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Associate Professor Jen Jen Chung
Associate Professor

Jen Jen Chung

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Overview

Background

Jen Jen Chung is an Associate Professor in Mechatronics within the School of Electrical Engineering and Computer Science at The University of Queensland. Her current research interests include perception, planning and learning for robotic mobile manipulation, algorithms for robot navigation through human crowds, informative path planning and adaptive sampling. Prior to working at UQ, Jen Jen was a Senior Researcher in the Autonomous Systems Lab (ASL) at ETH Zürich from 2018-2022 and was a Postdoctoral Scholar at Oregon State University researching multiagent learning methods from 2014-2017. She completed her Ph.D. on information-based exploration-exploitation strategies for autonomous soaring platforms at the Australian Centre for Field Robotics in the University of Sydney. She received her Ph.D. (2014) and B.E. (2010) from the University of Sydney.

Availability

Associate Professor Jen Jen Chung is:
Available for supervision
Media expert

Qualifications

  • Member, Institute of Electrical and Electronics Engineers, Institute of Electrical and Electronics Engineers

Works

Search Professor Jen Jen Chung’s works on UQ eSpace

64 works between 2011 and 2024

61 - 64 of 64 works

2014

Other Outputs

Learning to soar: exploration strategies in reinforcement learning for resource-constrained missions

Chung, Jen Jen (2014). Learning to soar: exploration strategies in reinforcement learning for resource-constrained missions. PhD Thesis, Faculty of Engineering and Information Technologies, School of Aerospace, Mechanical and Mechatronic Engineering, The University of Sydney.

Learning to soar: exploration strategies in reinforcement learning for resource-constrained missions

2013

Conference Publication

Gaussian processes for informative exploration in reinforcement learning

Chung, Jen Jen, Lawrance, Nicholas R.J. and Sukkarieh, Salah (2013). Gaussian processes for informative exploration in reinforcement learning. IEEE International Conference on Robotics and Automation, Karlsruhe, Germany, 6-10 May 2013. Washington, DC, United States: IEEE Computer Society. doi: 10.1109/icra.2013.6630938

Gaussian processes for informative exploration in reinforcement learning

2012

Conference Publication

A new utility function for smooth transition between exploration and exploitation of a wind energy field

Chung, Jen Jen, Angel, Miguel, Soto, Trujillo and Sukkarieh, Salah (2012). A new utility function for smooth transition between exploration and exploitation of a wind energy field. IEEE International Conference on Intelligent Robots and Systems, Vilamoura-Algarve, Portugal, 7-12 October 2012. Piscataway, NJ, United States: IEEE. doi: 10.1109/iros.2012.6385736

A new utility function for smooth transition between exploration and exploitation of a wind energy field

2011

Conference Publication

First airborne trial of a UAV based optical locust tracker

Brooker, Graham, Randle, Jeremy, Attia, Muhammad Esa, Xu, Zhe, Abuhashim, Tariq, Kassir, Abdallah, Chung, Jen Jen, Sukkarieh, Salah, Tahir, Nazifa and Dickens, John (2011). First airborne trial of a UAV based optical locust tracker. 2011 Australasian Conference on Robotics and Automation, Melbourne, VIC, Australia, 7-9 December 2011.

First airborne trial of a UAV based optical locust tracker

Funding

Current funding

  • 2025 - 2026
    Real-time 3D Situational Awareness for Mixed Autonomy Warehousing
    CSIRO
    Open grant

Supervision

Availability

Associate Professor Jen Jen Chung is:
Available for supervision

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Supervision history

Current supervision

  • Doctor Philosophy

    Adaptive Human-Robot Interaction for Unstructured, Dynamic Environments with Rich Physical Interactions

    Principal Advisor

    Other advisors: Dr Matthew D'Souza

Media

Enquiries

Contact Associate Professor Jen Jen Chung directly for media enquiries about:

  • informative and adaptive planning
  • multi-robot systems
  • reinforcement learning
  • robot crowd navigation
  • robotic mobile manipulation
  • robotic perception
  • robotics

Need help?

For help with finding experts, story ideas and media enquiries, contact our Media team:

communications@uq.edu.au