Details of the Researcher

PHOTO

Section
Graduate School of Information Sciences
Job title
Specially Appointed Associate Professor(Research)
Degree

  • Ph.D. (SOKENDAI (The Graduate University for Advanced Studies))

e-Rad No.
20639166

Research History 9

  • 2022/04 - Present
    Tohoku University　Graduate School of Information Sciences　Associate Professor

  • 2018/04 - 2022/03
    National Institute of Technology, Ichinoseki College　Division of Computer Engineering and Informatics, Department of Engineering for Future Innovation　Associate Professor

  • 2017/10 - 2022/03
    Tohoku University　Graduate School of Information Sciences　Collaborative Researcher

  • 2017/10 - 2018/03
    National Institute of Technology, Ichinoseki College　Division of Computer Engineering and Informatics, Department of Engineering for Future Innovation　Specially-Appointed Associate Professor

  • 2016/01 - 2017/09
    Tohoku University　Graduate School of Information Sciences　Assistant Professor

  • 2015/10 - 2015/12
    National Institute of Informatics　Researcher

  • 2012/05 - 2015/03
    National Institute of Informatics　Researcher

  • 2008/03 - 2012/04
    NAVITIME JAPAN Co., Ltd.

  • 2003/04 - 2008/02
    Hitachi, Ltd.　Consumer Electronics Laboratory

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Education 3

  • The University of Tokyo　Graduate School of Information Science and Technology　Special Research Student

    2014/04 - 2015/09

  • SOKENDAI (The Graduate University for Advanced Studies)　School of Multidisciplinary Sciences　The three-year Ph.D. course, Department of Informatics

    2012/10 - 2015/09

  • Tohoku University　Graduate School of Information Sciences　Master's course, System Information Sciences

    2001/04 - 2003/03

Committee Memberships 1

  • Tohoku branch, Information Processing Society of Japan　PR officer

    2022/06 - Present

Professional Memberships 2

  • Information Processing Society of Japan

    - Present

  • IEICE

Research Interests 8

  • Deep Learning

  • Machine Learning

  • user interface

  • Embedded Systems

  • GPU

  • graph algorithms

  • combinatorial optimization

  • parallel algorithms

Research Areas 4

  • Informatics / Intelligent informatics /

  • Informatics / Human interfaces and interactions /

  • Informatics / High-performance computing /

  • Informatics / Information theory /

Awards 2

  1. The 97th Conference Outstanding Presentation Award

    2024/05　IPSJ SIG-ITS　Wear Prediction for Aircraft Tires Considering Time Series Information

  2. Best Presentation Award

    2015/09　The 11th Workshop on Theoretical Computer Science　Fast Tree Reduction Algorithms on GPUs

Papers 7

  1. Introduction to Supervised Machine Learning for Data Science Peer-reviewed

    Mohammad Samy BALADRAM, Atsushi KOIKE, Kazunori D YAMADA

    Interdisciplinary Information Sciences　26　(1)　87-121　2020

    Publisher: Graduate School of Information Sciences, Tohoku University

    DOI： 10.4036/iis.2020.a.03 　

    ISSN： 1340-9050

    eISSN： 1347-6157

  2. Model-Agnostic Explanations for Decisions using Minimal Patterns International-journal Peer-reviewed

    Kohei Asano, Jinhee Chun, Atsushi Koike, Takeshi Tokuyama

    28th International Conference on Artificial Neural Networks (ICANN2019)　241-252　2019/09

    Publisher: Springer International Publishing

    DOI： 10.1007/978-3-030-30487-4_19 　

    ISSN： 0302-9743

    eISSN： 1611-3349

  3. A Computational Model and Algorithms to Utilize GPUs for Discrete Problems

    Atsushi Koike

    PhD Thesis, SOKENDAI (The Graduate University for Advanced Studies)　2015/09

  4. A Novel Computational Model for GPUs with Applications to Efficient Algorithms Peer-reviewed

    Atsushi Koike, Kunihiko Sadakane

    International Journal of Networking and Computing　5　(1)　26-60　2015/01

    Publisher: IJNC Editorial Committee

    DOI： 10.15803/ijnc.5.1_26 　

    ISSN： 2185-2839

    More details Close

    We propose a novel computational model for GPUs. Known parallel computational models such as the PRAM model are not appropriate for evaluating GPU-based algorithms. Our model, called AGPU, abstracts the essence of current GPU architectures such as global and shared memory, memory coalescing and bank conflicts. Using our model, we can evaluate asymptotic behavior of GPU algorithms more efficiently than the known models and we can develop algorithms that run fast on real GPU devices.As a showcase, we analyze the asymptotic behavior of basic existing algorithms including reduction, prefix scan, and comparison sorting. We further develop new algorithms by detecting and resolving performance bottlenecks of the existing algorithms. Our reduction algorithm has the optimal time and I/O complexities and works with non-commutative operators. Our comparison sorting algorithm has the optimal I/O complexity. Additionally, we show our algorithms run faster than the existing algorithms not only in theory but also in practice.

