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津田 宏治

津田 宏治 (TSUDA, Koji) 0000-0002-4288-1606

Address
305-0044 茨城県つくば市並木1-1 [アクセス]

[論文] | [書籍] | [会議録] | [口頭発表] | [その他の文献] | [公開特許出願]

論文 TSV

2023
  1. Ryo Tamura, Koji Tsuda, Shoichi Matsuda. NIMS-OS: an automation software to implement a closed loop between artificial intelligence and robotic experiments in materials science. Science and Technology of Advanced Materials: Methods. 3 [1] (2023) 2232297 10.1080/27660400.2023.2232297 Open Access
  2. Kei Terayama, Yamato Osaki, Takehiro Fujita, Ryo Tamura, Masanobu Naito, Koji Tsuda, Toru Matsui, Masato Sumita. Koopmans’ Theorem-Compliant Long-Range Corrected (KTLC) Density Functional Mediated by Black-Box Optimization and Data-Driven Prediction for Organic Molecules. Journal of Chemical Theory and Computation. 19 [19] (2023) 6770-6781 10.1021/acs.jctc.3c00764
  3. Jiawen Li, Masato Sumita, Ryo Tamura, Koji Tsuda. Interpretable Fragment‐Based Molecule Design with Self‐Learning Entropic Population Annealing. Advanced Intelligent Systems. 5 [10] (2023) 2300189 10.1002/aisy.202300189 Open Access
  4. Weilin Yuan, Yusuke Hibi, Ryo Tamura, Masato Sumita, Yasuyuki Nakamura, Masanobu Naito, Koji Tsuda. Revealing factors influencing polymer degradation with rank-based machine learning. Patterns. (2023) 100846 10.1016/j.patter.2023.100846 Open Access
  5. Ryo Tamura, Kei Terayama, Masato Sumita, Koji Tsuda. Ranking Pareto optimal solutions based on projection free energy. Physical Review Materials. 7 [9] (2023) 093804 10.1103/physrevmaterials.7.093804 Open Access
  6. Zetian Mao, Yoshiki Matsuda, Ryo Tamura, Koji Tsuda. Chemical design with GPU-based Ising machines. Digital Discovery. 2 [4] (2023) 1098-1103 10.1039/d3dd00047h Open Access
  7. Andrejs Tučs, Francois Berenger, Akiko Yumoto, Ryo Tamura, Takanori Uzawa, Koji Tsuda. Quantum Annealing Designs Nonhemolytic Antimicrobial Peptides in a Discrete Latent Space. ACS Medicinal Chemistry Letters. 14 [5] (2023) 577-582 10.1021/acsmedchemlett.2c00487 Open Access
2022
  1. Ryo Tamura, Masato Sumita, Kei Terayama, Koji Tsuda, Fujio Izumi, Yoshitaka Matsushita. Automatic Rietveld refinement by robotic process automation with RIETAN-FP. Science and Technology of Advanced Materials: Methods. 2 [1] (2022) 435-444 10.1080/27660400.2022.2146470 Open Access
  2. Tomoki Yamashita, Hiori Kino, Koji Tsuda, Takashi Miyake, Tamio Oguchi. Hybrid algorithm of Bayesian optimization and evolutionary algorithm in crystal structure prediction. Science and Technology of Advanced Materials: Methods. 2 [1] (2022) 67-74 10.1080/27660400.2022.2055987 Open Access
  3. Yuji Kaiya, Ryo Tamura, Koji Tsuda. Understanding Chemical Processes with Entropic Sampling. Organic Process Research & Development. 26 [12] (2022) 3276-3282 10.1021/acs.oprd.2c00254
  4. Masato Sumita, Kei Terayama, Ryo Tamura, Koji Tsuda. QCforever: A Quantum Chemistry Wrapper for Everyone to Use in Black-Box Optimization. Journal of Chemical Information and Modeling. 62 [18] (2022) 4427-4434 10.1021/acs.jcim.2c00812 Open Access
  5. Yuichi Motoyama, Ryo Tamura, Kazuyoshi Yoshimi, Kei Terayama, Tsuyoshi Ueno, Koji Tsuda. Bayesian optimization package: PHYSBO. Computer Physics Communications. 278 (2022) 108405 10.1016/j.cpc.2022.108405 Open Access
  6. Jiawen Li, Jinzhe Zhang, Ryo Tamura, Koji Tsuda. Self-learning entropic population annealing for interpretable materials design. Digital Discovery. 1 [3] (2022) 295-302 10.1039/d1dd00043h Open Access
