Updated on 2026/06/08

写真a

 
SHAO, Tengfei
 
Affiliation
Affiliated organization, Global Education Center
Job title
Assistant Professor(non-tenure-track)
Degree
博士（工学） ( 早稲田大学 )
Mail Address
メールアドレス
Homepage URL
https://www.tengfeishao.com/

Research Experience

  • 2025.04
    -
    Now

    Waseda University

  • 2025.04
    -
    Now

    早稲田大学   データサイエンス研究所   研究員

  • 2025.04
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    Now

    Kanagawa University

  • 2025.04
    -
    Now

    早稲田大学   GEC   講師

Education Background

  • 2022.04
    -
    2025.03

    早稲田大学   創造理工学研究科   経営システム専攻,博士  

  • 2020.04
    -
    2022.03

    Waseda University  

Committee Memberships

  • 2026.02
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    Now

    Elsevier, Finance Research Letters, 編集委員

  • 2025.06
    -
    Now

    International Conference on Artificial Intelligence and Future Education, カンファレンスチェア

  • 2024.03
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    Now

    SICE 社会システム部会  運営委員

Professional Memberships

  • 2025.04
    -
    Now

    日本経営工学会

  • 2024
    -
    Now

    Association for Computing Machinery（ACM）

  • 2024
    -
    Now

    Institute of Electrical and Electronics Engineers（IEEE）

  • 2022
    -
    Now

    計測自動制御学会 (SICE)

  • 2022
    -
    Now

    人工知能学会 (JSAI)

  • 2022
    -
    Now

    電子情報通信学会（IEICE）

  • 2020
    -
    Now

    情報処理学会 (IPSJ)

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Research Areas

  • Intelligent informatics / Statistical science   データサイエンス / Social systems engineering

Research Interests

  • 人工知能

  • 経営システム工学

  • データサイエンス

  • AIエージェント

  • 複雑システム

  • ネットワーク分析

  • マネージメントシステム

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Awards

  • Best Presentation Award, ACMSA 2025, "Integrating Structural and Semantic Signals: Multi-Cluster Analysis of Local Community Markets via Network Motifs", The 2025 Asian Conference of Management Science and Applications(ACMSA 2025)

    2025.12  

    Winner： Tengfei Shao, Xu Wang, Hideo Kanemitsu, Masayuki Goto

  • Excellent Paper Award, APIEMS2025, "Identifying Seasonal Quality Factors by Analyzing Topic Changes in Customer Reviews with BERTopic and Logistic Models", 25th Asia Pacific Industrial Engineering & Management System Conference (APIEMS 2025)

    2025.11  

  • Excellent Paper Award, APIEMS2025, "A RFM-R Review Analysis Model for Understanding Core Reviewers Using LDA and Logistic Regression", 25th Asia Pacific Industrial Engineering & Management System Conference (APIEMS 2025)

    2025.11  

  • Excellent Paper Award, APIEMS2025, "A Multilingual Text Analysis Model for Understanding Game Recommendation Behavior Using Topic-based Sentiment and Logistic Regression", 25th Asia Pacific Industrial Engineering & Management System Conference (APIEMS 2025)

    2025.11   Excellent Paper Award, APIEMS2025, "A Multilingual Text Analysis Model for Understanding Game Recommendation Behavior Using Topic-based Sentiment and Logistic Regression", 25th Asia Pacific Industrial Engineering & Management System Conference (APIEMS 2025)  

  • Best Paper Award, DSInS 2024, "FA-YOLO: Adaptive Feature Fusion and Multi-Scale Dilated Attention for Collision Detection", 2024 4th International Conference on Digital Society and Intelligent Systems, IEEE Xplore(DSInS 2024)

    2024.11  

    Winner： Haoran Luo, Tengfei Shao, Shenglei Li, Tomoji Kishi

  • Best Presentation Award, DSInS 2024, "Revealing Tourist Behavior Dynamics through Network Science and Satisfaction Metrics", 2024 4th International Conference on Digital Society and Intelligent Systems, IEEE Xplore(DSInS 2024)

    2024.11  

    Winner： Shao Tengfei, Yuya Ieiri, Haoran Luo, Shenglei Li, Masayuki Goto, Shingo Takahashi

  • Best Presentation Award, CAIBDA2024, "A Study of AI Ethics Education, International Conference on Artificial Intelligence, Big Data and Algorithms in the Context of Japanese Job-Hunting Based on Case Method Using Network Analysis", International Conference on Artificial Intelligence, Big Data and Algorithms, ACM DIGITAL LI-BRARY (CAIBDA2024)

    2024.07  

    Winner： Tengfei Shao, Tianxiang Yang, Haoran Luo, Masayuki Goto, Shingo Takahashi

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Papers

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Presentations

  • LLM型OSSを対象とした生存時間の予測と影響要因の分析

    王 茜, 邵 騰飛, 岸 知二

    情報処理学会 第88回全国大会 

    Presentation date： 2026.03

  • 商品情報を考慮したAutoTimes予測モデルの拡張に関する一考察

    伊澤 碧大, 邵 騰飛, 楊 添翔, 後藤 正幸

    日本経営工学会 2025年秋季大会 

    Presentation date： 2025.10

  • 顧客レビューを用いた電子製品の評価要因分析モデルに関する一考察

    呂 文博, 阪井 優太, 邵 騰飛, 後藤 正幸

    第24回情報科学技術フォーラム FIT2025 

    Presentation date： 2025.09

  • 顧客レビューによる購入目的別の品質要素比較分析モデル

    トウ シセン, 山極 綾子, 邵 騰飛, 後藤 正幸

    第24回情報科学技術フォーラム FIT2025 

    Presentation date： 2025.09

  • スポーツチームの試合結果・パフォーマンスとSNS世論構造の関連分析モデル

    李 芸海, 楊 添翔, 邵 騰飛, 後藤 正幸

    第24回情報科学技術フォーラム FIT2025 

    Presentation date： 2025.09

  • Webフレームワーク型OSSを対象にした生存時間の予測と影響要因の分析

    王 茜, 邵 腾飛, 岸 知二

    Presentation date： 2025.09

  • Webフレームワーク型OSSを対象にした生存時間の影響要因の分析

    王 茜, 邵 腾飛, 岸 知二

    Presentation date： 2025.08

  • 順序尺度を持つユーザ属性に対するレビューデータからの予測モデルの構築

    袁 キン, 楊 添翔, 邵 騰飛, 後藤正幸

    第39回人工知能学会全国大会(JSAI2025) 

    Presentation date： 2025.05

  • 顧客レビューのリピート投稿要因分析のためのテキスト分析モデル

    王 嘉翊, 邵 騰飛, 楊 添翔, 山下 遥, 後藤正幸

    第39回人工知能学会全国大会(JSAI2025) 

    Presentation date： 2025.05

  • トピックモデルと大規模言語モデルを基づくオープンワールドゲームにおけるプレイヤーの嗜好比較分析

    孫 思鋭, 楊 添翔, 邵 騰飛, 後藤正幸

    第39回人工知能学会全国大会(JSAI2025) 

    Presentation date： 2025.05

  • 就職活動におけるAI倫理問題に着目した教育手法の構築と検証のフレームワーク―ネットワークモチーフ分析を通した考察

    邵 騰飛, 楊 添翔, 後藤正幸, 高橋真吾

    第39回人工知能学会全国大会(JSAI2025) 

    Presentation date： 2025.05

  • 拡張現実技術による投扇興伝統文化体験の分析

    溝渕 健太, 蔡 弘亞, 邵 騰飛, 家入 祐也, 菱山 玲子

    Presentation date： 2022.03

  • Discovering Multiple Clusters of Second-Hand Luxury Goods to Improve the Profit of Supplier Based on Network Motif

    Tengfei Shao, Fumitoshi Teraoka, Keiji Ishizaki, Reiko Hishiyama

    2022年度情報処理学会全国大会(第84回，IPSJ2022) 

    Presentation date： 2022.03

  • An Analysis of Second-Hand Luxury Goods Sales Data Using Network Motifs

    Tengfei Shao, Reiko Hishiyama

    The 36th Annual Conference of the Japanese Society for Artificial Intelligence 2022 (JSAI2022) 

    Presentation date： 2022.03

  • Discovering Multiple Clusters of Sightseeing Spots for Improving Tourist Satisfaction Using Network Motif

    Tengfei Shao, Yuya Ieiri, Reiko Hishiyama

    2021年度情報処理学会全国大会(第 83 回，IPSJ2021) 

    Presentation date： 2021.03

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Misc

  • A Multilingual Text Analysis Model for Understanding Game Recommendation Behavior Using Topic-based Sentiment and Logistic Regression

    Sirui Sun, Tianxiang Yang, Tengfei Shao, Masayuki Goto

    The 25th Asia-Pacific Industrial Engineering and Management System Conference (APIEMS 2025), Hangzhou, China, 5246    2025.11  [Refereed]

    Research paper, summary (international conference)  

  • Identifying Seasonal Quality Factors by Analyzing Topic Changes in Customer Reviews with BERTopic and Logistic Models

    Zixuan Tong, Ayako Yamagiwa, Tengfei Shao, Masayuki Goto

    The 25th Asia-Pacific Industrial Engineering and Management System Conference (APIEMS 2025), Hangzhou, China, 5306    2025.11  [Refereed]

    Research paper, summary (international conference)  

  • A RFM-R Review Analysis Model for Understanding Core Reviewers Using LDA and Logistic Regression

    Jiayi Wang, Tengfei Shao, Tianxiang Yang, Masayuki Goto

    The 25th Asia-Pacific Industrial Engineering and Management System Conference (APIEMS 2025), Hangzhou, China, 5345    2025.11  [Refereed]

    Research paper, summary (international conference)  

  • Analysis of Rating-Sentiment Inconsistent Reviews via Sentiment Trajectory Clustering

    Wenbo Lyu, Yuta Sakai, Tengfei Sha, Masayuki Goto

    The 25th Asia-Pacific Industrial Engineering and Management System Conference (APIEMS 2025), Hangzhou, China, 5409    2025.11  [Refereed]

    Research paper, summary (international conference)  

  • An Analysis of Player Performance and Public Opinion: Linking On-Court Actions to Social Media Reactions in Volleyball

    Yihai Li, Tianxiang Yang, Tengfei Shao, Masayuki Goto

    The 25th Asia-Pacific Industrial Engineering and Management System Conference (APIEMS 2025), Hangzhou, China, 5412    2025.11  [Refereed]

  • An Interpretive Framework for Ordinal Attribute Modeling using Topic Embeddings and Ordered Regression

    Xin Yuan, Tianxiang Yang, Tengfei Shao, Masayuki Goto

    The 25th Asia-Pacific Industrial Engineering and Management System Conference (APIEMS 2025), Hangzhou, China, 5442    2025.11  [Refereed]

    Research paper, summary (international conference)  

  • Temporal Evolution of Retail Networks: A Hypergraph-Based Approach to Consumer-Store-Salesperson Interactions

    Tengfei Shao, Shenglei Li, Xu Wang, Hidehiro Kanemitsu, Masayuki Goto

    The 52nd International Conference on Computers and Industrial Engineering (CIE52), INSA Lyon, France (CIE2025-132)    2025.10  [Refereed]

    Authorship：Lead author

    Research paper, summary (international conference)  

  • Webフレームワーク型OSSを対象にした生存時間の予測と影響要因の分析

    王 茜, 邵 腾飛, 岸 知二

    情報科学技術フォーラム講演論文集   24th  2025.09  [Refereed]

    Research paper, summary (national, other academic conference)  

    J-GLOBAL

  • A consumer behavior analytics model for commercial district marketing using network-structured stamp rally data

