N. H. Shimada
(NHShimada93 -at- google.com)

Google Citations
Qiita (Japanese)


2012/03 - 2017/03
The University of Tokyo, Japan
BE (Materials Science) @Watanabe・Minamitani Lab.
2018/04 - 2020/04
The University of Tokyo, Japan
MS (Information of Science and Technology) @Hachisuka Lab.
2020/09 - present
University of Waterloo, Canada
PhD (Computer Science) @Hachisuka Lab.


Aidemy Inc. Machine learning engineer
 - Making teaching materials for deep reinforcement learning
 - Making teaching materials for blockchain
MDR Inc. Quantum computation engineer
 - Research and Development for VQE method
Preferred Networks Inc. Researcher for machine learning
 - Differentiable renderer


The Young Student Award of "日本金属学会・日本鉄鋼協会"
(= Excellent academic award of my department)


pic ・Quantum Coin Method for Numerical Integration
 We improve and implement the quantum algorithm for Monte Carlo integration (QCoin). We make sure on a simulator that the error rate of QCoin is better than the limitation of classical Monte Calro and comparable to the previous quantum algorithm (QSS). Moreover, we suggest that QCoin is a quantum-classical hybrid algorithm and fundamentally robust under the noise in actual quantum computers. We conduct numerical experiments on a quantum computer to confirm the robustness.
N. H. Shimada and T. Hachisuka, TBA -, - (2019) (arXiv)

pic ・First principle calculation for BCS-type superconductivity of hBN-Li-hBN
 A superconducting transition temperature (Tc) up to 25 K in the Li-intercalated bilayer of hexagonal boron nitride (h-BN) is predicted according to ab-initio calculations. A Tc higher than that of metal-intercalated graphene is ascribed to the characteristic spatial distribution of electronic states near the Fermi level, which is distinctly different from graphene's. Our results provide a new design guideline for two-dimensional superconductors based on intercalated layered materials.
N. H. Shimada, E. Minamitani, and S. Watanabe, Appl. Phys. Express 10, 093101 (2017)