  7. Syun Izawa, Koki Kitai, Shu Tanaka, Ryo Tamura, Koji Tsuda. Continuous black-box optimization with an Ising machine and random subspace coding. Physical Review Research. 4 [2] (2022) 023062 10.1103/physrevresearch.4.023062 Open Access
  8. Masato Sumita, Kei Terayama, Naoya Suzuki, Shinsuke Ishihara, Ryo Tamura, Mandeep K. Chahal, Daniel T. Payne, Kazuki Yoshizoe, Koji Tsuda. De novo creation of a naked eye–detectable fluorescent molecule based on quantum chemical computation and machine learning. Science Advances. 8 [10] (2022) 10.1126/sciadv.abj3906 Open Access
  9. Xiaolin Sun, Ryo Tamura, Masato Sumita, Kenichi Mori, Kei Terayama, Koji Tsuda. Integrating Incompatible Assay Data Sets with Deep Preference Learning. ACS Medicinal Chemistry Letters. 13 [1] (2022) 70-75 10.1021/acsmedchemlett.1c00439 Open Access
2021
  1. 隅田 真人, 寺山慧, 田村 亮, 津田 宏治. 理論化学とブラックボックス最適化による物質探索. 理論化学会誌 フロンティア. (2021) 120-132
  2. Hanxiao Xu, Koki Kitai, Kosuke Minami, Makito Nakatsu, Genki Yoshikawa, Koji Tsuda, Kota Shiba, Ryo Tamura. Determination of quasi-primary odors by endpoint detection. Scientific Reports. 11 [1] (2021) 12070 10.1038/s41598-021-91210-6 Open Access
  3. Zhufeng Hou, Yoshiki Takagiwa, Yoshikazu Shinohara, Yibin Xu, Koji Tsuda. First-principles study of electronic structures and elasticity of Al2Fe3Si3. Journal of Physics: Condensed Matter. 33 [19] (2021) 195501 10.1088/1361-648x/abe474
  4. Kei Terayama, Masato Sumita, Ryo Tamura, Koji Tsuda. Black-Box Optimization for Automated Discovery. Accounts of Chemical Research. 54 [6] (2021) 1334-1346 10.1021/acs.accounts.0c00713
  5. Ryo Tamura, Toshio Osada, Kazumi Minagawa, Takuma Kohata, Masashi Hirosawa, Koji Tsuda, Kyoko Kawagishi. Machine learning-driven optimization in powder manufacturing of Ni-Co based superalloy. Materials & Design. 198 (2021) 109290 10.1016/j.matdes.2020.109290 Open Access
  6. Tomoki Yamashita, Shinichi Kanehira, Nobuya Sato, Hiori Kino, Kei Terayama, Hikaru Sawahata, Takumi Sato, Futoshi Utsuno, Koji Tsuda, Takashi Miyake, Tamio Oguchi. CrySPY: a crystal structure prediction tool accelerated by machine learning. Science and Technology of Advanced Materials: Methods. 1 [1] (2021) 87-97 10.1080/27660400.2021.1943171 Open Access
  7. I. Ohkubo, Z. Hou, J.N. Lee, T. Aizawa, M. Lippmaa, T. Chikyow, K. Tsuda, T. Mori. Realization of closed-loop optimization of epitaxial titanium nitride thin-film growth via machine learning. Materials Today Physics. 16 (2021) 100296 10.1016/j.mtphys.2020.100296 Open Access
2020
  1. Kenji Homma, Yu Liu, Masato Sumita, Ryo Tamura, Naoki Fushimi, Junichi Iwata, Koji Tsuda, Chioko Kaneta. Optimization of a Heterogeneous Ternary Li3PO4–Li3BO3–Li2SO4 Mixture for Li-Ion Conductivity by Machine Learning. The Journal of Physical Chemistry C. 124 [24] (2020) 12865-12870 10.1021/acs.jpcc.9b11654 Open Access
  2. Kei Terayama, Masato Sumita, Ryo Tamura, Daniel T. Payne, Mandeep K. Chahal, Shinsuke Ishihara, Koji Tsuda. Pushing property limits in materials discovery via boundless objective-free exploration. Chemical Science. 11 [23] (2020) 5959-5968 10.1039/d0sc00982b Open Access
  3. Xiaolin Sun, Zhufeng Hou, Masato Sumita, Shinsuke Ishihara, Ryo Tamura, Koji Tsuda. Data integration for accelerated materials design via preference learning. New Journal of Physics. 22 [5] (2020) 055001 10.1088/1367-2630/ab82b9 Open Access
