September 15, 2022, Atlanta, USA and virtual (all over the world)

Combining Physical and Data-Driven Knowledge in Ubiquitous Computing

Ubicomp 2022 Workshop

ABOUT THE WORKSHOP

In the real-world ubiquitous computing systems, it is difficult to require a significant amount of data to obtain accurate information through pure data-driven methods. The performance of data-driven methods relies on the quantity and ‘quality’ of data. They perform well when a sufficient amount of data is available, which is regarded as ideal conditions. However, in real-world systems, collecting data can be costly or impossible due to practical limitations. On the other hand, it is promising to utilize physical knowledge to alleviate these issues of data limitation. The physical knowledge includes domain knowledge from experts, heuristics from experiences, analytic models of the physical phenomena and etc.

CALL FOR PAPER

The goal of the workshop is to explore the intersection between (and the combination of) data and physical knowledge. The workshop aims to bring together domain experts that explore the physical understanding of the data, practitioners that develop systems and the researchers in traditional data-driven domains. The workshop welcomes papers, which focuses on addressing these issues in different applications/domains as well as algorithmic and systematic approaches to applying physical knowledge. Therefore, we further seek to develop a community that systematically analyzes the data quality regarding inference and evaluates the improvements from physical knowledge. Preliminary and on-going work is welcomed.

  • The accepted papers are invited to be extended for a journal fast-track submission at (1) Digital Signal Processing: A Review Journal; and (2) Intelligent and Converged Networks with at least 30% contribution on novelty
  • Topics of Interests

    Topics of interests include, but are not limited to, the follows:
    • - Innovations in learning algorithms that combine physical knowledge or models for sensor perception and understanding
    • - Experiences, challenges, analysis, and comparisons of sensor data in terms of its physical properties
    • - Sensor data processing to improve learning accuracy
    • - Machine learning and deep learning with physical knowledge on sensor data
    • - Mobile and pervasive systems that utilize physical knowledge to enhance data acquisition
    • - System services such as time and location estimation enhanced by additional physical knowledge
    • - Heterogeneous collaborative sensing based on physical rules
    • - Distributed sensing for cyber-physical systems
    • - Advanced machine learning algorithms and solutions for efficient sensing
    The application areas include but not limited to:
    • - Human-centric sensing applications
    • - Environmental and structural monitoring
    • - Smart cities and urban health
    • - Health, wellness and medical
    • - Smart energy systems and intelligent transportation networks

    Successful submissions will explain why the topic is relevant to the data limitation caused problem that may be solved through the physical understanding of domain knowledge. In addition to citing relevant, published work, authors must cite and relate their submissions to relevant prior publications of their own. Ethical approval for experiments with human subjects should be demonstrated as part of the submission.

    Important Dates

    Submission Deadline: July 29, 2022 August 5, 2022

    Notifications: August 21, 2022

    Camera-ready: TBD

    Workshop: September 15, 2022

    Submission Guidelines

    Submissions can be made at PCS.

    Please submit short papers that are at most 5 single-spaced 8.5” x 11” pages, including figures and tables, but excluding references, two-column format, using 10-point type on 11-point (tight single-spaced) leading, with a maximum text block of 7” wide x 9” deep with an inter-column spacing of .25”. Submissions may include as many pages as needed for references.

    ACM Template can be found here.

    The accepted paper will be published in the proceedings with Ubicomp papers this year.

