada KD, Zhang Z, Hyperbolic chamfer distance for point cloud completion, International Conference on Computer Vision, 2023
  4. Nagase Y, Satoh T, Shigetome K, Tokumaru N, Matsumoto E, Yamada KD, Imafuku T, Watanabe H, Maruyama T, Ogata Y, Yoshida M, Saruwatari J, Oniki K, Serum fatty acid composition balance by fuzzy c-means method in individuals with or without metabolic dysfunction-associated fatty liver disease, Nutrients, 15(4):809, 2023
  5. Maas A, Kawada T, Yamada K, Nagahama T, Horita T, Identifying latent traits of questions for controllable machine generation, EdMedia + Innovate Learning, 2022
  6. Yamada KD, Baladram MS, Lin F, Relation is an option for processing context information, Frontiers in Artificial Intelligence, 5:924688, 2022
  7. Yasukawa K, Yamada K, Tokuda H, Koyama S, Utsumi H, Redox imaging of dextran sodium sulfate-induced colitis mice treated with nitric oxide synthase inhibitors, Advances in Redox Research, 6, 2022
  8. Lin F, Xu Y, Zhang Z, Gao C, Yamada KD, Cosmos Propagation Network: Deep learning model for point cloud completion, Neurocomputing, 507:221-234, 2022
  9. Yamada KD, Baladram MS, Lin F, Progress in research on implementing machine consciousness, Interdisciplinary Information Sciences, 28(1):95-105, 2022
  10. Lin F, Gao C, Yamada KD, An effective convolutional neural network for visualized understanding transboundary air pollution based on Himawari-8 satellite images, IEEE Geoscience and Remote Sensing Letters, 19:1-5, 2022
  11. Yamada KD, Lin F, Nakamura T, Developing a novel recurrent neural network architecture with fewer parameters and good learning performance, Interdisciplinary Information Sciences, 27(1):25-40, 2021
  12. Baladram MS, Koike A, Yamada KD, Introduction to supervised machine learning for data science, Interdisciplinary Information Sciences, 26(1):87-121, 2020
  13. Katoh K, Rozewicki J, Yamada KD, MAFFT online service: multiple sequence alignment, interactive sequence choice and visualization, Briefings in Bioinformatics, 20(4):1160-1166, 2019
  14. Yasukawa K, Hirago A, Yamada K, Tun X, Ohkuma K, Utsumi H, In vivo redox imaging of dextran sodium sulfate-induced colitis in mice using Overhauser-enhanced magnetic resonance imaging, Free Radical Biology and Medicine, 136:1-11, 2019
  15. Yamada KD, Kinoshita K, De novo profile generation based on sequence context specificity with the long short-term memory network, BMC Bioinformatics, 19(1):272, 2018
  16. Nakamura T, Yamada KD, Tomii K, Katoh K, Parallelization of MAFFT for large-scale multiple sequence alignments, Bioinformatics, 34(14):2490-2492, 2018
  17. Yamada KD, Derivative-free neural network for optimizing the scoring functions associated with dynamic programming of pairwise-profile alignment, Algorithms for Molecular Biology, 13:5, 2018
  18. Yamada KD, Kunishima N, Matsuura Y, Nakai K, Naitow H, Fukasawa Y, Tomii K, Designing better diffracting crystals of biotin carboxyl carrier protein from Pyrococcus horikoshii by a mutation based on crystal-packing propensity of amino acids, Acta Crystallographica Section D, 73(9):757-766, 2017
  19. Yamada KD, Omori S, Nish H, Miyagi M, Identification of the sequence determinants of protein N-terminal acetylation through a decision tree approach, BMC Bioinformatics, 18(1):289, 2017
  20. Lim K, Yamada KD, Frith MC, Tomii K, Protein sequence-similarity search acceleration using a heuristic algorithm with a sensitive matrix, Journal of Structural and Functional Genomics, 17(4):147-154, 2016
  21. Yamada KD, Tomii K, Katoh K, Application of the MAFFT sequence alignment program to large data - reexamination of the usefulness of chained guide trees, Bioinformatics, 32(21):3246-3251, 2016
  22. Imamura T, Fujita K, Tagawa K, Ikura T, Chen X, Homma H, Tamura T, Mao Y, Taniguchi JB, Motoki K, Nakabayashi M, Ito N, Yamada K, Tomii K, Okano H, Kaye J, Finkbeiner S, Okazawa H, Identification of hepta-histidine as a candidate drug for Huntington’s disease by in silico-in vitro-in vivo-integrated screens of chemical libraries, Scientific Reports, 6:33861, 2016