  4. Koki Kitai, Jiang Guo, Shenghong Ju, Shu Tanaka, Koji Tsuda, Junichiro Shiomi, Ryo Tamura. Designing metamaterials with quantum annealing and factorization machines. Physical Review Research. 2 [1] (2020) 013319 10.1103/physrevresearch.2.013319 Open Access
2019
  1. Yukari Katsura, Masaya Kumagai, Takushi Kodani, Mitsunori Kaneshige, Yuki Ando, Sakiko Gunji, Yoji Imai, Hideyasu Ouchi, Kazuki Tobita, Kaoru Kimura, Koji Tsuda. Data-driven analysis of electron relaxation times in PbTe-type thermoelectric materials. Science and Technology of Advanced Materials. 20 [1] (2019) 511-520 10.1080/14686996.2019.1603885 Open Access
  2. Kei Terayama, Koji Tsuda, Ryo Tamura. Efficient recommendation tool of materials by an executable file based on machine learning. Japanese Journal of Applied Physics. 58 [9] (2019) 098001 10.7567/1347-4065/ab349b Open Access
  3. Masato Sumita, Ryo Tamura, Kenji Homma, Chioko Kaneta, Koji Tsuda. Li-Ion Conductive Li3PO4-Li3BO3-Li2SO4 Mixture: Prevision through Density Functional Molecular Dynamics and Machine Learning. Bulletin of the Chemical Society of Japan. 92 [6] (2019) 1100-1106 10.1246/bcsj.20190041
  4. Thaer M. Dieb, Shenghong Ju, Junichiro Shiomi, Koji Tsuda. Monte Carlo tree search for materials design and discovery. MRS Communications. 9 [02] (2019) 532-536 10.1557/mrc.2019.40 Open Access
  5. Zhufeng Hou, Yoshiki Takagiwa, Yoshikazu Shinohara, Yibin Xu, Koji Tsuda. Machine-Learning-Assisted Development and Theoretical Consideration for the Al2Fe3Si3 Thermoelectric Material. ACS Applied Materials & Interfaces. 11 [12] (2019) 11545-11554 10.1021/acsami.9b02381 Open Access
  6. Atsushi Sakurai, Kyohei Yada, Tetsushi Simomura, Shenghong Ju, Makoto Kashiwagi, Hideyuki Okada, Tadaaki Nagao, Koji Tsuda, Junichiro Shiomi. Ultranarrow-Band Wavelength-Selective Thermal Emission with Aperiodic Multilayered Metamaterials Designed by Bayesian Optimization. ACS Central Science. 5 [2] (2019) 319-326 10.1021/acscentsci.8b00802 Open Access
2018
  1. Shin Kiyohara, Tomohiro Miyata, Koji Tsuda, Teruyasu Mizoguchi. Data-driven approach for the prediction and interpretation of core-electron loss spectroscopy. Scientific Reports. 8 [1] (2018) 10.1038/s41598-018-30994-6 Open Access
  2. Kei Terayama, Tomoki Yamashita, Tamio Oguchi, Koji Tsuda. Fine-grained optimization method for crystal structure prediction. npj Computational Materials. 4 [1] (2018) 10.1038/s41524-018-0090-y Open Access
  3. Naruki Yoshikawa, Kei Terayama, Masato Sumita, Teruki Homma, Kenta Oono, Koji Tsuda. Population-based De Novo Molecule Generation, Using Grammatical Evolution. Chemistry Letters. 47 [11] (2018) 1431-1434 10.1246/cl.180665
  4. Masato Sumita, Xiufeng Yang, Shinsuke Ishihara, Ryo Tamura, Koji Tsuda. Hunting for Organic Molecules with Artificial Intelligence: Molecules Optimized for Desired Excitation Energies. ACS Central Science. 4 [9] (2018) 1126-1133 10.1021/acscentsci.8b00213 Open Access
  5. Kota Shiba, Ryo Tamura, Takako Sugiyama, Yuko Kameyama, Keiko Koda, Eri Sakon, Kosuke Minami, Huynh Thien Ngo, Gaku Imamura, Koji Tsuda, Genki Yoshikawa. Functional Nanoparticles-Coated Nanomechanical Sensor Arrays for Machine Learning-Based Quantitative Odor Analysis. ACS Sensors. 3 [8] (2018) 1592-1600 10.1021/acssensors.8b00450 Open Access
