Pang Yanbo ＰａｎｇＹａｎｂｏ

Researcher Number	60870178
Other IDs
Affiliation (Current)	2025: 東京大学, 空間情報科学研究センター, 特任講師
Affiliation (based on the past Project Information) *help	2024: 東京大学, 空間情報科学研究センター, 特任講師 2021 – 2024: 東京大学, 空間情報科学研究センター, 特任助教
Review Section/Research Field	Principal Investigator Basic Section 22050:Civil engineering plan and transportation engineering-related Except Principal Investigator Basic Section 22050:Civil engineering plan and transportation engineering-related / Medium-sized Section 23:Architecture, building engineering, and related fields / Basic Section 25010:Social systems engineering-related / Medium-sized Section 4:Geography, cultural anthropology, folklore, and related fields
Keywords	Principal Investigator データ基盤 / 人の流れ / 大規模言語モデル / 対話型機械学習 / 強化学習 / 深層学習 / 擬似人流 / 生成系AI / 人間参加型機械学習 / エージェントシミュレーション … More Except Principal Investigator … More オープンデータ / 交通シミュレーション / エージェントモデル / グラフニューラルネットワーク / 人流データ / 生成AI技術 / 三次元建物データ / 三次元都市空間 / 経済レジリエンス / データコモンズ / グローバル / 人流 / 建物 / 自動抽出 / デジタルツイン / 擬似人流 Less

行動変容に対してレジリエントな地域経済ネットワークの構築に向けたデータ基盤の開発
- Principal Investigator
  
  矢部貴大
- Project Period (FY)
  2024 – 2026
- Research Category
  
  Grant-in-Aid for Scientific Research (B)
- Review Section
  
  Basic Section 25010:Social systems engineering-related
- Research Institution
  The University of Tokyo
大規模移動データに基づく生成系AIモデルMobilityGPTの開発と適用Principal Investigator
- Principal Investigator
  
  Pang Yanbo
- Project Period (FY)
  2024 – 2025
- Research Category
  
  Grant-in-Aid for Early-Career Scientists
- Review Section
  
  Basic Section 22050:Civil engineering plan and transportation engineering-related
- Research Institution
  The University of Tokyo
生成AI技術を用いた都市規模の三次元建物データの効率的な作成・更新技術の体系化
- Principal Investigator
  
  関本義秀
- Project Period (FY)
  2024 – 2025
- Research Category
  
  Grant-in-Aid for Challenging Research (Exploratory)
- Review Section
  
  Medium-sized Section 23:Architecture, building engineering, and related fields
- Research Institution
  The University of Tokyo
疑似人流開発プラットフォームの構築
- Principal Investigator
  
  樫山武浩
- Project Period (FY)
  2023 – 2025
- Research Category
  
  Grant-in-Aid for Scientific Research (C)
- Review Section
  
  Basic Section 22050:Civil engineering plan and transportation engineering-related
- Research Institution
  Osaka University of Economics
Fundamental Research for the Creation of a Global Human Flow Data Commons
- Principal Investigator
  
  SEKIMOTO YOSHIHIDE
- Project Period (FY)
  2022 – 2023
- Research Category
  
  Grant-in-Aid for Challenging Research (Exploratory)
- Review Section
  
  Medium-sized Section 4:Geography, cultural anthropology, folklore, and related fields
- Research Institution
  The University of Tokyo
Development of Human-in-the-Loop Human Mobility SimulationPrincipal Investigator
- Principal Investigator
  
  Pang Yanbo
- Project Period (FY)
  2021 – 2023
- Research Category
  
  Grant-in-Aid for Early-Career Scientists
- Review Section
  
  Basic Section 22050:Civil engineering plan and transportation engineering-related
- Research Institution
  The University of Tokyo

All 2024 2023 2022 2021

All Journal Article Presentation

[Journal Article] Nationwide Synthetic Human Mobility Dataset Construction from Limited Travel Surveys and Open Data2024
- Author(s)
  Takehiro Kashiyama, Yanbo Pang, Yuya Shibuya, Takahiro Yabe, Yoshihide Sekimoto
- Journal Title
  
