Research and Publications
Highlight projects:
Social Interaction Monitoring for Context-Sensitive Social Anxiety Detection and Interventions
working with Prof. Laura E. Barnes and Prof. Bethany A. Teachman
We use passively sensed biobehavioral data from wearable devices to detect state anxiety status and social contexts relevant to Social Anxiety Disorder (SAD). The ultimate goal is to develop personalized, context-sensitive just-in-time adaptive interventions (JITAIs) for SAD, enhancing digital mental health care accessibility and effectiveness.
Patient-Provider Communication Assessment using Mobile Technology and Language Models
working with Prof. Laura E. Barnes, Prof. Virginia T. LeBaron, and Prof. Tabor E. Flickinger
We merge mobile health with language models to develop tools for understanding patient-clinician interactions. These tools are designed for use in both clinical and online communication settings. The goal is to enhance healthcare communication and thereby improve the quality of treatment, especially in the domain of palliative care.
Social Crowdsensing and Information-Retrieval Generative AI Assistant
working with Prof. Laura E. Barnes and Prof. Jon Goodall
Publication List (^ indicates corresponding author, * indicates equal contributions, _ indicates my mentees, ordered by publication time)
2024
15. [ACM CSCW 2024] Zhiyuan Wang^, Nusayer Hassan, Virginia LeBaron, Tabor Flickinger, David Ling, James Edwards, Congyu Wu, Mehdi Boukhechba, Laura E. Barnes, CommSense: A Wearable-Based Computational Framework for Evaluating Patient-Clinician Interactions, The 27th ACM Conference on Computer-Supported Cooperative Work and Social Computing (conditionally accepted)
14. [ACM CHI EA] Zhiyuan Wang^, Varun Reddy, Karen Ingersoll, Tabor Flickinger, Laura E. Barnes, Rapport Matters: Enhancing HIV mHealth Communication through Linguistic Analysis and Large Language Models, ACM Conference on Human Factors in Computing Systems (CHI) Late-Breaking Work
2023
13. [IEEE BSN 2023] Zhiyuan Wang*^, Mark Rucker*, Emma R. Toner, Maria A. Larrazabal, Mehdi Boukhechba, Bethany A. Teachman, Laura E. Barnes, Understanding Privacy Risks versus Predictive Benefits in Wearable Sensor-Based Digital Phenotyping: A Quantitative Cost-Benefit Analysis, IEEE-EMBS International Conference on Body Sensor Networks 2023 [Online]
12. [ACM IMWUT 2023] Zhiyuan Wang*^, Maria A. Larrazabal*, Mark Rucker, Emma R. Toner, Katharine E Daniel, Shashwat Kumar, Mehdi Boukhechba, Bethany A. Teachman, Laura E. Barnes, Detecting Social Contexts from Mobile Sensing Indicators in Virtual Interactions with Socially Anxious Individuals, Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies [Online]
11. [IEEE EMBC 2023] Zhiyuan Wang^, Mingyue Tang, Maria A. Larrazabal, Emma Toner, Mark Rucker, Congyu Wu, Bethany A. Teachman, Mehdi Boukhechba, Laura E. Barnes, Personalized State Anxiety Detection: An Empirical Study with Linguistic Biomarkers and A Machine Learning Pipeline. 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Sydney, Australia, 2023. [Arxiv]
10. [ACM IMWUT 2023] Tieqi Shou*, Zhuohan Ye*, Yayao Hong, Zhiyuan Wang, Hang Zhu, Zhihan Jiang, Dingqi Yang, Binbin Zhou, Cheng Wang, Longbiao Chen, CrowdQ: Predicting the Queue State of Hospital Emergency Department Using Crowdsensing Mobility Data-Driven Models, Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies [Online]
9. [Digital Health] Virginia LeBaron^, Flickinger, Tabor, David Ling, David Lee, James Edwards, Anant Tewari, Zhiyuan Wang, Laura Barnes, Feasibility and Acceptability Testing of CommSense: A Novel Communication Technology to Enhance Health Equity in Clinician-Patient Interactions, Digital Health, 2023. [Online]
8. [Preprint 2023] Emma R. Toner*, Mark Rucker*, Zhiyuan Wang, Maria A. Larrazabal, Lihua Cai, Debajyoti Datta, Elizabeth Thompson, Haroon Lone, Mehdi Boukhechba, Bethany A. Teachman, and Laura E. Barnes. Wearable Sensor-based Multimodal Physiological Responses of Socially Anxious Individuals across Social Contexts. [Arxiv]
7. [ICCH 2023] Flickinger, Tabor, Virginia LeBaron, Mehdi Boukhechba, James Edwards, Zhiyuan Wang, David Ling, Daniel Wilson, and Laura Barnes. Evidence-based approach to designing wearable technology to improve patient-clinician communication, International Conference on Communication in Healthcare, 2023 (Poster) [Online]
2022
6. [IEEE IOTJ 2022] Zhiyuan Wang, Haoyi Xiong^, Jie Zhang, Sijia Yang, Mehdi Boukhechba, Daqing Zhang, Laura E. Barnes, Dejing Dou, From personalized medicine to population health: a survey of mHealth sensing techniques, IEEE Internet of Things Journal, 2022. [Online] [PDF]