  6. Thaer M. Dieb, Zhufeng Hou, Koji Tsuda. Structure prediction of boron-doped graphene by machine learning. The Journal of Chemical Physics. 148 [24] (2018) 241716 10.1063/1.5018065 Open Access
  7. Tomoki Yamashita, Nobuya Sato, Hiori Kino, Takashi Miyake, Koji Tsuda, Tamio Oguchi. Crystal structure prediction accelerated by Bayesian optimization. Physical Review Materials. 2 [1] (2018) 013803 10.1103/physrevmaterials.2.013803 Open Access
2017
  1. Tien Lam Pham, Hiori Kino, Kiyoyuki Terakura, Takashi Miyake, Koji Tsuda, Ichigaku Takigawa, Hieu Chi Dam. Machine learning reveals orbital interaction in materials. Science and Technology of Advanced Materials. 18 [1] (2017) 756-765 10.1080/14686996.2017.1378060 Open Access
  2. Xiufeng Yang, Jinzhe Zhang, Kazuki Yoshizoe, Kei Terayama, Koji Tsuda. ChemTS: an efficient python library for de novo molecular generation. Science and Technology of Advanced Materials. 18 [1] (2017) 972-976 10.1080/14686996.2017.1401424 Open Access
  3. Thaer M. Dieb, Shenghong Ju, Kazuki Yoshizoe, Zhufeng Hou, Junichiro Shiomi, Koji Tsuda. MDTS: automatic complex materials design using Monte Carlo tree search. Science and Technology of Advanced Materials. 18 [1] (2017) 498-503 10.1080/14686996.2017.1344083 Open Access
  4. Hiromi Oda, Shin Kiyohara, Koji Tsuda, Teruyasu Mizoguchi. Transfer Learning to Accelerate Interface Structure Searches. Journal of the Physical Society of Japan. 86 [12] (2017) 123601 10.7566/jpsj.86.123601 Open Access
  5. Xiufeng Yang, Kazuki Yoshizoe, Akito Taneda, Koji Tsuda. RNA inverse folding using Monte Carlo tree search. BMC Bioinformatics. 18 [1] (2017) 10.1186/s12859-017-1882-7 Open Access
  6. Shenghong Ju, Takuma Shiga, Lei Feng, Zhufeng Hou, Koji Tsuda, Junichiro Shiomi. Designing Nanostructures for Phonon Transport via Bayesian Optimization. Physical Review X. 7 [2] (2017) 021024 10.1103/physrevx.7.021024 Open Access
2016
  1. David A. duVerle, Sohiya Yotsukura, Seitaro Nomura, Hiroyuki Aburatani, Koji Tsuda. CellTree: an R/bioconductor package to infer the hierarchical structure of cell populations from single-cell RNA-seq data. BMC Bioinformatics. 17 [1] (2016) 10.1186/s12859-016-1175-6 Open Access
  2. Motoki Shiga, Kazuyoshi Tatsumi, Shunsuke Muto, Koji Tsuda, Yuta Yamamoto, Toshiyuki Mori, Takayoshi Tanji. Sparse modeling of EELS and EDX spectral imaging data by nonnegative matrix factorization. Ultramicroscopy. 170 (2016) 43-59 10.1016/j.ultramic.2016.08.006 Open Access
  3. Aika Terada, Ryo Yamada, Koji Tsuda, Jun Sese. LAMPLINK: detection of statistically significant SNP combinations from GWAS data. Bioinformatics. (2016) btw418 10.1093/bioinformatics/btw418 Open Access
  4. Ichigaku Takigawa, Ken-ichi Shimizu, Koji Tsuda, Satoru Takakusagi. Machine-learning prediction of the d-band center for metals and bimetals. RSC Advances. 6 [58] (2016) 52587-52595 10.1039/c6ra04345c
  5. Shin Kiyohara, Hiromi Oda, Koji Tsuda, Teruyasu Mizoguchi. Acceleration of stable interface structure searching using a kriging approach. Japanese Journal of Applied Physics. 55 [4] (2016) 045502 10.7567/jjap.55.045502
2015
  1. Atsuto Seko, Atsushi Togo, Hiroyuki Hayashi, Koji Tsuda, Laurent Chaput, Isao Tanaka. Prediction of Low-Thermal-Conductivity Compounds with First-Principles Anharmonic Lattice-Dynamics Calculations and Bayesian Optimization. Physical Review Letters. 115 [20] (2015) 205901 10.1103/physrevlett.115.205901

