Soto Anno (安納 爽響)

Researcher at Network Service Systems Laboratories, NTT Corporation, Tokyo, Japan.

Email: soto.anno [at] ntt.com
[CV(ver. 202409)][Google Schalor][GitHub]

Short Biography

I am Soto Anno (安納 爽響), a researcher at the Network Service Systems Laboratories, NTT Corporation. I obtained Ph.D. degree from the Department of Computer Science at Institute of Science Tokyo (previously known as Tokyo Institute of Technology). In my Ph.D. course, I am a member of Shimosaka Research Group, advised by Prof. Masamichi Shimosaka. I am also working on my researh with Dr. Kota Tsubouchi. I am a reseach fellow of Japan Society for the Promotion of Science(JSPS) research fellowship (DC1).

My research interest includes a data-driven understanding of cities, such as urban dynamics, human mobility, and the city's atmosphere. Specifically, I am exploring urban dynamics analysis and human mobility modeling. My research interests also include machine learning, deep learning, big data analysis, geographic information systems, urban computing, context-aware computing, computer vision, and domain adaptation.

News

2025

• [Others] Mar 2025. Received Ph.D. degree from Science Tokyo (previously known as Tokyo Tech).

2024

• [Award] Dec. 2024. Received Excellent Paper Award at IPSJ-UBI 84th workshop.
• [Award] Nov. 2024. Received Excellent Student Paper Award at the 61st Railway Cybernetics Symposium.
• [Paper & Presentation] Nov. 2024. Our poster paper was accepted and will be presented at IEEE BigData 2024.
• [Presentation] Nov. 2024. Presenting our work "LLMによるシーン中の物体の形容記述を用いた景観画像の印象予測" at IPSJ-UBI 84nd workshop.
• [Paper & Presentation] Aug. 2024. Two papers were accepted in ACM SIGSPATIAL 2024.
• [Award] Jul. 2024. Received the IPSJ Yamashita SIG Research Award.
• [Paper] Jun. 2024. Our paper "Forecasting Lifespan of Crowded Events With Acoustic Synthesis-Inspired Segmental Long Short-Term Memory" was accepted in IEEE Access.
• [Award] May. 2024. Received Student Paper Award at IPSJ-UBI 82nd workshop.
• [Presentation] May. 2024. Presenting our work "イベント告知情報と大規模言語モデルに基づくイベント会場周辺の早期群衆混雑予報" at IPSJ-UBI 82nd workshop.
• [Presentation] Feb. 2024. Presenting our work "トピックモデルと大規模位置履歴を用いた地域ごとの興味関心分布の分析" at IPSJ-UBI 81st workshop.

2023

• [Award] Dec. 2023. Received Excellent Paper Award at IPSJ-UBI 80th workshop.
• [Presentation] Nov. 2023. Presenting our work "敵対的生成モデルに基づく 活動人口の波形描画を用いた 混雑寿命予報" at IPSJ-UBI 80th workshop
• [Paper & Presentation] Our work "CityScouter: Exploring the Atmosphere of Urban Landscapes and Visitor Demands with Multimodal Data" was accepted in UbiComp 2023 Demo Track.
• [Paper] Nov. 2023. Our paper "CityOutlook+: Early Crowd Dynamics Forecast Through Unbiased Regression With Importance-Based Synthetic Oversampling" was accepted in IEEE Pervasive Computing.
• [Award] Jun. 2023. Received Student Paper Award at IPSJ-UBI 78th workshop.
• [Award] Jun. 2023. Received Excellent Paper Award at IPSJ-UBI 78th workshop.
• [Presentation] May. 2023. Presenting our work "混雑の生起・継続・終了を考慮した状態認識型RNNに基づく早期群衆混雑予報" at IPSJ-UBI 78th workshop.
• [Presentation] May. 2023. Presenting our work "景観画像と地理的特性を考慮した都市における雰囲気の定量化" at IPSJ-UBI 78th workshop.

2022

• [Award] Dec. 2022. I received Best Presentation Award from Tokyo Tech Academy for Convergence of Materials and Informatics (TAC-MI).
• [Presentation] Mar. 2022. Presenting our work "地域特性理解促進のための画像・検索クエリ・GISデータに基づくデジタルマップアプリケーション." at IPSJ-SIGUBI 73th Workshop.
• [Others] Mar 2022. Received master's degree from Tokyo Tech.

2021

• [Others] Sept. 2021. Received Research Fellowship for Young Scientists (JSPS Gakushin DC1)
• [Presentation] Sept. 2021. Presenting our work "Caputring spatial distribution of people interests with web quries and location data: A large scale empirical study of metropolises in Japan" at IPSJ-SIGUBI 71th Workshop.
• [Paper] Aug. 2021. "CityOutlook: Early Crowd Dynamics Forecast towards Irregular Events Detection with Synthetically Unbiased Regression" was accepted in ACM SIGSPATIAL GIS 2021.

