About Me

Assistant Professor (2022–present), JST PRESTO Researcher (2020–present)

• Department of Physics, Graduate School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033 Japan

• JST, PRESTO, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033 Japan

• [13] JST PRESTO (Grant number JPMJPR23FC) from Japan Science and Technology Agency (JST), 2023–2027.

• [12] Grant-in-Aid for Research Activity Start-up from Japan Society for the Promotion of Science (JSPS), 2023–2025.

• [11] Grant for attending the 4th Japanese-American-German Frontiers of Science Symposium (JAGFOS) from Japan Society for the Promotion of Science (JSPS), 2023.

• [10] Grant-in-Aid for Transformative Research Areas (A) Extreme Universe from Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT), 2021-2025, Research Collaborator.

• [9] JST PRESTO (Grant Number JPMJPR201A) from Japan Science and Technology Agency (JST), 2020–2024, 30000000 JPY for three years and half (about 265000 USD as of November 2021).

• [8] JSPS Overseas Research Fellowships from Japan Society for the Promotion of Science (JSPS), 2020–2022, 12556000 JPY for two years (about 111000 USD as of November 2021).

• [7] Financial support for students attending Quantum Information Processing (QIP), registration fee and accommodation, 2019.

• [6] JSPS Research Fellowships for Young Scientists (DC2, Grant Number 18J10192) from Japan Society for the Promotion of Science (JSPS), 2018–2019, 7800000 JPY for two years (about 69100 USD as of November 2021).

• [5] Overseas Challenge Program for Young Researchers from Japan Society for the Promotion of Science (JSPS), 2017, 1400000 JPY for three months (about 12400 USD as of November 2021).

• [4] Best student poster award in 16th Asian Quantum Information Science Conference (AQIS2016), 2016.

• [3] Scholarship from The Nakabe Scholarship Foundation, 2016–2018.

• [2] Scholarship from Fuji Seal Packaging Education and Scholarship Foundation, 2014–2016.

• [1] Scholarship from Tokio Marine Kagami Memorial Foundation, 2011–2014.

• Doctor of Science in Physics

  • The University of Tokyo, Tokyo, Japan, 25th March 2019,

  • Dissertation: “Entanglement theory in distributed quantum information processing,”

  • Supervisor: Mio Murao.

• Master of Science in Physics

  • The University of Tokyo, Tokyo, Japan, March 2016.

• Bachelor of Science in Physics

  • The University of Tokyo, Tokyo, Japan, March 2014.

• 2022–present Assistant Professor

  • Department of Physics, Graduate School of Science, The University of Tokyo,

  • With Mio Murao.

• 2020–present JST PRESTO Researcher

  • JST, PRESTO.

• 2020–2022 JSPS Overseas Research Fellow

  • Institute for Quantum Optics and Quantum Information (IQOQI) Vienna, Austrian Academy of Sciences,

  • Atominstitut, Technische Universität Wien,

  • With Marcus Huber.

• 2019–2020 Project Researcher

  • Photon Science Center, Graduate School of Engineering, The University of Tokyo,

  • With Masato Koashi.

• 2018–2019 JSPS Research Fellow

  • Department of Physics, Graduate School of Science, The University of Tokyo,

  • Supervised by Mio Murao.

• Lectures

  • [4] “Computational Physics Experiment II,” The University of Tokyo, 2023.

  • [3] “Computational Physics Experiment I,” The University of Tokyo, 2023.

  • [2] “Theoretical Physics Exercise I,” The University of Tokyo, 2023.

  • [1] “Theoretical Physics Exercise II,” The University of Tokyo, 2022.

• Supervision and Cosupervision

  • [9] Yuki Koizumi, “Exploring Low Overhead Fault-Tolerant Quantum Computation,” Theoretical Physics Exercise I for Bachelor's degree, The University of Tokyo, August 2023.

  • [8] Kaito Watanabe, “Review on ‘On a gap in the proof of the generalised quantum Stein’s lemma and its consequences for the reversibility of quantum resources’,” Theoretical Physics Exercise I for Bachelor's degree, The University of Tokyo, August 2023.

  • [7] Yuki Hakamada, “Short Review and Essay for GKP code,” Theoretical Physics Exercise II for Bachelor's degree, The University of Tokyo, February 2023.

  • [6] Takaya Matsuura, Ph.D. Degree, The University of Tokyo, March 2022. The University of Tokyo President's Award for Students was given to Takaya Matsuura.

  • [5] Javier Esteras Maza, Bachelor's degree, University of Vienna, September 2021.

  • [4] Francisca Crislane Vieira de Brito, CAPES PrInt: Program for Institutional Internationalization of the Federal University of ABC (research internship as a part of the program for Ph.D. degree), Austrian Academy of Sciences, September 2021.

  • [3] Karim-Fabian Osman, Master's degree, University of Vienna, June 2021.

  • [2] Kohdai Kuroiwa, Master's degree, University of Waterloo, 2021.

  • [1] Shiro Tamiya, Master's degree, The University of Tokyo, March 2021.

• Teaching Assistant

  • [5] “Exercise in Physics I,” The University of Tokyo, 2017.

  • [4] “Mathematical Method II,” The University of Tokyo, 2017.

  • [3] “Exercise in Physics II,” The University of Tokyo, 2016.

  • [2] “Mathematical Method II,” The University of Tokyo, 2016.

  • [1] “Exercise in Physics II,” The University of Tokyo, 2015.

• [31] “Cost-reduced all-Gaussian universality with the Gottesman-Kitaev-Preskill code: Resource-theoretic approach to cost analysis,” Seminar at QuRMIT, RMIT University, Melbourne, Australia, 8th November 2023.