  23. Lensink MF, Velankar S, Kryshtafovych A, Huang SY, Schneidman-Duhovny D, Sali A, Segura J, Fernandez-Fuentes N, Viswanath S, Elber R, Grudinin S, Popov P, Neveu E, Lee H, Baek M, Park S, Heo L, Rie Lee G, Seok C, Qin S, Zhou HX, Ritchie DW, Maigret B, Devignes MD, Ghoorah A, Torchala M, Chaleil RA, Bates PA, Ben-Zeev E, Eisenstein M, Negi SS, Weng Z, Vreven T, Pierce BG, Borrman TM, Yu J, Ochsenbein F, Guerois R, Vangone A, Rodrigues JP, van Zundert G, Nellen M, Xue L, Karaca E, Melquiond AS, Visscher K, Kastritis PL, Bonvin AM, Xu X, Qiu L, Yan C, Li J, Ma Z, Cheng J, Zou X, Shen Y, Peterson LX, Kim HR, Roy A, Han X, Esquivel-Rodriguez J, Kihara D, Yu X, Bruce NJ, Fuller JC, Wade RC, Anishchenko I, Kundrotas PJ, Vakser IA, Imai K, Yamada K, Oda T, Nakamura T, Tomii K, Pallara C, Romero-Durana M, Jiménez-García B, Moal IH, Férnandez-Recio J, Joung JY, Kim JY, Joo K, Lee J, Kozakov D, Vajda S, Mottarella S, Hall DR, Beglov D, Mamonov A, Xia B, Bohnuud T, Del Carpio CA, Ichiishi E, Marze N, Kuroda D, Roy Burman SS, Gray JJ, Chermak E, Cavallo L, Oliva R, Tovchigrechko A, Wodak SJ, Prediction of homoprotein and heteroprotein complexes by protein docking and template‐based modeling: A CASP‐CAPRI experiment, Proteins, 84(S1):323-348, 2016
  24. Kakisaka M, Yamada K, Yamaji-Hasegawa A, Kobayashi T, Aida Y, Intrinsically disordered region of influenza A NP regulates viral genome packaging via interactions with viral RNA and host PI(4,5)P2, Virology, 496:116-126, 2016
  25. Yamada KD, Nishi H, Nakata J, Kinoshita K, Structural characterization of single nucleotide variants at ligand binding sites and enzyme active sites of human proteins, Biophysics and Physicobiology, 13:157-163, 2016
  26. Tomii K, Yamada K, Systematic exploration of an efficient amino acid substitution matrix: MIQS, Methods in Molecular Biology, 1415:211-223, 2016
  27. Polat M, Takeshima SN, Hosomichi K, Kim J, Miyasaka T, Yamada K, Arainga M, Murakami T, Matsumoto Y, de la Barra Diaz V, Panei CJ, González ET, Kanemaki M, Onuma M, Giovambattista G, Aida Y, A new genotype of bovine leukemia virus in South America identified by NGS-based whole genome sequencing and molecular evolutionary genetic analysis, Retrovirology, 13(1):4, 2016
  28. Kakisaka M, Sasaki Y, Yamada K, Kondoh Y, Hikono H, Osada H, Tomii K, Saito T, Aida Y, A novel antiviral target structure involved in the RNA binding, dimerization, and nuclear export functions of the influenza A virus nucleoprotein, PLOS Pathogens, 11(7):e1005062, 2015
  29. Ito JI, Ikeda K, Yamada K, Mizuguchi K, Tomii K, PoSSuM v.2.0: data update and a new function for investigating ligand analogs and target proteins of small-molecule drugs, Nucleic Acids Research, 43(D1):D392-D398, 2015
  30. 山田和範, 富井健太郎, 遠縁タンパク質検索に適した新規アミノ酸置換行列, 生物物理, 55(3):133-136, 2015
  31. Chutiwitoonchai N, Kakisaka M, Yamada K, Aida Y, Comparative analysis of seven viral nuclear export signals (NESs) reveals the crucial role of nuclear export mediated by the third NES consensus sequence of nucleoprotein (NP) in influenza A virus replication, PLOS ONE, 9(8):e105081, 2014
  32. Yamada K, Tomii K, Revisiting amino acid substitution matrices for identifying distantly related proteins, Bioinformatics, 30(3):317-325, 2014
  33. Sasaki Y, Hagiwara K, Kakisaka M, Yamada K, Murakami T, Aida Y, Importin α3/Qip1 is involved in multiplication of mutant influenza virus with alanine mutation at amino acid 9 independently of nuclear transport function, PLOS ONE, 8(1):e55765, 2013
  34. Yamada K, Koyama H, Hagiwara K, Ueda A, Sasaki Y, Kanesashi SN, Ueno R, Nakamura HK, Kuwata K, Shimizu K, Suzuki M, Aida Y, Identification of a novel compound with antiviral activity against influenza A virus depending on PA subunit of viral RNA polymerase, Microbes and Infection, 14(9):740-747, 2012
  35. Hagiwara K, Kondoh Y, Ueda A, Yamada K, Goto H, Watanabe T, Nakata T, Osada H, Aida Y, Discovery of novel antiviral agents directed against the influenza A virus nucleoprotein using photo-cross-linked chemical arrays, Biochemical and Biophysical Research Communications, 394:721-727, 2010
  36. Preprint Entries

