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Last Updated :2026/09/13

Rio Tomioka

Faculty of Engineering
Assistant Lecturer/Assistant professor

Researcher information

■ Degree
  • Ph.D. in Information Engineering, Kyushu Institute of Technology, Mar. 2026
■ Research Keyword
  • Information Photonics
  • Optical Information Processing
  • Optoelectronics
  • Optical neural network
  • Optical computing
  • Holography

Career

■ Career
  • Apr. 2026 - Present
    Fukuoka University, Faculty of Engineering Department of Electronics Engineering and Computer Science, Assistant Professor
  • Apr. 2024 - Mar. 2026
    Kyushu Institute of Technology, Kyushu Institute Technology SPRING Scholarship Awarde
  • Apr. 2025 - Sep. 2025
    The University of Kitakyushu, Faculty of Economics and Business Administration Dept.of Business Administration, Part-time Teacher
  • Apr. 2023 - Mar. 2024
    Kyushu Institute of Technology, Kyutech Research Fellow
■ Educational Background
  • Apr. 2023 - Mar. 2026
    Kyushu Institute of Technology, Graduate School of Computer Science and Systems Engineering, Department of Creation Informatics
  • Apr. 2021 - Mar. 2023
    Kyushu Institute of Technology, Graduate School of Computer Science and Systems Engineering, Department of Advanced Informatics
  • Apr. 2017 - Mar. 2021
    Kyushu Institute of Technology, School of Computer Science and Systems Engineering, Department of Systems Design and Informatics