書籍 TSV

2021
  1. 田村 亮, 津田 宏治. 第1章　材料インフォマティクスに適した機械学習法の開拓. (株)エヌ・ティー・エス, 2021, 8.
  2. 寺山慧, 隅田 真人, 田村 亮, 津田 宏治. 機械学習による例外的材料探索の効率化. 情報技術協会, 2021, 8.

会議録 TSV

2018
  1. JU Shenghong, DIEB, Sae, TSUDA, Koji, SHIOMI, Junichiro. Optimizing Interface/Surface Roughness for Thermal Transport. Machine Learning for Molecules and Materials NIPS 2018 Workshop. (2018) 9999-1-9999-7
  2. JU Shenghong, DIEB, Sae, TSUDA, Koji, SHIOMI, Junichiro. Designing Nanostructures for Heat Transport via Materials Informatics.. The 16th International Heat Transfer Conference. (2018) 9999-1-9999-8
2016
  1. Aika Terada, David duVerle, Koji Tsuda. Significant Pattern Mining with Confounding Variables. ADVANCES IN KNOWLEDGE DISCOVERY AND DATA MINING. (2016) 277-289 10.1007/978-3-319-31753-3_23

口頭発表 TSV

2023
  1. TAMURA, Ryo, TSUDA, Koji. Materials design by black-box optimization with Ising machine. MRM2023/IUMRS-ICA2023. 2023 招待講演
2022
  1. エン イリン, 日比 裕理, 田村 亮, 隅田 真人, 中村 泰之, 内藤 昌信, 津田 宏治. Preference learningを用いたデータ統合によるポリマー分解性のランキング予測. 第71回高分子討論会. 2022
2021
  1. 桂 ゆかり, 熊谷 将也, 間藤 智也, 安藤 有希, 田中 敦美, 坂本 吉宏, 藤田 絵梨奈, 木村 薫, 津田 宏治. Starrydata: A Curation Based Database of Published Plot Data in Materials Science. Martials Research Meeting 2021. 2021 招待講演
  2. 大久保 勇男, ホー ズーフォン, Jiyeon N. Lee, 相澤 俊, Mikk Lippmaa, 知京 豊裕, 津田 宏治, 森 孝雄. 機械学習を用いたTiNエピタキシャル成長のclosed-loop optimization. 第41回電⼦材料研究討論会. 2021
  3. 大久保 勇男, ホー ズーフォン, Jiyeon N. Lee, 相澤 俊, Mikk Lippmaa, 知京 豊裕, 津田 宏治, 森 孝雄. 機械学習を活用した薄膜成長のclosed-loop optimization. 第50回結晶成⻑国内会議(JCCG-50). 2021 招待講演
  4. 桂 ゆかり, 熊谷 将也, 間藤 智也, 安藤 有希, 田中 敦美, 坂本 吉宏, 藤田 絵梨奈, 木村 薫, 津田 宏治. 論文 からの実験 データ の蓄積と共有がもたらす革新と課題. 第82回応用物理学会秋季学術講演会. 2021 招待講演
  5. 高際 良樹, Zhufeng Hou, 津田 宏治, 池田 輝之, 小島 宏康. 実験・計算科学・機械学習を用いたFe-Al-Si熱電材料(FAST材)の研究. 第18回日本熱電学会学術講演会（TSJ2021）. 2021
2020
  1. 隅田真人, 田村 亮, 津田 宏治, 廣戸 孝信, 松下 能孝. COMBO を利用した経験的リートベルト解析法. 第24回準結晶研究会. 2020
  2. TSUDA, Koji, TAMURA, Ryo. Overview of Data Science Group. MI2I最終成果報告会. 2020
