Research Profile

Yuuki Nishiyama, Ph.D.

Associate Professor, Center for Spatial Information Science, The University of Tokyo

Yuuki Nishiyama is an Associate Professor at the Center for Spatial Information Science (CSIS) in the University of Tokyo. He obtained M.S.(2014) in Media and Governance from Keio University, and Ph.D. in Media and Governance (2017) from Keio University, respectively. He had worked at Keio University in Japan and the University of Oulu in Finland, as a post-doctoral researcher respectively. He started work at the Institute of Industrial Science in the University of Tokyo as a Research Associate in 2019, and has worked as Assistant Professor at CSIS from 2022. Since 2025, he is working in the current position. His current research interests include ubiquitous computing systems, mobile-wearable sensing platforms, and human ability augmentation. He is a member of ACM, IEEE, and Information Processing Society of Japan (IPSJ). 

Background

  • Associate Professor: Center for Spatial Information Science, The University of Tokyo (Apr. 2025 – current)
  • Assistant Professor : Center for Spatial Information Science, The University of Tokyo (Apr. 2022 – Mar. 2025)
  • Research Associate : Institute of Industrial Science, The University of Tokyo (Jul. 2019 – Mar. 2022)
  • Postdoctoral Researcher: Faculty of Information Technology and Electrical Engineering, University of Oulu, Finland (Mar. 2018 – Jun. 2019) 
  • Postdoctoral Researcher: Graduate School of Media and Governance, Keio University, Japan (Aug. 2017 – Mar. 2018)
  • Research Assistant: Global Environmental System Leader (GESL) program, Graduate School of Media and Governance, Keio University, Japan (Apr. 2014 – Mar. 2017)

News

  • [2024.12.8] I had an invited talk at The 28th Annual Meeting of Japanese Society of Psychosomatic Internal Medicine about “Estimating mental state using passive mobile and wearable sensing“. 
  • [2024.10.13] I had an invited talk about “Estimating the state of a humen mental and physical condition using sensors on smartphone and machine learning,” at a special session of Humans Living in a Digital Society.
  • [2024.10.8] We received the Best Poster Award at ACM UbiComp 2024 for our research on “Investigating Acceptable Voice-based Notification Timings through Earable Devices: A Preliminary Field Study.”
  • [2024.10.8] We received the Best Poster Award at ACM UbiComp 2024 for our research on “Toward Detecting Student-Athletes’ Condition Using Passive Mobile and Wearable Sensing.“
  • [2024.07.16] A full paper, “Deep Learning-Based Compressed Sensing for Mobile Device-Derived Sensor Data,” was accepted at ACM CIKM2024.
  • [2024.07.01] Two poster papers are accepted by ACM UbiComp2024@Melbourne, Australia.
  • [2024.05.16] I had an invited talk at Mobile AI Systems which is a workshop in ACM MobiSys2024. The talk title is “In-the-wild IoT: Lessons from real-world implementations.”
  • [2024.04.24] Two poster papers are accepeted by ACM MobiSys2024@Tokyo.
  • A full paper, “RideGuard: Micro-Mobility Steering Maneuver Prediction with Smartphones,” was accepted at IEEE ICDCS2024@New Jersey.  
  • A full paper, “ReHEarSSE: Recognizing Hidden-in-the-Ear Silently Spelled Expressions,” was accepted at ACM CHI2024@Hawaii.  
  • I received an Outstanding Reviewer Award at the 25th ACM International Conference on Multimodal Interaction (ICMI2023) in Paris, France.  
  • I presented “Smartwatch-Based Sensing Framework for Continuous Data Collection: Design and Implementation“ at a workshop (Mental Health and Well-being: Sensing & Intervention) in ACM UbiComp23@Cancun.
  • A Late Breaking Results paper “Assessing Infant and Toddler Behaviors through Wearable Inertial Sensors: A Preliminary Investigation” was accepted in ACM ICMI2023.
  • A full paper “HeadSense: Visual Search Monitoring and Distracted Behavior Detection for Bicycle Riders” was accepted in IEEE WoWMoM2023.
  • A full paper “HeadMon: Head Dynamics Enabled Riding Maneuver Prediction” was accepted in IEEE PerCom2023.
  • We had two presentations about AthelteLife and UV estimation using GNSS Signal Strength in IPSJ SIG UBI78.

