Ms Jo Plested

PhD Student and Lecturer
MComp (Artificial Intelligence), BActS, BEc
CSIT (108), N320

I am currently in the final year of my PhD in Computer Science at ANU. I specialise in deep learning. I also work as a lecturer and tutor co-ordinator for COMP4660/8420 Neural Networks, Deep Learning and Bio-inspired Computing.

My overall research goal is to develop techniques that allow people with limited expertise in the area to access the power of deep learning algorithms.

I have a Masters in Computer Science specialising in Artificial Intelligence. My Masters thesis was on generating nonhomogeneous object images using deep neural networks.

My academic background also includes degrees in Actuarial Studies and Economics.

Deep learning, transfer learning, automated algorithms for transfer learning and hyperparameter optimisation, reinforcement learning.

Yao, Yue, Jo Plested, and Tom Gedeon. "Deep Feature Learning and Visualization for EEG Recording Using Autoencoders." International Conference on Neural Information Processing. Springer, Cham, 2018.

Yao, Yue, Jo Plested, and Tom Gedeon. "A Feature Filter for EEG Using Cycle-GAN Structure." International Conference on Neural Information Processing. Springer, Cham, 2018.

Plested, J. F., et al. "Detection of universal cross-cultural depression indicators from the physiological signals of observers." 2017 Seventh International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW). IEEE, 2017.

 

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