  3. SAKURAI, Atsushi, Kyohei Yada, Shenghong Ju, Makoto Kashiwagi, Hideyuki Okada, Tadaaki Nagao, TSUDA, Koji, SHIOMI, Junichiro. Ultra-narrowband wavelength-selective thermal emitter with multilayered metamaterials designed by Bayesian optimization. MI2I最終成果報告会. 2020
  4. YAMASHITA, Tomoki, Shinichi Kanehira, Nobuya Sato, KINO, Hiori, TSUDA, Koji, MIYAKE, Takashi, OGUCHI, Tamio. Development of Crystal Structure Prediction Method. MI2I最終成果報告会. 2020
  5. 津田 宏治. データ科学グループ研究報告. MI2I　最終報告会. 2020
2019
  1. YAMASHITA, Tomoki, 兼平　慎一, 佐藤　暢哉, KINO, Hiori, TSUDA, Koji, MIYAKE, Takashi, OGUCHI, Tamio. Hybrid Algorithm of Bayesian Optimization and Evolutionary algorithm in Crystal Structure Prediction. MATERIALS RESEARCH MEETING 2019. 2019
  2. TSUDA, Koji. Machine learning methods for designing new materials. 第１回産業科学AI センター主催国際シンポジウム. 2019
  3. 山下 智樹, 兼平慎一, 佐藤暢哉, 木野 日織, 津田 宏治, 三宅 隆, 小口 多美夫. 結晶構造探索におけるベイズ最適化と進化的アルゴリズムのハイブリッドアルゴリズム. 日本物理学会2019年秋季大会（物性）. 2019
  4. YAMASHITA, Tomoki, Nobuya Sato, Shinichi Kanehira, KINO, Hiori, TSUDA, Koji, MIYAKE, Takashi, OGUCHI, Tamio. Searching Efficiency of Bayesian Optimization and Evolutionary Algorithm in Crystal Structure Prediction. 10th International Conference on Materials for Advanced Technologies (ICMAT2019). 2019
  5. SAKURAI, Atsushi, Kyohei Yada, Tetsushi Simomura, 鞠 生宏, Makoto Kashiwagi, Makoto Kashiwagi, TSUDA, Koji, Hideyuki Okada, NAGAO, Tadaaki, SHIOMI, Junichiro. Ultra-Narrowband Wavelength-Selective Thermal Emitter and Absorber with Multi-Layered Metamaterials Designed by Bayesian Optimization. MRS spring meeting 2019. 2019
  6. JU Shenghong, DIEB, Sae, SHIOMI, Junichiro, TSUDA, Koji. Surface/Interface Roughness Optimization for Thermal Transport using Monte Carlo Tree Search. International Symposium on Materials Informatics. 2019
  7. 山下 智樹, 寺山慧, 兼平慎一, 佐藤暢哉, KINO, Hiori, TSUDA, Koji, MIYAKE, Takashi, OGUCHI, Tamio. Development of crystal structure prediction tool. さきがけマテリアルズインフォマティクス領域　国際シンポジウム. 2019
2018
  1. 津田 宏治. マテリアルズインフォマティクスを支えるアルゴリズム. 第79回応用物理学会秋季学術講演会. 特別シンポジウム. 2018
  2. 津田 宏治, 山下 智. 深層学習によって自動設計された有機分子の合成・評価. 第7回MI2Iフォーラム. 2018
