2024/01: One paper titled "Uncertainty-aware Health Diagnostics via Class-balanced Evidential Deep Learning" is accepted by IEEE Journal of Biomedical and Health Informatics (J-BHI).

2023: TPC and reviewer for IJCAI, AAAI, UbiComp, ICMI, INTERSPEECH, ACII, JMIR, IEEE TAC, etc.

2023/12: One paper titled "OptiBreathe: An Earable-based PPG System for Continuous Respiration Rate, Breathing Phase, and Tidal Volume Monitoring" is accepted by HotMobile 2024. 

2023/12: Two papers accepted by ICASSP 2024, titled "Variational Connectionist Temporal Classification for Order-Preserving Sequence Modeling" and "Towards enabling DPOAE estimation on single-speaker earbuds".

2023/10: One review paper titled "Human-centered AI for mobile health sensing: challenges and opportunities" is accepted by Royal Society Open Science

2023/10: Two papers are accepted by IMWUT

2023/09: Best paper award from ACII 2023!

2023/08: One paper titled "DNN Controlled Adaptive Front-end for Replay Attack Detection Systems" is accepted by Speech Communication! 

2023/07: We will be giving a tutorial on "Multi-model wearable eye and audio for affect analysis" at ACII in MIT media lab this Sep and at ICMI in Paris this Oct! 

2023/06: Our paper has been recognized as Top 3% at ICASSP 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: One paper titled "Conditional Neural ODE Processes for Individual Disease Progression Forecasting: A Case Study on COVID-19" is accepted by KDD 2023! 

2023/04: One paper titled "Evaluating Listening Performance for COVID-19 Detection by Clinicians and Machine Learning: A Comparative Study" is accepted by JMIR!

2023/04: Co-organizing WellComp Workshop 2023 in conjunction with UbiComp!

2023/03: Social media co-chair for INTERSPEECH 2026!

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!

2022/08: Coverage for our recent paper at JMIR by the University of Cambridge Department of Computer Science and Technology!

2022: Papes accepted by JMIR, ICASSP, INTERSPEECH, TSRML2022 in NeurIPS, HotMobile, PerCom, etc!

2021: Papes accepted by NeurIPS, NPJ digital medicine, Frontiers in Computer Science, INTERSPEECH, etc. 

Ting Dang

Senior Lecturer, University of Melbourne

Visiting Researcher, University of Cambridge

Visiting Fellow, University of New South Wales


Google Scholar


Hiring: I am looking for proactive PhD students with a solid Computer Science or Electrical Engineering foundation. Should you be interested in exploring the expansive fields of Mobile Health, Artificial Intelligence, and Speech/Audio Processing, feel free to contact me and include your CV. The University offers full scholarships to candidates who meet the qualifications. Details can be found in opportunities.

I am a senior lecturer at the University of Melbourne, and a visiting researcher in the Department of Computer Science and Technology, University of Cambridge. Prior to this, I worked as a senior research scientist in Nokia Bell Labs (UK), senior research associate (RA) working with Professor Cecilia Mascolo at the University of Cambridge, and a RA at the University of New South Wales (UNSW), Australia. I received the BE and MEngSc degrees in Signal Processing from the Northwestern Polytechnical University, China, and the Ph.D. degree under the supervision of Dr. Vidhyasaharan Sethu and Professor Eliathamby Ambikairajah from UNSW. My primary research interests are on exploring the potential of audio signals (e.g., speech) via mobile and wearable sensing for automatic mental state (e.g., emotion, depression) prediction and disease (e.g., COVID-19) detection and monitoring. Further, my work aims to develop generalised, interpretable, and robust machine learning models to improve healthcare delivery. I served as the program committee and reviewer for over 30 top-tier journals and conferences, including AAAI, IJCAI, UbiComp, ICASSP, IEEE TAC, IEEE TASLP, JASA, JMIR, etc. I have won the ACII best paper, ICASSP top 3% paper, Asian Dean's Forum Rising Star Women In Engineering Award 2022, and IEEE Early Career Writing Retreat Grant 2019.

Research Interests:

My research interests are on human-centred audio sensing and machine learning for mobile health monitoring, which explores the potential of audio signals (e.g., speech, cough) via mobile and wearable sensing for automatic mental state prediction and disease detection and monitoring (e.g., emotion, depression, COVID-19), and develops generalised, interpretable, and robust deep learning models to improve healthcare delivery. Specifically, it includes: