Soto Anno (安納 爽響)
3rd-year doctor student at Tokyo Institute of Technology, Tokyo, Japan.
Supervisor: Masamichi Shimosaka
Email: anno [at] miubiq.cs.titech.ac.jp
[CV(ver. 202409)][Google Schalor][GitHub]
Short Biography
I am Soto Anno (安納 爽響), a 3rd year doctor student in the Department of Computer Science at Tokyo Institute of Technology (Tokyo Tech). 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
2024
2023
2022
2021
2020
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]
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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)
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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.
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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.
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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]
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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]
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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]
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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
- 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
- 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
Education
- Doctor of Engineering, April 2022 – March 2025 (expected).
- 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
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
Soto Anno (安納 爽響)
3rd-year doctor student at Tokyo Institute of Technology, Tokyo, Japan.
Supervisor: Masamichi Shimosaka
Email: anno [at] miubiq.cs.titech.ac.jp
[CV(ver. 202409)][Google Schalor][GitHub]
Short Biography
I am Soto Anno (安納 爽響), a 3rd year doctor student in the Department of Computer Science at Tokyo Institute of Technology (Tokyo Tech). 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
2024
2023
2022
2021
2020
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)
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.
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.
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
Awards
Projects
Education
Research & Work Experience
Funding Source
Other Developing Experiences
Skills
Programming: Scala, Python, Java, Kotlin, C/C++, JavaScript
Crowd Computing: AWS