KAZUNORI YAMADA PROFILE

Affiliation

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

Research Interests

人工意識 / 文脈情報処理のためのニューラルネットワーク / 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 / video game and entertainment

Collaboration

企業の方との共同研究は未踏スケールデータアナリティクスセンターのソーシャルインテグレーション研究部門のミッションのひとつであるため，これを積極的に行っています．

  • 企業からの研究の純粋なる請け負いはリソースが不足しているため困難ですが，研究員を雇用するのが可能な程度の研究費を頂ける場合にはさせていただきます．
  • これとは別に，学生の人が自発的に興味を持って取り組めるようなトピックであれば進めることが可能で，その場合，それほど大きな研究費は必要ないと思います．
  • また，この逆，企業より研究者をリモートで派遣いただいて，東北大学にて主宰する研究室に所属いただいて研究を進めることもできます．主に知識の提供，具体的には週1回程度の研究相談，研究室のセミナーに参加，研究室のSlackに参加していただくことを提供します．

アカデミアの方との共同研究については，本人が直接データの解析や人工知能の構築はできませんが，それでも良いならぜひお願いいたします．研究室の構成員が興味を持った場合なら研究を進めることができると思います．または，研究員を雇用できる程度の研究予算を頂けるなら可能と思います．

Research Achievements

    Peer-reviewed Papers

  1. Kodate S, Sato M, Hishinuma E, Kojima K, Motoike IN, ToMMo Study Group, Koshiba S, Yamamoto M, Yamada KD, Kinoshita K, Simulating Metabolic Pathways to Enhance Interpretations of Metabolome Genome-wide Association Studies, Scientific Reports, 2025
  2. Shigetome K, Egarashi T, Tomita T, Higa N, Iwashita K, Morita K, Nishimura M, Kankeko T, Maeda H, Yamada KD, Kajiwara-Morita A, Oniki K, Yasui-Furukori N, Saruwatari J, Effect of Cumulative Exposure on the Efficacy of Paroxetine: a Population Pharmacokinetic-pharmacodynamic and Machine Learning Analyses, Pharmacometrics and Systems Pharmacology, 2025
  3. Lin F, Liu H, Zhang Z, Morales J, Zhang HK, Yamada KD, Kolachalama V, Saligrama V, GPS: A Probabilistic Distributional Similarity with Gumbel Priors for Set-to-Set Matching, International Conference on Learning Representations, 2025
  4. Lin F, Liu H, Zhou H, Hou S, Yamada KD, Fischer GS, Li Y, Zhang H, Zhang Z, Loss Distillation via Gradient Matching for Point Cloud Completion with Weighted Chamfer Distance, IEEE/RSJ International Conference on Intelligent Robots and Systems, 2024
  5. Kubota A, Kodate S, Li Y, Lin F, Fukuda H, Baladram MS, Yamada KD, Learning Random Numbers to Realize Appendable Memory System for Artificial Intelligence to Acquire New Knowledge after Deployment, Interdisciplinary Information Sciences, 2024
  6. 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
  7. 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
  8. 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
  9. 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
  10. Maas A, Kawada T, Yamada K, Nagahama T, Horita T, Identifying latent traits of questions for controllable machine generation, EdMedia + Innovate Learning, 2022
  11. Yamada KD, Baladram MS, Lin F, Relation is an option for processing context information, Frontiers in Artificial Intelligence, 5:924688, 2022
  12. 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
  13. 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
  14. Yamada KD, Baladram MS, Lin F, Progress in research on implementing machine consciousness, Interdisciplinary Information Sciences, 28(1):95-105, 2022
  15. 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
  16. 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
  17. Baladram MS, Koike A, Yamada KD, Introduction to supervised machine learning for data science, Interdisciplinary Information Sciences, 26(1):87-121, 2020
  18. 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
  19. 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
  20. 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
  21. Nakamura T, Yamada KD, Tomii K, Katoh K, Parallelization of MAFFT for large-scale multiple sequence alignments, Bioinformatics, 34(14):2490-2492, 2018
  22. 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
  23. 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
  24. 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
  25. 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
  26. 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
  27. 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
  28. 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
  29. 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
  30. 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
  31. Tomii K, Yamada K, Systematic exploration of an efficient amino acid substitution matrix: MIQS, Methods in Molecular Biology, 1415:211-223, 2016
  32. 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
  33. 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
  34. 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
  35. 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
  36. 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
  37. Yamada K, Tomii K, Revisiting amino acid substitution matrices for identifying distantly related proteins, Bioinformatics, 30(3):317-325, 2014
  38. 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
  39. 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
  40. 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

    41. Preprint Entries

  41. Yamada KD, Appendable memory system towards permanent memory for artificial intelligence to acquire new knowledge after deployment, bioRxiv, 2023.05.25.542376, 2023
  42. Yamada KD, Baladram MS, Lin F, Relation is an option for processing context information, bioRxiv, 2022.04.14.488336, 2022
  43. 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
  44. 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
  45. Yamada KD, Hyperparameter-free optimizer of gradient-descent method incorporating unit correction and moment estimation, bioRxiv, 348557, 2018
  46. Yamada KD, Kinoshita K, De novo profile generation based on sequence context specificity with the long short-term memory network, bioRxiv, 240515, 2018
  47. Yamada KD, Optimizing scoring function of dynamic programming of pairwise profile alignment using derivative free neural network, bioRxiv, 182493, 2018

    48. Awards

  48. Research Award, Yamada KD, Kinoshita K, Development of de novo generator of amino acid sequence profile using LSTM framework, IIBMP2017, 2017
  49. Excellent Poster Award, Yamada K, Tomii K, Development of a novel amino acid substitution matrix for remote homology detection, IIBMP2013, 2013
  50. Poster Award, Yamada K, Tomii K, Developing a novel amino acid substitution matrix suitable for detecting distantly related proteins, BiWO2013, 2013

Research Products

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.

Classes

2024

  • Data Science Training II / Data Science Challenge, Tohoku University, Spring semester
  • 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
  • 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

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

Professional Memberships

  • なし

Grants

  • 富井健太郎，椿真史，池田修己，山田和範，効率的な分解誘導薬創成に向けた分子設計AIの基盤開発，NEDO先導研究プログラム，2023
  • 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

Contact

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．

X: @YamadaVaio

耳鳴りについて

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．