  Computer-Aided Civil and Infrastructure Engineering
  
  Volume: -
- Peer Reviewed / Open Access / Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-22K18498
[Journal Article] Spatial Attention Based Grid Representation Learning For Predicting Origin?Destination Flow2022
- Author(s)
  Cai Mingfei、Pang Yanbo、Sekimoto Yoshihide
- Journal Title
  
  2022 IEEE International Conference on Big Data (Big Data)
  
  Volume: - Pages: 485-494
- DOI
  10.1109/bigdata55660.2022.10021023
- Peer Reviewed
- Data Source
  KAKENHI-PROJECT-21K14260
[Journal Article] Deep Learning for Destination Choice Modeling: A Fundamental Approach for National Level People Flow Reconstruction2022
- Author(s)
  Pang Yanbo、Sekimoto Yoshihide
- Journal Title
  
  2022 IEEE International Conference on Big Data (Big Data)
  
  Volume: - Pages: 1900-1905
- DOI
  10.1109/bigdata55660.2022.10020165
- Peer Reviewed
- Data Source
  KAKENHI-PROJECT-21K14260
[Journal Article] Uncertainty of Traffic Congestion Estimation Using Nationwide Pseudo Trip Data and Agent-Based Simulation2022
- Author(s)
  Tewari Aayush、Pang Yanbo、Sekimoto Yoshihide
- Journal Title
  
  2022 IEEE International Conference on Big Data (Big Data)
  
  Volume: - Pages: 3854-3863
- DOI
  10.1109/bigdata55660.2022.10020749
- Peer Reviewed
- Data Source
  KAKENHI-PROJECT-21K14260
[Journal Article] Simulating Human Mobility with Agent-based Modeling and Particle Filter Following Mobile Spatial Statistics2021
- Author(s)
  Cai Mingfei、Pang Yanbo、Kashiyama Takehiro、Sekimoto Yoshihide
- Journal Title
  
  Proceedings of the 29th International Conference on Advances in Geographic Information Systems
  
  Volume: - Pages: 411-414
- DOI
  10.1145/3474717.3484203
- Peer Reviewed / Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-21K14260
[Presentation] Deep Learning Approach to Logistics Trips Generation: Enhancing Pseudo People Flow with Agent-based Modeling2023
- Author(s)
  Zhang, K., Pang, Y., and Sekimoto, Y
- Organizer
  IEEE ITS Annual Conference
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-22K18498
[Presentation] Synthetic Network Traffic Data Generation using Deep Generative Models2023
- Author(s)
  Yanbo Pang, Pierre Ferry, Kunyi Zhang
- Organizer
  NetMob 2023 Book of Abstracts
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-21K14260
[Presentation] Synthetic Network Traffic Data Generation using Deep Generative Models2023
- Author(s)
  Yanbo Pang, Pierre Ferry, Kunyi Zhang
- Organizer
  Netmob 2023
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-22K18498
[Presentation] Towards Pseudo People Flow: Developing a Deep Generative Model based on PT Data to Reproduce Large-Scale Daily People Activity Profiles2023
- Author(s)
  Yurong ZHANG, Kunyi ZHANG, Yanbo PANG, Yoshihide SEKIMOTO
- Organizer
  第32回地理情報システム学会学術研究発表大会講演論文集
- Data Source
  KAKENHI-PROJECT-21K14260
[Presentation] Deep Learning Approach to Logistics Trips Generation: Enhancing Pseudo People Flow with Agent-based Modeling2023
- Author(s)
  Zhang, K., Pang, Y., and Sekimoto, Y
- Organizer
  IEEE ITSC-2023
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-21K14260
[Presentation] 全国擬似人流データの提供と評価2022
- Author(s)
  Yanbo Pang，樫山武浩，関本義秀，
- Organizer
  第31回地理情報システム学会研究発表大会
- Data Source
  KAKENHI-PROJECT-21K14260
[Presentation] シナリオに基づく擬似人流生成のためのシミュレーション基盤の構築2022
- Author(s)
  澁谷遊野，Yanbo Pang，関本義秀
- Organizer
  第31回地理情報システム学会研究発表大会
- Data Source
  KAKENHI-PROJECT-21K14260
[Presentation] 擬似人流データにおける時刻表を考慮した自治体全域の交通手段の推計 ―静岡県裾野市を対象に―2022
- Author(s)
  笠原有貴，Yanbo Pang，樫山武浩，関本義秀，瀬崎薫
- Organizer
  第31回地理情報システム学会研究発表大会
- Data Source
  KAKENHI-PROJECT-21K14260
[Presentation] Development of a Reinforcement Learning based Agent Model and People Flow Data to Mega Metropolitan Area2021
- Author(s)
  Pang Yanbo、Kashiyama Takehiro、Sekimoto Yoshihide
- Organizer
  IEEE International Conference on Big Data (Big Data)
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-21K14260

