Demos

Research prototypes and student projects from our group, showcasing real-world applications of AI and IoT technologies.

Research Group Demos

Brain Computer Interface (BCI) Systems

EEG-based Brain Computer Interface enables people to communicate with external devices by interpreting brain signals. Our work focuses on intention recognition, mental state decoding, and image reconstruction from brain activity.

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Related Publications

  • Dynamic Illness Severity Prediction via Multi-task RNNs (ICDM 2018)
  • Subject-Independent Movement Intention Recognition (CIKM 2018)
  • MindID: Person Identification from Brain Waves (IMWUT/UbiComp 2018)
  • Fuzzy Integral Optimization with Deep Q-Network (PAKDD 2018)

Human Activity Recognition

Device-free and wearable sensor approaches for real-time activity recognition. Applications include fall detection, ambulatory monitoring, and assistive living for elderly care.

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Related Publications

  • Multi-modality Sensor Data Classification (IJCAI 2018)
  • Interpretable Recurrent Convolutional Neural Networks (IJCNN 2018)
  • Compressive Representation for Device-Free Activity Recognition (IEEE TMC 2017)

Internet of Things and Smart Homes

Computational framework for activity recognition in personalized smart environments. Our system enables intelligent monitoring and automation in home settings through IoT sensors.

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Related Publications

  • Up in the Air: When Smart Homes Meet IoT (Computing, Springer 2017)
  • Web-based Management of Internet of Things (IEEE Internet Computing 2015)
  • Keeping You in the Loop (CIKM 2014)

Indoor Localization and Tracking

Novel localization and tracking system using Received Signal Strength field from passive RFID tags. Enables device-free indoor positioning without requiring users to carry any device.

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Related Publications

  • Device-Free Indoor Localization via Human-Object Interactions (WoWMoM 2016)
  • Tag-free RFID-based Passive Localization (CIKM 2014)
  • TagTrack: Device-free Localization Using Passive RFID Tags (MobiQuitous 2014)

Student Projects

Emotion Sensing via Smart Phone

Machine learning application utilizing smartphone sensors to monitor mental status and track emotional states through activity and environmental data collection.

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Guangyang Qi (Master Research Project, 2016)

Trust-based Social Recommendation

System designed to prevent fraudulent ratings and fake reviews in recommendation platforms by exploiting multi-layer trust relationships in social media.

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Zhen Zhu (Master Research Project, 2015)

Marauder's Map via Internet of Things

Web-based IoT application for location tracking and activity recognition, enabling identification of where everyone is and what they are doing in a smart building.

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Jack Gerrits (Bachelor CS Advanced Research Project, 2015)

Activity Recognition Using Smartphone Sensors

Android system utilizing accelerometer, gyroscope, and magnetometer sensors to recognize common human actions and postures such as standing, sitting, walking, and lying down.

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Leon Chea (Bachelor CS Advanced Research Project, 2015)

Detecting Unhealthy Smartphone Usage

Automated approach for detecting problematic smartphone usage patterns through collection and analysis of phone usage data, including usage in low-light conditions.

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Yuchieh (Henry) Yang (Bachelor CS Advanced Research Project, 2015)