5. [SPJ-HDS 2022] Zhiyuan Wang^*, Haoyi Xiong*, Mingyue Tang, Mehdi Boukhechba, Tabor E Flickinger, Laura E. Barnes, Mobile Sensing in the COVID-19 Era, Science Partner Journal Health Data Science, AAAS, 2022. [Online]
4. [IEEE TMC 2022] Jiang Bian, Haoyi Xiong^, Zhiyuan Wang, Jingbo Zhou, Shilei Ji, Hongyang Chen, Daqing Zhang, Dejing Dou, AFCS: Aggregation-free spatial-temporal mobile community sensing, IEEE Transactions on Mobile Computing, 2022. [Online] [PDF]
3. [IEEE UIC 2022] Tieqi Shou*, Zhiyuan Wang*, Shang Shi, Dingqi Yang, Binbin Zhou, Cheng Wang, Longbiao Chen, Modeling Crowdedness of Emergency Departments Leveraging Crowdsensing Mobility Data, IEEE International Conference on Ubiquitous Intelligence and Computing, 2022. []
2. [ACM TOSN 2022] Guimin Dong, Mingyue Tang, Zhiyuan Wang, Jiechao Gao, Lihua Cai, Bradford Campbell, Laura E. Barnes, Mehdi Boukhechba, Graph neural networks in IoT sensing: a survey, ACM Transactions on Sensor Networks, 2022. [PDF] [Online] [Github]
1. [IEEE TMC 2022] Hang Zhu, Tieqi Shou, Ruiying Guo, Zhihan Jiang, Zeyu Wang, Zhiyuan Wang, Zhiyong Yu, Weijie Zhang, Cheng Wang, Longbiao Chen, RedPacketBike: a graph-based demand modeling and crowd-driven station rebalancing framework for bike sharing systems, IEEE Transactions on Mobile Computing, 2022. [Online]
Presentations/Invited Talks
International Conference on Communication in Healthcare, 2024: "Application of Linguistic Analysis and Large Language Models to Patient-Clinician Communication"
UVA Cognitive Science Program CogFest: "Towards Sensing and Personalized Intervnetions for Mental Health" (Invited by Prof. Per Sederberg)
ACM CHI conference on Human Factors in Computing Systems, 2024: "Rapport Matters: Enhancing HIV mHealth Communication through Linguistic Analysis and Large Language Models"
Commonwealth Cyber Initiative Symposium, 2024: “When and where feel anxious? Towards an In-Context Social Anxiety Sensing and Interventions with Mobile Sensing”
State of the Science in Hospice and Palliative Care, 2024: “Testing the Feasibility and Acceptability of Wearable Technology to Improve Patient-Clinician Communication”
ACM International Joint Conference on Pervasive and Ubiquitous Computing, 2023: “Detecting Social Contexts from Mobile Sensing Indicators in Virtual Interactions with Socially Anxious Individuals”
IEEE International Conference on Body Sensor Networks: “Understanding Privacy Risks versus Predictive Benefits in Wearable Sensor-Based Digital Phenotyping: A Quantitative Cost-Benefit Analysis”
Digital Mental Health & AI Symposium, 2023: “Detecting Social Contexts from Mobile Sensing Indicators in Virtual Interactions with Socially Anxious Individuals”
Digital Mental Health & AI Symposium, 2023: “CAMSA:Context-Aware Micro-interventions for Social Anxiety”
IEEE International Conference of the Engineering in Medicine and Biology Society, 2023: “Personalized State Anxiety Detection: An Empirical Study with Linguistic Biomarkers and A Machine Learning Pipeline”
Association for Behavioral and Cognitive Therapies 57th Annual Convention, 2023: “Personalized Models for Social Context Detection using Passively Sensed Data”
UVA Engineering Research Symposium, 2023: “Detecting Social Contexts from Mobile Sensing Indicators for Social Anxiety JITAIs”
LinkLab Student Flash Talk, 2023: “Toward Personalized, Context-Aware Interventions for Social Anxiety”
NSF-NIH Smart and Connected Health PI Meeting, 2022: “Student Presentation: Personalized Machine Learning for Digital Mental Health”
International Conference on Communication in Healthcare, 2022: “Evidence-based approach to designing wearable technology to improve patient-clinician communication”
McGill International Congress on Palliative Care, 2022: Developing ‘best practices’ communication metrics to inform design of wearable technology to improve patient-clinician interactions
The Society of General Internal Medicine Annual Conference, 2022: Evaluating Acceptability and Feasibility of CommSense, a Novel Wearable Technology to Improve Clinician-Patient Communication
Research Mentees
Ms. Kaleigh O'Hara, Personalized Mental Health Interventions, MS in data science, (2023~present, UVA - now PhD student in UVA Data Science)
Mr. Varun Reddy, Audio Analysis and Generative AI, Undergrad in computer science, (2022~present, UVA)
Mr. Nusayer Hassan, Patient-Provider Communication, MS in systems and information engineering, (2022~present, UVA)
Mr. Francisco Santiago, Social Dynamics and Anxiety, Undergrad in computer science, via VA-NC Alliance Research Program (2023 Summer, UVA)
Ms. Shang Shi, Queueing Theory and Estimation, Undergrad in applied math in Imperial College London (2021, Xiamen University)