2020

• [Presentation] Nov 2020. Presenting our work "地域の幾何的関係を考慮したマルチタスク回帰に基づく高性能な都市動態予報" at IPSJ-SIGUBI 68th Workshop.
• [Paper] Aug 2020. "Supervised-CityProphet: Towards Accurate Anomalous Crowd Prediction" was accepted in ACM SIGSPATIAL GIS 2020.
• [Award] [Presentation] Jun 2020. I recieved the student paper award at IPSJ-SIGUBI 66th Workshop.
• [Presentation] May 2020. Presenting our work "GPS位置履歴と鉄道の乗換検索履歴を用いた異常混雑事前予測" at IPSJ-SIGUBI 66th Workshop.
• [Others] Mar 2020. Graduated from Tokyo Tech (one-year earlier graduation).

2019

• [Others] Oct 2019. Participated in Shimosaka Research Group at Tokyo Institute of Technology.
• [Paper] Aug 2019. "GAN-based Abnormal Detection by Recognizing Ungeneratable Patterns" was accpted in Asian Conference on Pattern Recognition (ACPR) 2019.

Publications

Journal Papers (Peer-reviewed)

• Soto Anno, Kota Tsubouchi, and Masamichi Shimosaka, "Forecasting Lifespan of Crowded Events With Acoustic Synthesis-Inspired Segmental Long Short-Term Memory," in IEEE Access, vol. 12, pp. 87309-87322, 2024, doi: 10.1109/ACCESS.2024.3417509. [link]

• Soto Anno, Kota Tsubouchi, and Masamichi Shimosaka, "CityOutlook+: Early Crowd Dynamics Forecast Through Unbiased Regression With Importance-Based Synthetic Oversampling" in IEEE Pervasive Computing, vol. 22, no. 04, pp. 26-34, 2023. doi: 10.1109/MPRV.2023.3312652. [link]

International Conferences (Peer-reviewed)

• Kaoru Miyanaga, Soto Anno, Kota Tsubouchi, and Masamichi Shimosaka. Revealing Universities' Atmosphere from Visitor Interests Using Search Queries and GPS Logs. Proceedings of the 2024 IEEE International Conference on Big Data (BigData) , pp. 8777-8777, Washington D.C., United States of America, 12 2024. [link].

• Soto Anno, Dario Tenore, Kota Tsubouchi, and Masamichi Shimosaka. Are Crowded Events Forecastable from Promotional Announcements with Large Language Models?. In Proceedings of the 32nd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL GIS 2024), Atlanta, GA, USA, Oct. 29 - Nov. 1. 2024. [link]

• Soto Anno, Kota Tsubouchi, and Masamichi Shimosaka. Congestion Forecast for Trains with Railroad-Graph-based Semi-Supervised Learning using Sparse Passenger Reports. In Proceedings of the 32nd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL GIS 2024), Atlanta, GA, USA, Oct. 29 - Nov. 1. 2024. [link]

• Yuki Kubota, Soto Anno, Tomomi Taniguchi, Kosei Miyazaki, Akira Tsujimoto, Hiraki Yasuda, Takayuki Sakamoto, Takaaki Ishikawa, Kota Tsubouchi, and Masamichi Shimosaka. 2023. CityScouter: Exploring the Atmosphere of Urban Landscapes and Visitor Demands with Multimodal Data. In Adjunct Proceedings of the 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing & the 2023 ACM International Symposium on Wearable Computing (UbiComp/ISWC '23 Adjunct). Association for Computing Machinery, New York, NY, USA, 157–161. [link]

• Soto Anno, Kota Tsubouchi, and Masamichi Shimosaka. CityOutlook: Early Crowd Dynamics Forecast towards Irregular Events Detection with Synthetically Unbiased Regression. In Proceedings of the 29th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL GIS 2021), Seattle, WA, USA, 2-5 Nov. 2021. [link]

• Soto Anno, Kota Tsubouchi, and Masamichi Shimosaka. Supervised-CityProphet: Towards accurate anomalous crowd prediction. In Proceedings of the 28th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL GIS 2020), Seattle, WA, USA, 3-6 Nov. 2020. [link]

• Soto Anno and Yuichi Sasaki. "GAN-based abnormal detection by recognizing ungeneratable patterns", Asian Conference on Pattern Recognition (ACPR) 2019, Auckland, New Zealand, 26-29 Nov. 2019. [link]