  5. A Novel Computational Model for GPUs with Application to I/O Optimal Sorting Algorithms Peer-reviewed

    Atsushi Koike, Kunihiko Sadakane

    PROCEEDINGS OF 2014 IEEE INTERNATIONAL PARALLEL & DISTRIBUTED PROCESSING SYMPOSIUM WORKSHOPS (IPDPSW)　615-624　2014

    DOI： 10.1109/IPDPSW.2014.72 　

  6. Labeling points with rectangles of various shapes Peer-reviewed

    A Koike, SI Nakano, T Nishizeki, T Tokuyama, S Watanabe

    INTERNATIONAL JOURNAL OF COMPUTATIONAL GEOMETRY & APPLICATIONS　12　(6)　511-528　2002/12

    DOI： 10.1142/S0218195902001018 　

    ISSN： 0218-1959

  7. New functions of scanning nonlinear dielectric microscopy - Higher-order measurement and vertical resolution Peer-reviewed

    YS Cho, K Ohara, A Koike, H Odagawa

    JAPANESE JOURNAL OF APPLIED PHYSICS PART 1-REGULAR PAPERS SHORT NOTES & REVIEW PAPERS　40　(5B)　3544-3548　2001/05

    DOI： 10.1143/JJAP.40.3544 　

    ISSN： 0021-4922

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Misc. 21

  1. Glass-Box Deep Learning Models with Both Flexibility and Explainability

    Atsushi Koike

    IEICE Technical Report　124　(413)　127-132　2025/03

  2. Wear Prediction for Aircraft Tires Considering Time Series Information

    RYO HANADA, ATSUSHI KOIKE

    SIG Technical Reports　2024-ITS-97　(1)　1-7　2024/05

  3. Gait Modeling for Estimating Mild Cognitive Impairment by Self-Supervised Learning

    Taiki Sato, Atsushi Koike, Akihiro Suzuki, Tomomichi Hayakawa

    (T23-1-11)　2023/11

  4. Early Detection of Dementia by Gait Analysis Using Machine Learning

    Yuta Kikuchi, Atsushi Koike, Akihiro Suzuki, Tomomichi Hayakawa

    (T23-3-03)　2023/11

  5. 手描き画像からキャラクター画像を生成するニューラルネットワークの構築

    上山由章, 千田栄幸, 小池敦

    令和4年東北・北海道地区高等専門学校専攻科 産学連携シンポジウム　2022/11/26

  6. ユーザー属性を保持したパスワード付き顔変換手法の提案

    髙橋源輝, 千田栄幸, 小池敦

    令和4年東北・北海道地区高等専門学校専攻科 産学連携シンポジウム　2022/11/26

  7. An Image Classification Model Featuring Explainability by Image Morphing

    Taiki Sato, Atsushi Koike

    The 84th National Convention of IPSJ　(2P-02)　2022/03

  8. Why are GPUs utilized for AI calculation?

    Atsushi Koike et al.

    I/O November 2020.　45　(11)　37-40　2020/11

    Publisher: Kohgakusha

  9. DS-1-9 Implementation and Evaluation of GPU-based Comparison Sorting Algorithms

    Koike Atsushi, Sadakane Kunihiko

    Proceedings of the IEICE General Conference　2014　(1)　"S-17"-"S-18"　2014/03/04

    Publisher: The Institute of Electronics, Information and Communication Engineers

  10. I/O Optimal Comparison Sorting Algorithms for GPUs

    Atsushi Koike, Kunihiko Sadakane

    HPCS2014　2014/01

  11. GPUを用いた並列ソートアルゴリズムの実装と評価

    小池敦, 定兼邦彦

    研究報告アルゴリズム（AL）　2013　(16)　1-8　2013/10/30

    Publisher: 一般社団法人情報処理学会

    ISSN： 0913-5685

    More details Close

    GPU を用いた並列比較ソートアルゴリズムを扱う．GPU 上でプログラムを高速動作させる場合，コアの計算量だけでなくメモリアクセスについても適切に考慮する必要がある．筆者らは GPU 上のアルゴリズムを評価するためのモデルとして AGPU モデルを提案しており，本モデルでは I/O 計算量を用いることにより，メモリアクセスの評価を行うことができる．また，筆者らは GPU 上での比較ソートに関して，I/O 計算量のオーダーが理論的な下界と一致するアルゴリズムを提案している．本稿ではアルゴリズムを実装し，実 GPU 上で評価を行うことで，本アルゴリズムの有効性を示す．

