JINGYAO WU
PhD Candidate at School of Electrical Engineering and Telecommunications
University of New South Wales, Sydney, Australia
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Research Interests
Hi, Welcome to my page! I am Jingyao, final year PhD candidate from UNSW Sydney. My research interest lies in affective computing, machine learning, speech processing and AI in healthcare. I specialize in developing advanced frameworks for emotion representations, with a particular emphasis on quantifying and modelling ambiguous quantities (e.g., emotions and human perceptions). I explore the possibilities offered by different modalities, such as audio and video signals, in transmitting and predicting human behaviours. Additionally, I develop novel machine learning and deep learning models with applications in various domains, including emotion recognition, human-computer interaction and healthcare. Specifically, it includes:
Emotion recognition: investigation of emotion dynamics and emotion ambiguity modelling.
Time Series and Uncertainty Modelling: explore probability theory and statistical models for quantifying and interpreting ambiguous quantities, and integrate it with advanced machine learning.
Latest News
2023/09: My leading authored paper received the Best Paper Award 🏆 at ACII 2023, MIT Media Lab, USA!
2023/11: Invited talk at OMU-UNSW Joint Symposium on Engineering Research by Women at Osaka Metropolitan University, Osaka, Japan.
2023/11: Invited talk at The Rising Star Women in Engineering Workshop 2023, University of Tokyo, Tokyo, Japan.
2023/11: Visit and give invited talk at NTT Communication Science Laboratories, Tokyo, Japan.
2023/08: ISCA Grant (International Speech Communication Association), INTERSPEECH Dublin, Ireland 2023.
2023/07: Shorted listed candidate of Asian Deans’ Forum – The Rising Stars Women in Engineering Workshop, The University of Tokyo, 2023.
2023/07: Runner-up 🏆 of the Three-Minute-Thesis (3MT) competition of the Faculty of Engineering, UNSW, 2023
2023/06: Top 3% paper recognition 🏆 at ICASSP, Rhodes Island, Greece 2023.
2023/06: One paper titled "Belief Mismatch Coefficient (BMC): A Novel Interpretable Measure of Prediction Accuracy for Ambiquous Emotion States" is accepted by ACII 2023.
2023/05: One paper titled "From Interval to Ordinal: A HMM based Approach for Emotion Label Conversion" is accepted by INTERSPEECH 2023.
2023/05: Winner 🏆 of Three-Minute-Thesis (3MT) competition of the School of Electrical Engineering and Telecommunications, UNSW, 2023
2023/02: One paper titled "Constrained Dynamical Neural ODE for Time Series Modelling: A Case Study on Continuous Emotion Prediction" is accepted by ICASSP 2023.