  37. Yamada KD, Appendable memory system towards permanent memory for artificial intelligence to acquire new knowledge after deployment, bioRxiv, 2023.05.25.542376, 2023
  38. Yamada KD, Baladram MS, Lin F, Relation is an option for processing context information, bioRxiv, 2022.04.14.488336, 2022
  39. Yan Z, Omori S, Yamada KD, Nishi H, Kinoshita K, Prediction and characterization of disorder-order transition regions in proteins by deep learning, bioRxiv, 2021.06.11.448022, 2021
  40. Yamada KD, Lin F, Nakamura T, Developing a novel recurrent neural network architecture with fewer parameters and good learning performance, bioRxiv, 2020.04.08.031484, 2020
  41. Yamada KD, Hyperparameter-free optimizer of gradient-descent method incorporating unit correction and moment estimation, bioRxiv, 348557, 2018
  42. Yamada KD, Kinoshita K, De novo profile generation based on sequence context specificity with the long short-term memory network, bioRxiv, 240515, 2018
  43. Yamada KD, Optimizing scoring function of dynamic programming of pairwise profile alignment using derivative free neural network, bioRxiv, 182493, 2018

あまりにも多いので明記しますが「何の興味もない研究ドメインにて深層学習モデル作ってください」みたいな,やってるこっちが何も面白くない「共同研究」という名のだたの下働きのお誘い,そんなことに費やす時間はないのでぜひご遠慮下さい.ご自身に置き換えて想像してみてください.「あなたと共同研究したいです.エクセル使ってひたすら足し算してくれますか?」みたいな共同研究したいですか?

深層学習を含むデータ科学はアカデミアにおいてはコモディティ化しつつあります.情報科学の研究者が共同研究者からデータを預かってデータ科学を適用することが良しとされたフェーズはずっと前に終わっています.ぜひ各研究ドメインでデータ科学を使ってください.アカデミアの情報科学の研究者にはもっと別の役割があることをご理解ください.いやホントマジでそろそろ理解してください.

現在のところ,東北大学国際放射光イノベーションスマート研究センター,情報科学研究科,多元物質科学研究所,東北メディカルメガバンク,これら以外からのお誘いは以下の場合を除いて,誘っていただいても受けません.日本の文化に則って断ってんのかそうじゃないのかよくわからん文言で断るのマジで面倒なので絶対誘ってこないでください.

プログラム書かないし計算機実験もしないで良くて,開発中のアルゴリズムをそのまま計画書に取り込みたいというなら受けます.また,人工知能に関する知識を共有してほしいというのも受けます.または,年間1000万円を複数年くれて,その予算で研究員を雇用して,その方に研究してもらうということで良いなら受けます.「年間数百万円自由に使って良いですから」みたいなん,いやいや要らん要らん.お金は困ってないです.時間がほしいです.想像してください.あなたのこと育ててくれた学生時代の研究室のヘッド,自らプログラム書いてたくさん計算機実験できるほどの余裕ありましたか?管理とか運営とか教育とかに追われていませんでしたか?そういうことです.

  1. Research Award, Yamada KD, Kinoshita K, Development of de novo generator of amino acid sequence profile using LSTM framework, IIBMP2017, 2017
  2. Excellent Poster Award, Yamada K, Tomii K, Development of a novel amino acid substitution matrix for remote homology detection, IIBMP2013, 2013
  3. Poster Award, Yamada K, Tomii K, Developing a novel amino acid substitution matrix suitable for detecting distantly related proteins, BiWO2013, 2013
Algorithm to process context information of sequential data with good time complexity.
Recurrent neural network with good space complexity.
De novo profile generator based on recurrent neural network.
N-terminal acetylation predictor based on decision tree classification.
PSSM-PSSM pairwise aligner with neural network enhanced scoring function of dynamic programming.
Benchmark results of MAFFT-sparasecore and other methods on large scale dataset.