Research activity information

■ Award
  • Dec. 2022
    映像情報メディア学会, 優秀研究発表賞
    自己参照型ホログラフィックニューラルネットワークにおける透過行列を用いた学習過程の改善, Japan society
    冨岡莉生
■ Paper
  • Numerical simulations on self-referential holographic data storage with built-in denoising function by self-referential holographic deep neural network
    Yuta Eto; Rio Tomioka; Taichi Takatsu; Masanori Takabayashi
    Optical Review, 21 Jun. 2025, 32:534 - 545, Refereed
  • Numerical simulations on optoelectronic deep neural network hardware based on self-referential holography
    Rio Tomioka; Masanori Takabayashi
    Optical Review, 28 Apr. 2023, 30:387 - 396, Refereed
    Corresponding
  • Fundamental Studies of Optoelectronic Deep Neural Network Using Cluster-wise Simultaneous Perturbation Stochastic Approximation Algorithms
    Takumi Hashiguchi; Rio Tomioka; Taichi Takatsu; Masanori Takabayashi
    Program and Abstracts, the 8th International Symposium on Neuromorphic AI Hardware, 06 Mar. 2026, :92 - 92, Refereed
  • Numerical Study of Interface Design for Spatial Light Modulation-Based Deep Neural Networks Using Hyperparameter Optimization
    Rio Tomioka; Masanori Takabayashi
    Program and Abstracts, the 8th International Symposium on Neuromorphic AI Hardware, 06 Mar. 2026, :93 - 93, Refereed
    Lead
  • 空間光変調に基づく光電融合深層ニューラルネットワークハードウェアに関する研究
    冨岡 莉生
    九州工業大学博士学位論文, Mar. 2026
  • Numerical Simulations of Parallel Image Recognition with Self-Referential Holographic Deep Neural Network
    Shoichi Sakai; Rio Tomioka; Yuta Eto; Masanori Takabayashi
    IWH2025, 12 Nov. 2025, Refereed
  • Numerical simulations on denoising capability of self-referential holographic data storage with built-in denoising function
    Yuta Eto; Rio Tomioka; Masanori Takabayashi
    IWH2025, 12 Nov. 2025, Refereed
  • Numerical Simulation of Autonomous Mask Design for Optoelectronic Deep Neural Network by Hyperparameter Optimization
    Rio Tomioka; Masanori Takabayashi
    IWH2025, 12 Nov. 2025, Refereed
    Lead
  • Numerical Simulations of Optoelectronic Neural Network Using Off-Axis Binary Holograms on Digital Micromirror Device
    Yusaku Matsumoto; Rio Tomioka; Masanori Takabayashi
    ISOM2025, 19 Oct. 2025, Refereed
  • Numerical Simulation of Output Filter Design for Optoelectronic Deep Neural Network Using Hyperparameter Optimization
    Rio Tomioka; Taichi Takatsu; Masanori Takabayashi
    the 6th International Symposium on Neuromorphic AI Hardware, 03 Mar. 2025, (P1-21):39 - 39, Refereed
    Lead
  • Numerical simulation of deep reinforcement learning using self- referential holographic deep neural network
    Rio Tomioka; Masanori Takabayashi
    IWH2024, 10 Dec. 2024, (S5-2), Refereed
    Lead
  • Self-referential holographic data storage with integrated denoising function by deep learning
    Yuta Eto; Rio Tomioka; Taichi Takatsu; Masanori Takabayashi
    ISOM2024, 20 Oct. 2024, (Mo-D-01), Refereed
  • Numerical Simulations of Optoelectronic Deep Neural Network Using Trainable Activation Function
    Taichi Takatsu; Rio Tomioka; Masanori Takabayashi
    ISOM2024, 20 Oct. 2024, (Tu-E-44), Refereed
  • Numerical simulations on image recognition by self-referential holographic deep neural network with electronic output layer
    Rio Tomioka; Taichi Takatsu; Masanori Takabayashi
    ODF2024, 10 Jul. 2024, (ThP-39), Refereed
    Lead
  • Numerical analysis on contributions of individual layers in self-referential holographic deep neural network
    Taichi Takatsu; Rio Tomioka; Masanori Takabayashi
    ODF2024, 10 Jul. 2024, (ThP-40), Refereed
  • Numerical simulation on wavefront transformation using self-referential holographic deep neural network
    Rio Tomioka; Taichi Takatsu; Masanori Takabayashi
    the 5th International Symposium on Neuromorphic AI Hardware, 01 Mar. 2024, (O3-04/P1-22):14 - 14, Refereed
    Lead
  • Effective training method using transmission matrix for optoelectronic deep neural network
    Taichi Takatsu; Rio Tomioka; Masanori Takabayashi
    the 5th International Symposium on Neuromorphic AI Hardware, 01 Mar. 2024, (P1-12):25 - 25, Refereed
  • Self-referential holographic neural network with single spatial light modulator
    Rio Tomioka; Masanori Takabayashi
    the 4th International Symposium on Neuromorphic AI Hardware, 13 Dec. 2022, (P2-2):35 - 35, Refereed