1. SEKIMOTO YOSHIHIDE (60356087)

# of Collaborated Projects: 3 results

# of Collaborated Products: 2 results
2. 矢部貴大 (30940431)

# of Collaborated Projects: 3 results

# of Collaborated Products: 1 results
3. 小川芳樹 (70794296)

# of Collaborated Projects: 3 results

# of Collaborated Products: 0 results
4. 樫山武浩 (10611155)

# of Collaborated Projects: 2 results

# of Collaborated Products: 1 results
5. 瀬戸寿一 (80454502)

# of Collaborated Projects: 2 results

# of Collaborated Products: 0 results
6. 澁谷遊野 (20847917)

# of Collaborated Projects: 2 results

# of Collaborated Products: 1 results
7. 井上寛康 (60418499)

# of Collaborated Projects: 1 results

# of Collaborated Products: 0 results
8. 坪井和史 (60992302)

# of Collaborated Projects: 1 results

# of Collaborated Products: 0 results

Pang Yanbo Ｐａｎｇ Ｙａｎｂｏ

Research Projects

Research Products

Co-Researchers

行動変容に対してレジリエントな地域経済ネットワークの構築に向けたデータ基盤の開発

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

大規模移動データに基づく生成系AIモデルMobilityGPTの開発と適用Principal Investigator

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

生成AI技術を用いた都市規模の三次元建物データの効率的な作成・更新技術の体系化

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

疑似人流開発プラットフォームの構築

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

Fundamental Research for the Creation of a Global Human Flow Data Commons

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

Development of Human-in-the-Loop Human Mobility SimulationPrincipal Investigator

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

[Journal Article] Nationwide Synthetic Human Mobility Dataset Construction from Limited Travel Surveys and Open Data2024

Author(s)

Journal Title

Data Source

[Journal Article] Spatial Attention Based Grid Representation Learning For Predicting Origin?Destination Flow2022

Author(s)

Journal Title

DOI

Data Source

[Journal Article] Deep Learning for Destination Choice Modeling: A Fundamental Approach for National Level People Flow Reconstruction2022

Author(s)

Journal Title

DOI

Data Source

[Journal Article] Uncertainty of Traffic Congestion Estimation Using Nationwide Pseudo Trip Data and Agent-Based Simulation2022

Author(s)

Journal Title

DOI

Data Source

[Journal Article] Simulating Human Mobility with Agent-based Modeling and Particle Filter Following Mobile Spatial Statistics2021

Author(s)

Journal Title

DOI

Data Source

[Presentation] Deep Learning Approach to Logistics Trips Generation: Enhancing Pseudo People Flow with Agent-based Modeling2023

Author(s)

Organizer

Data Source

[Presentation] Synthetic Network Traffic Data Generation using Deep Generative Models2023

Author(s)

Organizer

Data Source

[Presentation] Synthetic Network Traffic Data Generation using Deep Generative Models2023

Author(s)

Organizer

Data Source

[Presentation] Towards Pseudo People Flow: Developing a Deep Generative Model based on PT Data to Reproduce Large-Scale Daily People Activity Profiles2023

Author(s)

Organizer

Data Source

Pang Yanbo ＰａｎｇＹａｎｂｏ