2023

  • 先端応用データ解析, Tohoku University, Fall semester
  • 先端技術の基礎と実践, Tohoku University, Fall semester
  • Data Science Training Camp II / Big Data Challenge, Tohoku University, Fall semester
  • 学際情報科学論, Tohoku University, Fall semester
  • ドメインデータサイエンティスト養成講座, Tohoku University, Fall semester
  • Google Colaboratoryを利用したKaggle問題解決, Tohoku University, Fall semester

2022

  • Data Science Training Camp II / Big Data Challenge, Tohoku University, Spring semester
  • 先端技術の基礎と実践, Tohoku University, Fall semester
  • 学際情報科学論, Tohoku University, Fall semester
  • ドメインデータサイエンティスト養成講座, Tohoku University, Fall semester

2021

  • Data Science Training Camp II / Big Data Challenge, Tohoku University, Spring semester
  • Data Science Training Camp II / Big Data Challenge, Tohoku University, Fall semester
  • 学際情報科学論, Tohoku University, Fall semester
  • 仙台X-Techプロジェクト遂行型学習, Tohoku University, Fall semester

2020

  • Data Science Training Camp II / Big Data Challenge, Tohoku University, Spring semester
  • Data Science Training Camp II / Big Data Challenge, Tohoku University, Fall semester
  • 学際情報科学論, Tohoku University, Fall semester
  • 数理工学PBL深層学習講習会, Osaka University, Fall semester

2019

  • Big Data Skill-up Training, Tohoku University, Spring semester
  • Data Science Training Camp I, Tohoku University, Spring semester
  • Data Science Training Camp II / Big Data Challenge, Tohoku University, Spring semester
  • Applied Data Science, Tohoku University, Spring semester
  • Big Data Skill-up Training, Tohoku University, Fall semester
  • Data Science Training Camp I, Tohoku University, Fall semester
  • Data Science Training Camp II / Big Data Challenge, Tohoku University, Fall semester
  • Data Science Basic, Tohoku University, Fall semester
  • 学際情報科学論, Tohoku University, Fall semester
  • スーパーコンピューターを利用した深層学習講習会, Osaka University, Fall semester

2018

  • Big Data Skill-up Training, Tohoku University, Spring semester
  • Data Science Training Camp I, Tohoku University, Spring semester
  • Data Science Training Camp II / Big Data Challenge, Tohoku University, Spring semester
  • Big Data Skill-up Training, Tohoku University, Fall semester
  • Data Science Training Camp I, Tohoku University, Fall semester
  • Data Science Training Camp II / Big Data Challenge, Tohoku University, Fall semester
  • PythonユーザーのためのGPUコンピューティング, Osaka University, Fall semester

2017

  • Data Science Training Camp I, Tohoku University, Spring semester
  • Data Science Training Camp II / Big Data Challenge, Tohoku University, Spring semester
  • Big Data Skill-up Training, Tohoku University, Fall semester
  • Data Science Training Camp I, Tohoku University, Fall semester
  • Data Science Training Camp II / Big Data Challenge, Tohoku University, Fall semester

2016

  • Data Science Training Camp II / Big Data Challenge, Tohoku University, Spring semester
  • Big Data Skill-up Training, Tohoku University, Fall semester
  • Data Science Training Camp I, Tohoku University, Fall semester

2015

  • Big Data Skill-up Training, Tohoku University, Fall semester
  • Data Science Training Camp I, Tohoku University, Fall semester
  • 日本メディカルAI学会
  • 山田和範,人工知能で目指すアミノ酸配列類似性検索法の高速化および高感度化研究,科研費・若手研究,2018 - 2020
  • 加藤和貴,山田和範,富井健太郎,MAFFT多重アラインメントプログラムの大量配列データへの対応と機能拡張,科研費基盤研究C,2016 - 2020

Email: y[a-z]ma[a-z]a@tohoku.ac.jp

ハンター試験なのですがメールアドレスの2個の[a-z]はそれぞれ英語アルファベットの内の互いに異なる小文字1個です.

耳鳴りに悩む人に生きてほしくて,同じ病気(?)を持つ身からのメッセージです.