Research Topics

  • Context-aware technologies and systems: 
    • Technology for recognizing and predicting the behavior of micro-mobility riders to improve the safety of micro-mobility
    • Detection technology of infant/toddler behavior and parenting behavior related behaviors to support child-rearing
    • Methods of detecting infection prevention behavior (i.e., hand-washing, mask-usage, and conversation events) using consumer devices
  • Passive mobile and wearable sensing and its platforms:
    • Postpartum depression detection using passive sensing technology
    • Development of information platform for improving the performance and condition of athletes using mobile/wearable devices: Athlete Life, MiQ, and Ripken.
    • Open-source passive mobile/wearable sensing platform (mainly iOS, watchOS, and Android): AWARE, Senbay, and MOCHA
  • Human behavior change and intervention methods:
    • Platform for promoting team-level behavior change using competitive and cooperative lifelog sharing
    • Investigation of the impact of the way incentives are offered on infectious disease prevention behavior
Details

Selected Publication

  • Z. Han, E. Wang, M. Yu, J. Wang, Y. Nishiyama, K. Sezaki, "HeadMon+: Domain Adaptive Head Dynamic-based Riding Maneuver Prediction," In: IEEE Transactions on Mobile Computing, pp. 1-14, 2025.
  • A. Onodera, R. Ishioka, Y. Nishiyama, K. Sezaki, "Multi-label Classification Model for Infant Activity Recognition Using Single Inertial Sensor," In: IEEE Pervasive Computing, pp. 1-10, 2024.
  • L. Xu, Y. Nishiyama, K. Tsubouchi, K. Sezaki, "Deep Learning-Based Compressed Sensing for Mobile Device-Derived Sensor Data," In: Proceedings of the 33rd ACM International Conference on Information and Knowledge Management (ACM CIKM), pp. 5023–5030, ACM, Boise, ID, USA, 2024.
  • X. Dong, Y. Chen, Y. Nishiyama, K. Sezaki, Y. Wang, K. Christofferson, A. Mariakakis, "ReHEarSSE: Recognizing Hidden-in-the-Ear Silently Spelled Expressions," In: Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems (ACM CHI), Association for Computing Machinery, Hawaii, US, 2024.
  • Z. Han, X. Dong, L. Xu, Z. Zhu, E. Wang, Y. Nishiyama, K. Sezaki, "RideGuard: Micro-Mobility Steering Maneuver Prediction with Smartphones," In: 2024 IEEE 44th International Conference on Distributed Computing Systems (IEEE ICDCS), pp. 1039-1049, IEEE Computer Society, Jersey City, New Jersey, USA, 2024.
  • Y. Nishiyama, K. Sezaki, "Smartwatch-Based Sensing Framework for Continuous Data Collection: Design and Implementation," In: Adjunct Proceedings of the 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing (ACM UbiComp), ACM, Cancun, Mexico, 2023.
  • Z. Han, L. Xu, X. Dong, Y. Nishiyama, K. Sezaki "HeadMon: Head Dynamics Enabled Riding Maneuver Prediction," In: IEEE International Conference on Pervasive Computing and Communications (IEEE PerCom), IEEE, Atlanta, USA, 2023.
  • H. Peng, Y. Nishiyama, K. Sezaki, "Assessing environmental benefits from shared micromobility systems using machine learning algorithms and Monte Carlo simulation" In: Sustainable Cities and Society, pp. 104207, 2022, ISSN: 2210-6707.
  • Y. Nishiyama, H. Murakami, R. Suzuki, K. Oko, I. Sukeda, K. Sezaki, and Y. Kawahara, "MOCHA: Mobile Check-in Application for University Campuses Beyond COVID-19," In Proceedings of the 23rd International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing, ACM, Seoul, Republic of Korea, 2022 (Presented in a joint workshop, MobiCOVID 2022)
  • Y. Nishiyama, et al. "Physical Activity Analysis of College Students during the COVID-19 Pandemic Using Smartphones," Transactions of Information Processing Society of Japan (IPSJ), vol. 62, no. 10, page 1630-1643, 2021.
  • Y. Nishiyama, D. Ferreira, Y. Eigen, W. Sasaki, T. Okoshi, J. Nakazawa, A. K. Dey, and K. Sezaki, “iOS crowd-sensing won’t hurt a bit!: AWARE Framework and Sustainable Study Guideline for iOS Platform,” In: Distributed, Ambient and Pervasive Interactions (HCII 2020). Lecture Notes in Computer Science, vol 12203. Springer, Cham
  • Y. Nishiyama, T. Okoshi, T. Yonezawa, J. Nakazawa, K. Takashio, and H. Tokuda, “Towards Health Exercise Behavior Change for Teams Using Lifelog Sharing Models.,” IEEE J. Biomed. Heal. informatics, vol. PP, no. 99, p. 1, Sep. 2015.
Complete Publication List

Selected Awards

  • Best Poster Award: The ACM international joint conference on Pervasive and Ubiquitous Computing (ACM UbiComp 2024), October 8.
  • Outstanding Reviewer Awards: 25th ACM International Conference on Multimodal Interaction (ICMI2023)
  • Honorable Mention Award (Demo): 20th International Conference on Human-Computer Interaction with Mobile Devices and Services (MobileHCI 2018), September 2018
  • Best Young Researcher Award: IEICE Technical Committee on Ambient Intelligence and Sensor Networks, May 2015
  • SFC Student Award: KEIO University, March 2015
  • Best Paper Award: 2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (IEEE HealthCom 2014), October 2014
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