    Yuya Ieiri, Shao Tengfei, Osamu Yoshie

    Decision Analytics Journal   15   100567  2025.06

    DOI

  • Dissecting the Second-hand Luxury Market Dynamics: Insights from E-commerce versus Brick-and-Mortar

    Tengfei Shao, Yuya Ieiri, Shingo Takahashi

      66 ( 3 )  2025.03

  • Dynamic Analysis of the Second-hand Luxury Goods Market in an E-commerce Context: A Network Motif and Time-series Perspective

      66 ( 1 )  2025.01

  • A Study of AI Ethics Education in the Context of Japanese Job-Hunting Based on Case Method Using Network Motif

    SHAO Tengfei, YANG Tianxiang, 後藤正幸, 高橋真吾

    人工知能学会全国大会論文集(Web)   39th   3I5GS1101 - 3I5GS1101  2025

    　View Summary

    As the influence of AI continues to expand across diverse sectors, the need for a practical ethical framework to prevent biases and guide responsible applications becomes increasingly paramount. This study proposes an innovative educational approach that combines the Case Method with network analysis to examine ethical challenges in AI. To evaluate the framework’s capacity for analyzing response patterns and enhancing ethical decision-making, we conduct a comprehensive case study focusing on the use of AI in Japanese job-hunting practices. Analyzing participant responses before and after targeted educational interventions reveals notable improvements in ethical reasoning and awareness, thereby underscoring the framework’s effectiveness in fostering critical ethical engagement.

    DOI J-GLOBAL

  • A Text Analysis Model for Exploring Factors Influencing Repeat of Customer Review Posting

    WANG Jiayi, SHAO Tengfei, YANG Tianxiang, 山下遥, 後藤正幸

    人工知能学会全国大会論文集(Web)   39th   4S1GS202 - 4S1GS202  2025

    DOI J-GLOBAL

  • Comparative analysis of player preferences in open-world game based on topic modeling and large language model

    SUN Sirui, YANG Tianxiang, SHAO Tengfei, 後藤正幸

    人工知能学会全国大会論文集(Web)   39th   3S6GS205 - 3S6GS205  2025

    DOI J-GLOBAL

  • Construction of a Prediction Model from Review Data for User Attributes with Ordinal Scale

    YUAN Xin, YANG Tianxiang, SHAO Tengfei, 後藤正幸

    人工知能学会全国大会論文集(Web)   39th   4S1GS204 - 4S1GS204  2025

    DOI J-GLOBAL

  • An Analysis of Evaluation Factors for Electronic Products Based on Customer Reviews

    LYU Wenbo, 阪井優太, SHAO Tengfei, 後藤正幸

    情報科学技術フォーラム講演論文集   24th  2025

    J-GLOBAL

  • A Model for Analyzing the Relationship Between Team Game Results, Performance and the Structure of Public Opinion on Social Media

    LI Yihai, YANG Tianxiang, SHAO Tengfei, 後藤正幸

    情報科学技術フォーラム講演論文集   24th  2025

    J-GLOBAL

  • Comparative analysis model of quality factors by purpose of purchase based on customer reviews

    トウ シセン, 山極綾子, SHAO Tengfei, 後藤正幸

    情報科学技術フォーラム講演論文集   24th  2025

    J-GLOBAL

  • Multiple Clusters Discovery Utilizing Network Motifs for Community Improvement: Insights from Tourism and Goods' Transactions

      65 ( 3 )  2024.03

  • FSAMT: Face Shape Adaptive Makeup Transfer

    LUO Haoran, SHAO Tengfei, LI Shenglei, HISHIYAMA Reiko

    IEICE Transactions on Information and Systems (Web)   E107.D ( 8 ) 1059 - 1069  2024

    　View Summary

    Makeup transfer is the process of applying the makeup style from one picture (reference) to another (source), allowing for the modification of characters' makeup styles. To meet the diverse makeup needs of individuals or samples, the makeup transfer framework should accurately handle various makeup degrees, ranging from subtle to bold, and exhibit intelligence in adapting to the source makeup. This paper introduces a “3-level” adaptive makeup transfer framework, addressing facial makeup through two sub-tasks: 1. Makeup adaptation, utilizing feature descriptors and eyelid curve algorithms to classify 135 organ-level face shapes; 2. Makeup transfer, achieved by learning the reference picture from three branches (color, highlight, pattern) and applying it to the source picture. The proposed framework, termed “Face Shape Adaptive Makeup Transfer” (FSAMT), demonstrates superior results in makeup transfer output quality, as confirmed by experimental results.

