Faculty of International Social Sciences

Takashi Nicholas MAEDA

(前田高志ニコラス)

Profile Information

Affiliation: Associate Professor, Computer Centre, Gakushuin University

Degree: 博士（工学）(東京大学)

J-GLOBAL ID: 201901001726169782
researchmap Member ID: B000354059

Research Areas

1

Informatics / Intelligent informatics /

Research History

5

Sep, 2024 - Present

Specially Appointed Associate Professor, Data Science and AI Innovation Research Promotion Center, Shiga University
Apr, 2024 - Present

Associate professor, Computer Centre, Gakushuin University
Apr, 2022 - Present

Visiting scientist, RIKEN
Apr, 2022 - Mar, 2024

Associate professor, School of System Design and Technology, Tokyo Denki University
Apr, 2019 - Mar, 2022

Postdoctoral researcher, Center for Advanced Intelligence Project, RIKEN

Education

3

Apr, 2016 - Mar, 2019

Department of System Innovation, The Graduate School of Engineering, The University of Tokyo
Apr, 2014 - Mar, 2016

Department of System Innovation, The Graduate School of Engineering, The University of Tokyo
Faculty of Letters, Faculty of Letters, Kyoto University

Papers

9

Use of Prior Knowledge to Discover Causal Additive Models with Unobserved Variables and its Application to Time Series Data.

Takashi Nicholas Maeda, Shohei Shimizu

CoRR, abs/2401.07231, 2024
Python package for causal discovery based on LiNGAM

Takashi Ikeuchi, Mayumi Ide, Yan Zeng, Takashi Nicholas Maeda, and Shohei Shimizu

Journal of Machine Learning Research, 24(14), Jan, 2023 Peer-reviewed
The economic value of urban landscapes in a suburban city of Tokyo, Japan: A semantic segmentation approach using Google Street View images

Masatomo Suzuki, Junichiro Mori, Takashi Nicholas Maeda, Jun Ikeda

Journal of Asian Architecture and Building Engineering, 22(3) 1110-1125, Jul 14, 2022 Peer-reviewed
I-RCD: An improved algorithm of repetitive causal discovery from data with latent confounders

Takashi Nicholas MAEDA

Behaviormetrika, Jun 4, 2022 Peer-reviewedInvitedLead authorLast authorCorresponding author
Repetitive causal discovery of linear non-Gaussian acyclic models in the presence of latent confounders

Takashi Nicholas MAEDA, Shohei SHIMIZU

International Journal of Data Science and Analytics, 13(2) 77-89, Sep 7, 2021 Peer-reviewedLead author

Misc.

2

大学別の博士課程進学等に関するデータセットの構築と統計的因果探索

高山, 正行, 小松, 尚登, ファム, テトン, 前田, 高志ニコラス, 三内, 顕義, 小柴, 等, 清水, 昌平

年次学術大会講演要旨集, 38 874-879, Oct 28, 2023

一般講演要旨 identifier:https://dspace.jaist.ac.jp/dspace/handle/10119/19271
博士課程進学率に関する因果モデルの構築

高山正行, 小柴等, 前田高志ニコラス, 三内顕義, 清水昌平, 星野利彦

Jxiv, Mar, 2022

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