• [30] “General Quantum Resource Theories: Maximal Resources, Catalytic Replication, and Asymptotically Consistent Measures,” Theory Group seminar, University of Warwick, Coventry, United Kingdom, 29th September 2023.

• [29] “Time-Efficient Constant-Space-Overhead Fault-Tolerant Quantum Computation,” CQIF seminar, University of Cambridge, Cambridge, United Kingdom, 28th September 2023.

• [28] “Quantum Ridgelet Transform: Winning Lottery Ticket of Neural Networks with Quantum Computation,” Regular seminar at Institute for Physics of Intelligence, The University of Tokyo, Tokyo, Japan, 21st July 2023.

• [27] “Quantum Ridgelet Transform: Winning Lottery Ticket of Neural Networks with Quantum Computation,” QIQB, Osaka University, Osaka, Japan, 12th July 2023.

• [26]  “Time-Efficient Constant-Space-Overhead Fault-Tolerant Quantum Computation,” Extreme Universe circular meeting, online, 31st May 2023.

• [25]  “Foundation of fast and widely applicable quantum machine learning,” JUKEN7 LLC, Tokyo, Japan, 13th May 2023.

• [24]  “Foundation of fast and widely applicable quantum machine learning,” Lunch Talk at Department of Physics, Faculty of Science, The University of Tokyo, Tokyo, Japan, 28th April 2023.

• [23]  “Time-Efficient Constant-Space-Overhead Fault-Tolerant Quantum Computation,” Chalmers University of Technology, Gothenburg, Sweden, 13th February 2023.

• [22]  “Constant-Time Testing of Large-Scale Graph States,” Chuo University, Online, 17th January 2023.

• [21]  “Time-Efficient Constant-Space-Overhead Fault-Tolerant Quantum Computation,” NTT R&D, Tokyo, Japan, 13th January 2023.

• [20]  “Time-Efficient Constant-Space-Overhead Fault-Tolerant Quantum Computation,” The University of Tokyo, Tokyo, Japan, 16th December 2022.

• [19]  “Present and Future of Quantum Computer and Quantum Machine Learning,” (量子コンピュータと量子機械学習の今と展望), Ehime University DS research seminar, Ehime University, online, 18th November 2022.

• [18] “Quantum Machine Learning with Optimized Random Features: Applications of Exponential Speedup without Sparsity and Low-Rankness Assumptions,” Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Korea, 26th July 2022.

• [17] “Time-Efficient Constant-Space-Overhead Fault-Tolerant Quantum Computation,” Kyung Hee University, Seoul, Korea, 22nd July 2022.

• [16] “Quantum Machine Learning: Basics of quantum computation and techniques for accelerating machine learning,” University of Seoul, Seoul, Korea, 21th July 2022.

• [15] “Lattice Surgery for Photonic Measurement-Based Quantum Computation,” Xanadu, Online, July 2022.

• [14] “Quantum Machine Learning with Optimized Random Features: Applications of Exponential Speedup without Assumptions on Sparse and Low-Rank Matrices,” IQOQI Vienna, Online, January 2022.

• [13] “Magic state distillation: Toward overhead estimation for GKP MBQC,” Xanadu, Online, September 2021.

• [12] “Learning with Optimized Random Features: Quantum Computation for Accelerating Machine Learning,”  Quantum Machine Learning Seminar, RIKEN AIP, Online, July 2021. Slide (English and Japanese)

• [11] “Recent Progress on Quantum Machine Learning and Fault-Tolerant Photonic Quantum Computation,” NTT, Online, January 2021.

• [10] “Polylog-overhead highly fault-tolerant measurement-based quantum computation: all-Gaussian implementation with Gottesman-Kitaev-Preskill code,” seminar meeting of Quantum Code Design and Architecture (QCDA) project, Online, September 2020.

• [9] “Overview of recent research,” Austrian Academy of Sciences, Vienna, Austria, September 2020. 

• [8] “Fast quantum algorithm for supervised learning by optimized random features,” The University of Tokyo, Tokyo, Japan, November 2019.

• [7] “Fast quantum algorithm for data approximation by optimized random features,” Kyoto University, Tokyo, Japan, October 2019.

• [6] “Distributed Encoding and Decoding of Quantum Information over Networks,” Kyung Hee University, Seoul, Korea, August 2019.

• [5] “Distributed Encoding and Decoding of Quantum Information over Networks,” University of Technology Sydney, Sydney, Australia, June 2019.

• [4] “Quantum-side-information preprocessing and backward classical communication in one-shot quantum state merging,” University of Technology Sydney, Sydney, Australia, December 2018.

• [3] “Multipartite entanglement outperforms bipartite entanglement under limited quantum system sizes,” University of Vienna, Vienna, Austria, June 2018.

• [2] “Entanglement cost of concentrating/spreading quantum information over networks through exact quantum state merging/splitting,” The University of Tokyo, Tokyo, Japan, February 2018.

• [1] “Graph-associated entanglement cost of multipartite states and multiparty distributed quantum coding,” University of Innsbruck, Innsbruck, Austria, September 2017.

• [2] Organizer of International workshop on quantum information processing and quantum machine learning (QIP-QML 2022) https://sites.google.com/view/qip-qml2022/home, 2022.

• [1] Organizer of Qulink seminars https://qis1.ex.nii.ac.jp/qulink/, 2017–2018.

• [2] "Basic Physics," A series of video seminars for high school students, in collaboration with Kunihiko Kasahara, Ayaka Oyanagi, and Makio, JUKEN7, online, September 2021-present. 

• [1] “Entanglement theory in distributed quantum information processing,” The Nakabe Scholarship Foundation, Tokyo, Japan, July 2019.