    ORGANIZERS

    Workshop Chairs

    Linqi Song City University of Hong Kong

    Zhengxiong Li University of Colorado Denver

    Amir H. Alavi University of Pittsburgh

    Advising Committee

    Wenbo Ding Tsinghua University

    Xinlei Chen Tsinghua University

    Shijia Pan University of California Merced

    Workshop TPC Chairs

    Sicong Liu Xiamen University

    Yongpan Zou Shenzhen University

    Susu Xu Stony Brook University

    Technical Programm Committee

    Yaxiong Xie Princeton University

    Susu Xu Stony Brook University

    Shuai Wang Southeast University

    Weitao Xu City University of Hong Kong

    Shijia Pan University of California Merced

    Sicong Liu Xiamen University

    Amir H. Alavi University of Pittsburgh

    Yongpan Zou Shenzhen University

    Linqi Song City University of Hong Kong

    Wenbo Ding Tsinghua University

    Zhengxiong Li University of Colorado Denver

    Xinlei Chen Tsinghua University

    Chenglin Miao University of Georgia

    Hailu Xu California State University, Long Beach

    Yidan Hu Rochester Institute of Technology

    Yinchen Jin University at Buffalo

    Qianyi Huang Shaanxi University of Science & Technology

    Zimu Zhou Singapore Management University

    Chengwen Luo Shenzhen University

    Man Zhou Huazhong University of Science and Technology

    Yu Yang Lehigh University

    Wenchuan Wei University of California San Diego

    Yuchong Zhang Chalmers University of Technology

    Web Chairs

    Guangfeng Yan City University of Hong Kong

    Xiaoming Xue City University of Hong Kong

    Publicity Chair

    Linqi Song City University of Hong Kong

    Sicong Liu Xiamen University

    AGENDA

    15th September 2022 (Eastern Daylight Time)

    Oral Session 1 (8:30-9:50): Sensing

    8:30-8:50 TRACT: Towards Large-Scale Crowdsensing With High-Efficiency Swarm Path Planning

    Presenter: Zuxin Li, Tsinghua-Berkeley Shenzhen Institute

    8:50-09:10 Multimodal Surface Sensing based on Hybrid Flexible Triboelectric and Piezoresistive Sensor

    Presenter: Zenan Lin, Tsinghua-Berkeley Shenzhen Institute

    09:10-09:30 EmoTracer: A Wearable Physiological and Psychological Monitoring System With Multi-modal Sensors

    Presenter: Danyang Wang, Shenzhen University

    9:30-9:50 Design of High Sensitivity Interdigital Capactive Humidity Sensor Based on Uncertainty Analysis

    Presenter: Dapeng Li, Beihang University


    5-min break

    Oral Session 2 (9:55-11:15): Privacy and Security

    9:55-10:15 Privacy-Preserving Cooperative Visible Light Positioning for Nonstationary Environment: A Federated Learning Perspective

    Presenter: Tiankuo Wei, Xiamen University

    10:15-10:35 Privacy-preserved Intermediate Feature Compression for Cyber-Physical Systems

    Presenter: Zixi Wang, Xi'an Jiaotong University

    10:35-10:55 MobileKey: A Fast and Robust Key Generation System for Mobile Devices

    Presenter: Keqi Song, City University of Hong Kong

    10:55-11:15 Anomaly Detection based on Broad Leaning System for Rolling Element Bearing Fault Diagnosis

    Presenter: Le Yang, Xi'an Jiaotong University


    5-min break

    Oral Session 3 (11:20-12:40): Learning for Wireless Systems

    11:20-11:40 Power and Interference Control for VLC-Based UDN: A Reinforcement Learning Approach

    Presenter: Xiao Tang, Xiamen University

    11:40-12:00 Incentivizing Mobility of Multi-agent Vehicle Swarms with Deep Reinforcement Learning for Sensing Coverage Optimization

    Presenter: Mohib Azam, Stony Brook University

    12:00-12:20 Federated Capsule Graph Neural Network with Personalization

    Presenter: Meilin Yang, Tsinghua-Berkeley Shenzhen Institute

    12:20-12:40 DeliverSense: Efficient Delivery Drone Scheduling for Crowdsensing with Deep Reinforcement Learning

    Presenter: Xuecheng Chen, Tsinghua-Berkeley Shenzhen Institute


    THE VENUE

    The CPD 2022 workshop is part of Ubicomp 2022, which will be held at Atlanta.

    Online Conference Room (Main)

    CPD 2022 (co-located with ACM UbiComp 2022)

    Meeting ID: 926 3523 7310

    Password : 892173

    Click to join the meeting

    Awards

    The Award of Best Paper

    DeliverSense: Efficient Delivery Drone Scheduling for Crowdsensing with Deep Reinforcement Learning

    Authors: Xuecheng Chen, Haoyang Wang, Zuxin Li, Wenbo Ding, Fan Dang, Chenye Wu, Xinlei Chen


    The Award of Best Paper Runner-Up

    Incentivizing Mobility of Multi-agent Vehicle Swarms with Deep Reinforcement Learning for Sensing Coverage Optimization

    Authors: Mohib Azam, Xinlei Chen, Susu Xu


    The Award of Best Presentation

    Pravacy-preserved Intermediate Feature Compression for Cyber-Physical Systems

    Authors: Zixi Wang, Yuan Zhang, Le Yang, Fan Li