    DOI J-GLOBAL

  • 拡張現実技術を用いた投扇興アプリによる伝統文化体験分析

    溝渕, 健太, 蔡, 弘亞, 邵, 騰飛, 家入, 祐也, 菱山, 玲子

    第84回全国大会講演論文集   2022 ( 1 ) 205 - 206  2022.02

    　View Summary

    本稿では，ユーザにとって拡張現実技術（AR）による伝統文化体験が，実際の伝統文化体験への動機づけに対してどのように影響するのか解明する．この目的を達成するために，日本の伝統文化のひとつである「投扇興」を体験できるアプリケーションを開発し，47名の被験者に対し，母国を異にする2つの被験者グループを作成し，3つのプレイ環境で統制実験を行った．その結果，被験者グループにより動機づけの度合いが異なることが分かった．更に，日本人の被験者グループにとっては，プレイ環境の設定が動機づけに影響することが分かった．

  • Discovering Multiple Clusters of Second-Hand Luxury Goods to Improve the Profit of Supplier Based on Network Motif

      2022 ( 1 ) 691 - 692  2022.02

  • Discovering Multiple Clusters of Sightseeing Spots for Improving Tourist Satisfaction Using Network Motif

      2021 ( 1 ) 621 - 622  2021.03

    CiNii

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Syllabus

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Teaching Experience

  • 経営工学実験実習Ⅰ（神奈川大学）

    2025.04
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    Now
     

  • AIプログラミング基礎（早稲田大学）

    2025.04
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  • データベース（管理と運用）（早稲田大学）

    2025.04
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  • データベース（SQL入門）（早稲田大学）

    2025.04
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  • プログラミング初級（Java）（早稲田大学）

    2025.04
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  • プログラミング初級（C/C++）（早稲田大学）

    2025.04
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  • Introduction to Programming（早稲田大学）

    2025.04
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  • プログラミング入門（早稲田大学）

    2025.04
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  • 情報科学の基礎（早稲田大学）

    2025.04
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    Now
     

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Social Activities

  • Volunteer

    Social Capital Markets Conference 2020 (SOCAP20) 

    2020.10
    　
    　

Academic Activities

  • Elsevier, Finance Research Letters誌

    Peer review

    2025.10
    -
    Now

  • 日本経営工学会論文誌

    Peer review

    2025.04
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    Now

  • 電子情報通信学会 論文誌

    Scientific advice/Review

    2024.03
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    Now

Internal Special Research Projects

  • A Hypergraph Motif Analysis Method for Understanding Structures in Consumer Evaluations

    2025   Goto Masayuki, Yuya Ieiri, Xu Wang

    　View Summary

    This research successfully developed a hypergraph motif analysis method to decode complex, non-linear structures in consumer evaluations. Unlike traditional pairwise analysis, our approach captures high-order interactions among consumers, products, and sentiments.The project yielded three core contributions:Methodological Innovation: Established a robust framework utilizing network motifs to model time-series dynamics and multi-dimensional consumer feedback.Empirical Validation: The method was successfully applied to diverse real-world datasets, validating its effectiveness across second-hand luxury e-commerce, commercial district marketing (stamp rally data), and AI ethics education.Market Insight Generation: The analysis revealed critical structural patterns, including dynamic sentiment dependencies and distinct behavioral differences between e-commerce and brick-and-mortar luxury markets.These findings provide granular, actionable insights for data-driven marketing strategies. The project outcomes have been widely disseminated, resulting in three peer-reviewed journal articles (including Decision Analytics Journal and Journal of Information Processing) and one international conference proceeding in 2025.