  12. GPUを用いた並列ソートアルゴリズムの実装と評価(グラフ,ペトリネット,ニューラルネット及び一般)

    小池 敦, 定兼 邦彦

    電子情報通信学会技術研究報告. MSS, システム数理と応用　113　(279)　91-98　2013/10/30

    Publisher: 一般社団法人電子情報通信学会

    More details Close

    GPUを用いた並列比較ソートアルゴリズムを扱う. GPU上でプログラムを高速動作させる場合,コアの計算量だけでなくメモリアクセスについても適切に考慮する必要がある.筆者らはGPU上のアルゴリズムを評価するためのモデルとしてAGPUモデルを提案しており,本モデルではI/O計算量を用いることにより,メモリアクセスの評価を行うことができる.また,筆者らはGPU上での比較ソートに関して, I/O計算量のオーダーが理論的な下界と一致するアルゴリズムを提案している.本稿ではアルゴリズムを実装し,実GPU上で評価を行うことで,本アルゴリズムの有効性を示す.

  13. Parallel Computational Model for GPU-based Algorithms

    Atsushi Koike, Kunihiko Sadakane

    GPU Technology Conference Japan 2013　2013/07

  14. On Complexities of Parallel Sort Algorithms on AGPU model

    KOIKE Atsushi, SADAKANE Kunihiko, VU Hoa

    IEICE technical report. Theoretical foundations of Computing　113　(50)　75-80　2013/05/17

    Publisher: The Institute of Electronics, Information and Communication Engineers

    ISSN： 0913-5685

    More details Close

    This paper is concerned with complexities of parallel sorting algorithms on AGPU model. First, we analyze known sort algorithms such as bitonic sort and GPU-Warpsort. Next, we give a lower bound of I/O complexities of comparison-based sorting algorithms on AGPU model. Let b be the number of cores in a multiprocessor, p be the total number of cores, and M be the total number of words in shared memories in multiprocessors. Then the necessary number of global memory accesses to comparison-sort n elements is shown to be Ω(n/b log_<M/p> n/b). We also propose a sorting algorithm whose I/O complexity matches this lower bound. Its time complexity is O(n/p log n/b log b).

  15. On Complexities of Parallel Sort Algorithms on AGPU model

    Atsushi Koike, Kunihiko Sadakane, Hoa Vu

    IPSJ SIG Notes　2013　(12)　1-6　2013/05/10

    Publisher: Information Processing Society of Japan (IPSJ)

    ISSN： 0919-6072

    More details Close

    This paper is concerned with complexities of parallel sorting algorithms on AGPU model. First, we analyze known sort algorithms such as bitonic sort and GPU-Warpsort. Next, we give a lower bound of I/O complexities of comparison-based sorting algorithms on AGPU model. Let b be the number of cores in a multiprocessor, p be the total number of cores, and M be the total number of words in shared memories in multiprocessors. Then the necessary number of global memory accesses to comparison-sort n elements is shown to be Ω(n/b log M/p n/b). We also propose a sorting algorithm whose I/O complexity matches this lower bound. Its time complexity is O(n/p log n/b log b).

  16. Abstract Computation Model for Analyzing Complexity of GPU-based Algorithms Peer-reviewed

    Atsushi Koike, Kunihiko Sadakane

    Proceedings of AAAC　2013/04

  17. DS-1-13 The Effect of Multi-threading in the AGPU model

    KOIKE Atsushi, SADAKANE Kunihiko

    Proceedings of the IEICE General Conference　2013　(1)　"S-25"-"S-26"　2013/03/05

    Publisher: The Institute of Electronics, Information and Communication Engineers

  18. A Novel Computation Model for GPU

    Atsushi Koike, Kunihiko Sadakane

    HPCS2013　2013/01/15

  19. Implementation and Computational Evaluation of Fast Map Labeling Algorithm

    KOIKE Atsushi, TOKUYAMA Takeahi

    IEICE technical report. Theoretical foundations of Computing　102　(396)　9-16　2002/10/17

