Data Dynamics

Current project

Applications for 2021 intake open 14 September 2020

 Fill out the Expression of Interest Form if you're interested in applying.

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VIP Snapshot

Diving into the data big bang - do cool things that help us manage massive data and support data-driven science, healthy living and global mobility!

Data Dynamics

ChallENG research goals

We will conduct analyses and develop techniques and tools on interactions between human, machine and infrastructure systems over multi-source data by looking at Machine Learning (ML), Artificial Intelligence (AI), Intelligent Transportation Systems (ITS), Human-Machine Interactions (HMI), human-vehicle-infrastructure interactions, and user experience design, among others. We have the following main themes:

Intelligent Science

  • Analyse signals for brain dynamics analysis, such as brain signals, of information consumption, with the help of data analytical methods
  • Applications on videos and images, such as movie caption generation, video classification, object detection and human action recognition
  • Design and develop a data management system to collect and organise data while keeping data integrity or achieving data anonymization
  • Interactive Living

    • Experiment on machine learning of music, such as instrument transformation and music composition
    • Look at content recommendations for decision making, for shopping, location, etc.
    • Design and develop smart living or smart mobility apps (e.g., parking information and guidance systems) for mobile and other devices

    Efficient Transportation

    • Big data analytics on massive travel trajectory data to uncover mobility patterns of various groups of people to traffic events/conditions prediction
    • Develop deep learning techniques for real-time and robust demand/traffic forecasting for optimal transportation scheduling and routing
    • Develop analytical models for driver/passenger behaviour detection for road safety
    • Develop artificial intelligence-based learning and controlling framework for a range of smart transport applications, e.g., autonomous vehicle trajectory control and traffic management, real-time ride-sourcing driver-rider matching, and vehicle dispatching

    Research, design or technical ChallENG for Data Dynamics

    • Data acquisition and storage, data labelling and augmentation algorithms and data representation and association learning
    • Exploring new machine learning models of analysing multimedia data and building models on devices with lower resources, such as mobiles
    • Descriptive, predictive and prescriptive modelling
    • Data visualization and model explanation

    Desired Background

    All engineering degrees are welcome, however, students specialising in the below areas are encouraged to apply.

    Research Areas* Degrees
    • Machine Learning
    • Artificial Intelligence
    • Data Mining
    • Human-Computer Interactions
    • Transport System Engineering
    • Large-scale Control and Optimization
    • Computer Science / Information Technology
    • Machine Learning / Algorithm designing
    • Web programming / Mobile app development / Software Engineering
    • Embedded systems
    • Data Visualization
    • Civil and Infrastructure Engineering
    • Automation Control Engineering
    • Mathematics/Statistics