Domestic Conference

• 井手 海翔, 安納 爽響, 坪内 孝太, 下坂 正倫. LLMによるシーン中の物体の形容記述を用いた景観画像の印象予測. 情報処理学会研究報告 第84回UBI研究発表会, 兵庫県淡路市, 2024. [link]
• 安納爽響, 坪内孝太, 下坂正倫. イベント告知情報と大規模言語モデルに基づくイベント会場周辺の早期群衆混雑予報. 情報処理学会研究報告 第 82 回 UBI 研究発表会, 鹿児島県, 2024. [link]
• 宮永薫, 安納爽響, 坪内孝太, 下坂正倫. トピックモデルと大規模位置履歴を用いた地域ごとの興味関心分布の分析. 情報処理学会研究報告 第 81 回 UBI 研究発表会, 福岡県, 2024. [link]
• 安納爽響, 坪内孝太, 下坂正倫. 敵対的生成モデルに基づく 活動人口の波形描画を用いた 混雑寿命予報. 情報処理学会研究報告 第 80 回 UBI 研究発表会, 兵庫県, 2023. [link]
• 安納爽響, 坪内孝太, 下坂正倫. 混雑の生起・継続・終了を考慮した状態認識型 RNN に基づく 早期群衆混雑予報. 情報処理学会研究報告 第 78 回 UBI 研究発表会, 東京都, 2023. [link]
• 久保田祐輝, 安納爽響, 坪内孝太, 下坂正倫. 景観画像と地理的特性を考慮した都市における雰囲気の定量化. 情報処理学会研究報告 第 78 回 UBI 研究発表会, 東京都, 2023. [link]
• 久保田 祐輝, 安納 爽響, 谷口 智美, 坂本 隆之, 辻本 顕, 安田 啓紀, 宮崎 光世, 石川 貴明, 坪内 孝太, 下坂 正倫. 地域特性理解促進のための画像・検索クエリ・GISデータに基づくデジタルマップアプリケーション. 情報処理学会研究報告 第73回UBI研究発表会, オンライン開催, 3 2022. [link]
• Jinyuan Li, Soto Anno, Takayuki Sakamoto, Hiraki Yasuda, Akira Tsujimoto, Kota Tsubouchi, Masamichi Shimosaka. Caputring spatial distribution of people interests with web quries and location data: A large scale empirical study of metropolises in Japan. 情報処理学会研究報告 第 71 回 UBI 研究発表会, 4, 東京都, 9 2021. [link]
• 安納爽響, 坪内孝太, 下坂正倫. 地域の幾何的関係を考慮したマルチタスク回帰に基づく高性能な都市動態予報. 情報処理学会研究報告 第 68 回 UBI 研究発表会, 4, 東京都, 12 2020. [link]
• 安納爽響, 坪内孝太, 下坂正倫. GPS 位置履歴情報と鉄道の乗換検索履歴を用いた異常混雑事前予測. 情報処理学会研究報告 第 66 回 UBI 研究発表会, 4, 東京都, 5 2020. [link]

Awards

• Excellent paper award at IPSJ-SIGUBI 84th Workshop, 12, 2024
• Excellent student paper award at the 61st Railway Cybernetics Symposium.
• IPSJ Yamashita SIG Research Award 2024, 7, 2024
• Student paper award at IPSJ-SIGUBI 82nd Workshop, 5, 2024
• Excellent paper award at IPSJ-SIGUBI 80th Workshop, 11, 2023
• Excellent paper award at IPSJ-SIGUBI 78th Workshop, 6, 2023
• Student paper award at IPSJ-SIGUBI 78th Workshop, 6, 2023
• Best presentation award at TAC-MI International Forum, 12, 2022
• Student paper award at IPSJ-SIGUBI 66th Workshop, 6, 2020

Projects

• 楽音合成技術にヒントを得た 混雑の生起・継続・終了状態の認識に基づく 混雑寿命予報 (下坂研究室 プロジェクトページ)
• 地域の幾何的的関係を考慮した高性能な都市動態予報 (下坂研究室 プロジェクトページ)
• 位置情報履歴・乗換検索履歴を用いた異常度最適化に基づく異常混雑予報 (下坂研究室 プロジェクトページ)
• GANを用いた画像復元に基づく異常検知

Education

• Doctor of Engineering, April 2022 – March 2025.
  • Graduate School of Computing, Tokyo Institute of Technology, Japan
  • Research field: Urban Dynamics Analysis, Urban Computing, Big Data Analysis
  • Adviser: Prof. Masamichi Shimosaka
• Master of Engineering, April 2020 – March 2022.
  • Graduate School of Computing, Tokyo Institute of Technology, Japan
  • Research field: Urban Dynamics Analysis, Urban Computing, Big Data Analysis
  • Adviser: Prof. Masamichi Shimosaka
• Bachelor of Engineering, April 2017 – March 2020. (1-year earlier graduation)
  • Undergraduate School of Computing, Tokyo Institute of Technology, Japan
  • Research field of the bachelor thesis: Urban Dynamics Analysis, Big Data Analysis
  • Adviser: Prof. Masamichi Shimosaka

Research & Work Experience

• [April. 2025 - Present] Researcher, NTT R&D.
• [Sep. 2020 - Mar. 2024] Research internship, Yahoo! JAPAN Research.
• [Apr. 2019 - Mar. 2022] AI engineering intern, Neural Pocket Inc..
• [Aug. 2018 - Mar. 2022] AI engineering intern, AIQ Co., LTD..

Funding Source

• Research Fellowship for Young Scientists (DC1), JSPS. 2022.4-2025.3. [link]

Other Developing Experiences

• Developing a web application for smartphone using React + AWS (AppSync, Amplify, Congnito, DynamoDB)

Skills

Programming: Scala, Python, Java, Kotlin, C/C++, JavaScript
Crowd Computing: AWS