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@techouse-inc

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nodematerial/README.md

Career

  • Software Engineer at Techouse, Inc. 2022/09 ~
  • Master of Engineering (the University of Tokyo 2022 ~ 2024)
  • Bachelor of Engineering (the University of Tokyo 2018 ~ 2022)

Skills

Ruby, Ruby on Rails, Python3, Machine Learning

Sorfware

Researches

I used to major in material simulation&informatics

  • Molecular dynamics & Deep Learning (Master)
  • Microscophic image analysis (Bachelor)

Papers

  1. Prediction of potential energy profiles of molecular dynamic simulation by graph convolutional networks. Kota Noda, Yasushi Shibuta. Computational Materials Science. 229:112448, 2023.
  2. Predicting long-term trends in physical properties from short-term molecular dynamics simulations using long short-term memory. Kota Noda, Yasushi Shibuta. J Phys Condens Matter. 36:385902, 2024.
  • 卒業論文 : 画像解析と深層学習に基づく水性塗料成膜・硬化機構解明
  • 修士論文 : 深層学習による分⼦動⼒学の物理量時間発展モデル

Presentations

  • 深層⽣成モデルによる多結晶原⼦構造の特徴量抽出および復元 日本金属学会2022年秋期(第171回)講演大会 Kohei Sase, Kota Noda, Yasushi Shibuta
  • グラフニューラルネットワークを使用した深層学習モデルによる分子動力学シミュレーションの物理量予測 日本金属学会2023年秋期(第173回)講演大会 Kota Noda, Yasushi Shibuta
  • High-precision prediction of physical properties of molecular dynamic simulation using graph neural networks PRICM11 Kota Noda, Yasushi Shibuta

Competitions

Kaggle Competition Expert

  • Algorithm: highest 970
  • Heuristic: highest 414
  • atnacup#13 4 of 127 teams

Pinned Loading

  1. cch cch Public

    Browse, search and resume Claude Code conversations across projects

    Shell 1

  2. MD-GNN MD-GNN Public

    Implementation for "Prediction of potential energy profiles of molecular dynamic simulation by graph convolutional networks"

    Python 6

  3. Kaggle_amex Kaggle_amex Public

    code & solution of Kaggle American Express - Default Prediction competition

    Python 3 1

  4. MD-GNN_TimeSeries MD-GNN_TimeSeries Public

    Predicting long-term trends in physical properties from short-term MD simulations with GCN + LSTM (J. Phys.: Condens. Matter, 2024)

    Python