Yuuki Nishiyama, Ph.D.
Yuuki Nishiyama is an Assistant Professor at the Center for Spatial Information Science 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 held his current position since 2022. 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).
- Assistant Professor : Center for Spatial Information Science, The University of Tokyo (Apr. 2022 – current)
- 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)
- A Late Breaking Results paper “Assessing Infant and Toddler Behaviors through Wearable Inertial Sensors: A Preliminary Investigation” was accepted in the 20th ACM International Conference on Multimodal Interaction (ICMI2023).
- A workshop paper, “Smartwatch-Based Sensing Framework for Continuous Data Collection: Design and Implementation”, was accepted in the ACM UbiComp/ISWC Workshop (8th Mental Health: Sensing & Intervention).
- A full paper “HeadSense: Visual Search Monitoring and Distracted Behavior Detection for Bicycle Riders” was accepted in the 24th IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM2023).
- A full paper “HeadMon: Head Dynamics Enabled Riding Maneuver Prediction” was accepted in IEEE International Conference on Pervasive Computing and Communications (PerCom2023).
- We had two presentations about AthelteLife and UV estimation using GNSS Signal Strength in IPSJ SIG UBI78.
- We had a presentation about a baby behavior recogntion method using a wearable motion sensor in the 85th National Convention of IPSJ.
- A full paper “Detecting hand hygienic behaviors in-the-wild using a microphone and motion sensor on a smartwatch” was accepted in 25th HCI International Conference (HCII2023).
- Two full papers regarding distributed ML and opportunistic routing were accepeted in IEEE 20th Annual Consumer Communications & Networking Conference (CCNC)
- 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