Zhiwen Yu

schoolNorthwestern Polytechnical Universitybar_chart#807 Global Rank

Total Papers

HCI Rank

#807

Research Areas

Years Active

Recent Publications

Wisdom of Crowds: A Human-Machine-Things Cooperative Scheduling Method for Heterogeneous Mobile Crowdsensing

Relying on the development of crowdsourcing ideas and mobile crowd sensing (MCS) technology, many tasks that originally required a lot of manpower and material resources have been solved efficiently. However, with the development of urbanization, the traditional MCS systems have gradually been unable to cope with the…

UBICOMP '24CorrespondingComputational Methods in HCI +1

LiqDetector: Enabling Container-Independent Liquid Detection with mmWave Signals Based on a Dual-Reflection Model

Wang等人提出LiqDetector毫米波液体检测系统，采用双反射模型突破容器限制，实现高灵敏度液体类型识别。

UBICOMP '24CorrespondingContext-Aware Computing +1

EchoPFL: Asynchronous Personalized Federated Learning on Mobile Devices with On-Demand Staleness Control

Li 等人提出 EchoPFL 框架，通过异步本地训练和按需陈旧度控制实现移动端高效的个性化联邦学习，保护用户隐私。

UBICOMP '245th+ AuthorContext-Aware Computing +2

GrainSense: A Wireless Grain Moisture Sensing System based on Wi-Fi Signals

Wang 等人开发 GrainSense 系统，利用 Wi-Fi 信号无接触测量谷物水分，实现仓储谷物湿度的实时无线监测。

UBICOMP '235th+ AuthorContext-Aware Computing +1

Understanding the Mechanism of Through-Wall Wireless Sensing: A Model-based Perspective

"During the last few years, there is a growing interest on the usage of Wi-Fi signals for human activity detection. A large number of Wi-Fi based sensing systems have been developed, including respiration detection, gesture classification, identity recognition, etc. However, the usability and robustness of such system…

UBICOMP '23CorrespondingSmart Cities & Urban Sensing +1

sUrban: Stable Prediction for Unseen Urban Data from Location-based Sensors

"Recent machine learning research on smart cities has achieved great success in predicting future trends, under the key assumption that the test data follows the same distribution of the training data. The rapid urbanization, however, makes this assumption challenging to hold in practice. Because new data is emerging…

UBICOMP '23CorrespondingGenerative AI (Text, Image, Music, Video) +2

AdaEnlight: Energy-aware Low-light Video Stream Enhancement on Mobile Devices

"The ubiquity of camera-embedded devices and the advances in deep learning have stimulated various intelligent mobile video applications. These applications often demand on-device processing of video streams to deliver real-time, high-quality services for privacy and robustness concerns. However, the performance of th…

UBICOMP '232nd AuthorHuman-LLM Collaboration +2

Genie in the Model: Automatic Generation of Human-in-the-Loop Deep Neural Networks for Mobile Applications

"Advances in deep neural networks (DNNs) have fostered a wide spectrum of intelligent mobile applications ranging from voice assistants on smartphones to augmented reality with smart-glasses. To deliver high-quality services, these DNNs should operate on resource-constrained mobile platforms and yield consistent perfo…

MOBILEHCI '233rd AuthorContext-Aware Computing +1

VPRNet: Voxel-based Efficient and Partial-to-Partial Point Cloud Registration on Mobile Devices

With the popularity of embedded devices such as LIDAR sensors and depth cameras, the resulting point clouds become the main data format for representing the 3D world and spawn various smart mobile applications. A key technology for enabling these applications to furnish high-quality services is real-time point cloud r…

CSCW '212nd AuthorCrowds and Collaboration

Task Execution Quality Maximization for Mobile Crowdsourcing in Geo-Social Networks

With the rapid development of smart devices and high-quality wireless technologies, mobile crowdsourcing (MCS) has been drawing increasing attention with its great potential in collaboratively completing complicated tasks on a large scale. A key issue toward successful MCS is participant recruitment, where a MCS platf…

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