    Publisher: The Institute of Electronics, Information and Communication Engineers

    ISSN： 0913-5685

    More details Close

    We deal with a map-labeling problem, named LOFL(Left-part Ordered Flexible Labeling). The label for each object point is selected from a set of rectangles with various shapes which satisfies the left-part ordered property, and is placed after scaled by a scaling factor σ which is common to all object points. The label must be placed so that other labels or polygonal obstacle may not be intersected. In this paper we implement the fast algorithm which finds the optimal (maximum) scaling factor and evaluate the scaling factor at some variations of LOFL. It turns out that the scaling factor changes greatly with variations. Moreover,it is shown that the technique of limiting label candidates for the sake of having left-part ordered property and solving the optimal solution of LOFL is effictive to a pratical map-labeling problem.

  20. A-12 Implementation of Left-part Ordered Flexible Labeling

    Koike Atsushi, Tokuyama Takeshi

    2002　(1)　23-24　2002/09/13

    Publisher: Forum on Information Technology

  21. New Functions of Scanning Nonlinear Dielectric Microscopy : Higher Order Measurement and Vertical Resolution

    CHO Yasuo, OHARA Koya, KOIKE Atsushi, ODAGAWA Hiroyuki

    IEICE technical report. Ultrasonics　100　(291)　9-15　2000/09/12

    Publisher: The Institute of Electronics, Information and Communication Engineers

    ISSN： 0913-5685

    More details Close

    Recently, we have proposed and developed the SNDM, which is a new, purely electrical technique for imaging the state of ferroelectric polarization and the local crystal anisotropy of dielectric materials. This time, we investigated the new functions of SNDM, which are measurement of the higher order nonlinear dielectric constant and the vertical resolution of SNDM. It is expected to obtain the higher resolution by the higher order measurement than that by the conventional SNDM imaging. Moreover, using the very high vertical resolution of SNDM, a new microscopy for measuring the microscopic topography and a new displacement sensor for the very small will be available.

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Books and Other Publications 1

  1. 図解深層学習 : 数理で理解する基本原理

    小池, 敦

    近代科学社　2023/12

    ISBN: 9784764906754

Presentations 22

  1. Explainability in Machine Learning Invited

    Atsushi Koike

    [CDLE Miyagi] 1st Study Session　2024/12/06

  2. GPU programming with super computers Invited

    Atsushi Koike

    2020/03/01

  3. Deep learning with web applications Invited

    Atsushi Koike

    2020/02/29

  4. A GPU-based Non-commutative Reduction and Its Applications to Operations for Difference Arrays

    Atsushi Koike, Kunihiko Sadakane

    Technical Committee on Theoretical Foundations of Computing , IEICE　2019/03/18

  5. GPU-Based Non-Commutative Reduction and It's Applications Invited

    Atsushi Koike

    Workshop on Mathematical Engineering　2019/03/03

  6. Introduction to GPU Programming Invited

    Atsushi Koike

    Workshop on Mathematical Engineering　2018/11/14

  7. Efficient Pruned Searches for Shortest Path Queries in Directed Road Networks

    Atsushi Koike

    SIGAL　2018/05/26

  8. A New Strategy for Solving N-Person Perfect Information Stochastic Games via Pareto Optimal Strategy Enumeration International-presentation