  3. 山下 智樹, 佐藤暢哉, 佐藤暢哉, 木野 日織, 三宅 隆, 津田 宏治, 小口 多美夫. 結晶構造探索ソフトCrySPYの開発. 第7回MI2Iフォーラム. 2018
  4. 津田 宏治, 田村 亮. データ科学グループの最新研究紹介. 第7回MI2Iフォーラム. 2018
  5. DIEB, Sae, JU Shenghong, HOU, Zhufeng, SHIOMI, Junichiro, TSUDA, Koji. Materials Structure Design using Monte Carlo Tree Search with Bayesian rollout. ERATO Minato Discrete Manipulation System Project, Early Summer. 2018
2017
  1. 津田 宏治. Automatic design of functional molecules and materials with machine learning. CPMD2017. 2017
  2. 山下 智樹, 木野 日織, 津田 宏治, 小口 多美夫. ベイズ最適化を用いた高効率結晶構造探索手法の開発. 日本金属学会2017年秋期講演大会. 2017
  3. ディーブ モスタファ サエル, Shenghong Ju, Kazuki Yoshizoe, 塩見 淳一郎, 津田 宏治. Materials Design using Tree Search. The 15th International Confernece on Advanced Materials. 2017
  4. 鞠 生宏, ディーブ モスタファ サエル, 美添 一樹, 津田 宏治, 塩見 淳一郎. マテリアルズ・インフォマティクスによるフォノン輸送制御のためのナノ構造設計. 第54回 日本伝熱シンポジウム. 2017
  5. 山下 智樹, 三宅 隆, 小口 多美夫, 津田 宏治, 木野 日織. 結晶構造探索手法の開発. 日本物理学会　第72回年次大会. 2017
2016
  1. ディーブ モスタファ サエル, 津田 宏治. DAMAS: An Annotation Support Tool for Materials Information. The 5th Asian Materials Data Symposium. 2016
  2. 津田 宏治. 超基礎からのベイズ最適化. MI2Iチュートリアルセミナー (第3回). 2016
  3. ディーブ モスタファ サエル, Kazuki Yoshizoe, Shenghong Ju, 津田 宏治. Superlattice Structure Design Using Monte Carlo Tree Search. Machine learning meets many particles problems. 2016
  4. Shenghong Ju, Takuma Shiga, Lei Feng, ホー ズーフォン, 津田 宏治, 塩見 淳一郎. フォノン輸送制御を目的としたベイズ最適化による界面ナノ構造の設計. 2016 第77回 応用物理学会秋季学術講演会. 2016
  5. ディーブ モスタファ サエル, 津田 宏治, ホー ズーフォン. Potential Energy Prediction of Crystals using Kernel Methods. ERATO Minato Discrete Manipulation System Project, Early Summer. 2016
  6. 津田 宏治. データ科学グループについて. 第2回MI2Iフォーラム. 2016
  7. 津田 宏治. 物質・材料開発のための機械学習： 仮想スクリーニングとベイズ最適化. 第2回MI2Iフォーラム. 2016
2015
  1. 津田 宏治. マテリアルズ・インフォマティクス. マテリアルズインフォマテックスに関するワークショップ. 2015

その他の文献 TSV

2021
  1. 田村 亮, 長田 俊郎, 皆川 和己, 小幡 卓眞, 廣澤 正志, 津田 宏治, 川岸 京子. 機械学習による超合金粉末製造プロセス最適化. 季刊「溶射技術」. (2021) 56-62

公開特許出願 TSV

  1. 原臭選定方法、原臭の組み合わせによりニオイを表現、提示または合成する方法、及びそのための装置 (2023)
  2. 狭帯熱放射スペクトルを有する構造体 (2019)

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