    Lead
  • Numerical Simulations of Optoelectronic AI Hardware using Transmission Matrix of Real Object
    Masanori Takabayashi; Rio Tomioka; Kaito Inoue; Atsushi Shibukawa
    the 4th International Symposium on Neuromorphic AI Hardware, 13 Dec. 2022, (S-4):7 - 7, Refereed
  • Dependence of activation function on image recognition accuracy in self-referential holographic deep neural network
    Rio Tomioka; Masanori Takabayashi
    ISOM2022, 31 Jul. 2022, (ITuPJ_01), Refereed
    Lead
  • Self-referential holographic neural network with electronically implemented nonlinear layer
    Rio Tomioka; Masanori Takabayashi
    the 3rd International Symposium on Neuromorphic AI Hardware, 18 Mar. 2022, (P-AM8):17 - 17, Refereed
    Lead
  • Hyperparameter tuning for accurate image classification using self-referential holographic neural network
    Masanori Takabayashi; Sae Isayama; Rio Tomioka
    IWH2021, 11 Mar. 2022, (11-P08), Refereed
  • Numerical simulations of neural network hardware based on self-referential holography
    Rio Tomioka; Masanori Takabayashi
    ISOM21, 03 Oct. 2021, (We-A-02):123 - 124, Refereed
    Lead
■ MISC
  • 自己参照型ホログラフィの原理を用いた光電子深層ニューラルネットワークハードウェア
    Masanori Takabayashi; Rio Tomioka
    Photonics NEWS, 10 Mar. 2024, 9(3):147 - 151, Refereed
  • 自己参照型ホログラフィックニューラルネットワークにおける透過行列を用いた学習過程の改善
    Rio Tomioka; Masanori Takabayashi
    ITE technical report, 21 Feb. 2022, 46(6):61 - 66
    Lead
  • 自己参照型ホログラフィック深層ニューラルネットワークを用いた並列画像デノイジングに関する数値シミュレーション
    Shoichi Sakai; Yuta Eto; Rio Tomioka; Masanori Takabayashi
    映情学技報, 18 Feb. 2026, 50(5):17 - 20
  • 深層学習によるデノイズ機能を内在した自己参照型ホログラフィックメモリのための効率的な学習手法の検討
    Yuta Eto; Rio Tomioka; Masanori Takabayashi
    第86回応用物理学会秋季学術講演会, 07 Sep. 2025, :8p-N205-01
  • 散乱媒質を挿入した光電子融合型深層ニューラルネットワークを用いた画像識別実験
    Kaito Inoue; Takumi Hashiguchi; Taichi Takatsu; Rio Tomioka; Atsushi Shibukawa; Masanori Takabayashi
    映情報学技報, 19 Feb. 2025, 49(4):161 - 166
  • 深層学習に基づく再生データページのデノイズ機能を内在する 自己参照型ホログラフィックメモリ ～ 学習用データセットの生成法に関する検討 ～
    Yuta Eto; Rio Tomioka; Taichi Takatsu; Masanori Takabayashi
    映情報学技報, 05 Dec. 2024, 48(41):1 - 6
  • Numerical simulation on phase-to-intensity conversion by self-referential holographic deep neural network
    Rio Tomioka; Masanori Takabayashi
    The 13th Japan-Korea Workshop on Digital Holography and Information Photonics, 18 Dec. 2023, :54 - 54
    Lead
  • 訪問地事前体験のための仮想空間アプリケーションの開発及び実証実験
    山崎駆; 山口健太; 冨岡莉生; 梶谷柊; 高津太一; 根崎翔; 井上快斗; 岸田隆之; 井上創造; 柴田智広
    第7回福祉工学会九州支部大会, 10 Dec. 2022, (P1-3):30 - 31
  • 仮想空間アプリケーションを利用した訪問地の事前体験と高齢化社会への適用
    山崎駆; 山口健太; 冨岡莉生; 梶谷柊; 高津太一; 根崎翔; 井上快斗; 岸田隆之; 井上創造; 柴田智広
    第25回ASD研究会, 02 Dec. 2022, (2022-ASD-25-6)
■ Lectures, oral presentations, etc.
  • 自己参照型ホログラフィック深層ニューラルネットワークによる並列画像識別
    坂井翔一; 冨岡莉生; 江藤優太; 髙林正典
    光の極限性能を生かすフォトニックコンピューティング 第7回領域会議, 15 Dec. 2025
  • 自己参照型ホログラフィック深層ニューラルネットワークを用いた画像デノイズに関する数値シミュレーション
    江藤優太; 冨岡莉生; 髙林正典
    光の極限性能を生かすフォトニックコンピューティング 第6回領域会議, 04 Aug. 2025
  • 空間光変調に基づく複素深層ニューラルネットワーク
    冨岡莉生; 高津太一; 高林正典
    「光の極限性能を生かすフォトニックコンピューティングの創成」第2回公開シンポジウム, 17 Dec. 2024
  • 学習可能な電子演算部を有する光電融合深層ニューラルネットワークに関するシミュレーション
    Rio Tomioka; Taichi Takatsu; Masanori Takabayashi
    光の極限性能を生かすフォトニックコンピューティング 第4回領域会議, 05 Aug. 2024
  • Numerical simulations of efficient training method on optoelectronic deep neural network using transmission matrix
    Taichi Takatsu; Rio Tomioka; Masanori Takabayashi
    Materials Meet Robots 2024, 07 May 2024
  • Numerical simulations on complex-valued optoelectronic deep neural network
    Rio Tomioka; Taichi Takatsu; Kaito Inoue; Atsushi Shibukawa; Masanori Takabayashi
    The First International Symposium on Photonic Computing, 11 Mar. 2024
  • 複素振幅分布を入出力とする光電子融合型深層ニューラルネットワークハードウェアにおける複素活性化関数の影響
    冨岡莉生; 高林正典
    光の極限性能を生かすフォトニックコンピューティング 第3回領域会議, 07 Aug. 2023
  • 自己参照型ホログラフィックメモリの光学系を用いたニューラルネットワークハードウェア
    冨岡莉生; 高林正典
    情報フォトニクス研究討論会2023, 21 Jul. 2023
  • 自己参照型ホログラフィの原理に基づく光電子融合型ニューラルネットワークハードウェア
    冨岡莉生
    第２回光ニューロワークショップ, 13 Mar. 2023
■ Courses
  • Computer system
    Apr. 2025 - Sep. 2025
    The University of Kitakyushu
■ Affiliated academic society
  • May 2023 - Present
    The Optical Society of Japan
  • Nov. 2022 - Present
    The Institute of Image Information and Television Engineers