    Takanari Seito, Matias Korman, Atsushi Koike, Takeshi Tokuyama

    AAAC2017　2017/05/06

  9. Bicluster Mining by Data Cleaning like Approach

    Takeaki Uno, Atsushi Koike, Takanobu Nakahara, Yukinobu Hamuro

    SIGAL　2017/03/13

  10. Pruned Tree Labeling Algorithms for Shortest Path Queries in Road Networks

    Atsushi Koike, Kunihiko Sadakane

    SIGAL　2016/09/23

  11. Shortest Path Query Algorithms in Road Networks Using Pruned Tree Labeling

    Atsushi Koike, Kunihiko Sadakane

    LA 2016 Summer　2016/07/21

  12. A Tree-based Labeling Algorithm for Shortest Path Queries in Road Networks International-presentation

    Atsushi Koike

    AAAC 2016　2016/05/15

  13. Fast tree reduction algorithms utilizing GPUs

    Atsushi Koike, Kunihiko Sadakane

    WTCS2015　2015/09/17

  14. GPU-based parallel sorting algorithms

    Atsushi Koike, Kunihiko Sadakane

    WTCS2014　2014/09/18

  15. Implementation and Evaluation of GPU-based Comparison Sorting Algorithms

    Atsushi Koike, Kunihiko Sadakane

    Proceedings of the 2014 IEICE General Conference　2014/03/19

  16. Implementation and Evaluation of Parallel Comparison Sorting Algorithms using GPUs

    Atsushi Koike, Kunihiko Sadakane

    IPSJ SIG Notes　2013/11/07

  17. On Complexities of Parallel Sort Algorithms on AGPU model

    Atsushi Koike, Kunihiko Sadakane, Hoa Vu

    IEICE technical report. Theoretical foundations of Computing　2013/05/17

  18. Abstract Computation Model for Analyzing Complexity of GPU-based Algorithms International-presentation

    Atsushi Koike, Kunihiko Sadakane

    The 6th Annual Meeting of Asian Association for Algorithms and Computation (AAAC2013)　2013/04/20

  19. The Effect of Multi-threading in the AGPU model

    Atsushi Koike, Kunihiko Sadakane

    IEICE Technical Report　2013/03

  20. A Novel Computation Model for GPU

    Atsushi Koike, Kunihiko Sadakane

    IEICE technical report. Theoretical foundations of Computing　2012/10

  21. Implementation and Computational Evaluation of Fast Map Labeling Algorithm.

    KOIKE ATSUSHI, TOKUYAMA TAKESHI

    IEICE Technical Report　2002/10

  22. Implementation of Left-part Ordered Flexible Labeling

    Atsushi Koike, Takeshi Tokuyama

    FIT2002　2002/09

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Industrial Property Rights 31

  1. 経路探索システム、経路探索方法、および、プログラム

    太田 恒平, 小池 敦

    Property Type: Patent

  2. 経路探索システム、経路探索方法、および、プログラム

    太田 恒平, 小池 敦

    特許第5925354号

    Property Type: Patent

  3. 走行速度関連情報管理装置、ナビゲーション装置、走行速度関連情報管理システム、ナビゲーションシステム、走行速度関連情報管理サーバ、ナビゲーションサーバ、走行速度関連情報管理方法、ナビゲーション方法、および、プログラム

    太田 恒平, 小池 敦, 小田中 育生

    Property Type: Patent

  4. 経路探索装置、経路探索システム、サーバ装置、端末装置、経路探索方法、および、プログラム

    太田 恒平, 小池 敦

    Property Type: Patent

  5. 経路探索装置、経路探索システム、サーバ装置、端末装置、経路探索方法、および、プログラム

    太田 恒平, 小池 敦

    特許第5802053号

    Property Type: Patent

  6. 検索システム、ナビゲーションサーバ、検索装置、検索方法、および、プログラム

    小池 敦, 太田 恒平

    Property Type: Patent

  7. 検索システム、ナビゲーションサーバ、検索方法、および、プログラム

    小池 敦, 太田 恒平

    特許第5671350号

    Property Type: Patent

  8. 録音装置、再生装置、録音方法、再生方法、及びコンピュータプログラム

    戸上 真人, ロットウィブンチャイ, グンティダー, 小池 敦, 滝澤 和之, 大淵 康成, 川口 洋平, 松延 豊, 品川 明生

    Property Type: Patent

  9. 音声処理装置、音声処理装置の音声処理方法及びプログラム

    小池 敦, 戸上 真人

    Property Type: Patent

  10. 音声処理装置、音声処理装置の音声処理方法及びプログラム

    小池 敦, 戸上 真人

    特許第5034107号

    Property Type: Patent

  11. 情報処理装置、情報処理装置の音源分離方法及びプログラム

    ロットウィブンチャイ, グンティダー, 小池 敦, 滝澤 和之

    Property Type: Patent

  12. 情報処理装置、情報処理装置の音源分離方法及びプログラム

    ロットウィブンチャイ, グンティダー, 小池 敦, 滝澤 和之

    特許第5070594号

    Property Type: Patent

  13. 音声取得装置、音声出力装置、雑音除去システム、及び、プログラム

    小池 敦, 戸上 真人

    Property Type: Patent

  14. 音声取得装置、雑音除去システム、及び、プログラム

    小池 敦, 戸上 真人

    特許第4431836号

    Property Type: Patent

  15. 携帯端末、参照信号出力回路、及びコンピュータプログラム

    滝澤 和之, 小池 敦, ロットウィブンチャイ, グンティダー

    特許第5023390号

    Property Type: Patent

  16. 携帯端末、参照信号出力回路、及びコンピュータプログラム

    滝澤 和之, 小池 敦, ロットウィブンチャイ, グンティダー

    Property Type: Patent

  17. 情報処理装置、プログラム

    ロットウィブンチャイ, グンティダー, 戸上 真人, 小池 敦, 荒井 郁也

    Property Type: Patent

  18. 情報処理装置、プログラム

    ロットウィブンチャイ, グンティダー, 戸上 真人, 小池 敦, 荒井 郁也

    特許第5029986号

    Property Type: Patent

  19. 番組予約情報取得システムおよびこれに用いる通信装置、サーバ

    ロットウィブンチャイ, グンティダー, 小池敦

    Property Type: Patent

  20. 移動通信端末、移動通信方法、及び、プログラム

    小池 敦

    Property Type: Patent

  21. 移動通信端末、移動通信方法、及び、プログラム

    小池 敦

    特許第4757710号

    Property Type: Patent

  22. 情報提供装置および情報提供方法

    小池 敦, 坂庭 秀紀, 須藤 茂幸

    Property Type: Patent

  23. 画像入力装置、画像出力装置及び画像入出力システム

    舟戸 昭一郎, 坂庭 秀紀, 小池 敦

    Property Type: Patent

  24. 無線通信端末

    坂庭 秀紀, 小池 敦, 木谷 光博

    Property Type: Patent

  25. 無線通信端末

    坂庭 秀紀, 小池 敦, 木谷 光博

    特許第4086200号

    Property Type: Patent

  26. 移動通信端末及び通信制御方法

    小池 敦, 宮田 克也

    Property Type: Patent

  27. 移動通信端末及び通信制御方法

    小池 敦, 宮田 克也

    特許第4465661号

    Property Type: Patent

  28. 移動通信端末、基地局およびレジストレーション制御方法

    小池 敦

    Property Type: Patent

  29. 移動通信端末、基地局およびレジストレーション制御方法

    小池 敦

    特許第4247994号

    Property Type: Patent

  30. 情報処理装置

    小池 敦, 宮田 克也

    Property Type: Patent

  31. 情報処理装置

    小池 敦, 岡野 祐三

    Property Type: Patent

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Research Projects 2

  1. An Inductive Explanatory Model for Artificial Intelligence and Its Application to Human-Cooperative Artificial Intelligence

    Offer Organization: Japan Society for the Promotion of Science

    System: Grants-in-Aid for Scientific Research

    Category: Grant-in-Aid for Scientific Research (C)

    Institution: Tohoku University

    2024/04/01 - 2028/03/31

  2. Theory and Applications of Kinetic Computational Geometry with Uncertanity

    Tokuyama Takeshi

    Offer Organization: Japan Society for the Promotion of Science

    System: Grants-in-Aid for Scientific Research

    Category: Grant-in-Aid for Scientific Research (B)

    2015/04/01 - 2020/03/31

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    In this project, we developed a theory of kinetic and efficient data structure to handle nondeterministic update of continuous data movement. We considered realistic model of kinetic data structure to store the discrete features of geometric trajectories. We considered several solutions of important problems of geometric data processing including geographic data management and ad-hoc network construction. As consequence, we enabled efficient and flexible handling of time-space data analysis. We have done several international joint research with Korea Hong-Kong, US, Holland and Germany, and published 21 research papers in international journals and international refereed conferences, as well as a lot of presentations on those results.

Teaching Experience 22

  1. Machine Learning　Tohoku University

  2. Deep Learning　Tohoku University

  3. AI System Development Workshop Using Jetson and AWS　Tohoku University

  4. Practical Cloud Computing　Tohoku University

  5. Introduction to Cloud Computing　Tohoku University

  6. [X-TECH Business Development Program: Advanced Edition] AI and Data Utilization Projects Accompanied by PBL　Sendai City

  7. 情報工学基礎実習I　一関高専

  8. 応用プログラミング　一関高専

  9. パターン情報処理　八戸工大

  10. 離散数学　一関高専

  11. 情報特論　一関高専

  12. プログラミング演習　一関高専

  13. プログラミング言語　一関高専

  14. ネットワークシステム　一関高専

  15. 情報リテラシー　一関高専

  16. アルゴリズム　一関高専

  17. オペレーティングシステム　一関高専

  18. コンピュータネットワーク　東北工大

  19. プログラミングI　仙台高専

  20. Mathematics for Informatics　Ichinoseki National College of Technology

  21. Graph Theory　Ichinoseki National College of Technology

  22. Application of Informatics Engineering II　National Institute of Technology, Ichinoseki College

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