Ting Dang
Senior Lecturer, The University of Melbourne
ting.dang@unimelb.edu.au
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Mobile Health - Audio and Speech Processing
Deep Learning - Affective Computing - Time Series Modelling
CV
About Me
I am a Senior Lecturer at the University of Melbourne. Previously, I served as a Senior Research Scientist at Nokia Bell Labs in the UK, a Senior Research Associate at the University of Cambridge, and a Research Associate at the University of New South Wales (UNSW), Australia, where I also earned my Ph.D. My research primarily focuses on human-centered AI and sensing for health delivery. Specifically, I develop AI models that leverage audio signals (such as speech and breathing) and physiological signals (like PPG and EEG) through mobile and wearable sensing to detect and monitor health conditions. I am serving as the Editor for IEEE Pervasive Computing and Elsevier Computer Speech and Language, an Area Chair for ICASSP and Senior PC for AAAI.
Research Interests
- Machine learning in mobile health: Pioneering the development of machine learning algorithms tailored for diverse health applications, aimed at enhancing the reliability and effectiveness of ML in screening, diagnosis, and monitoring.
- Speech and Audio Processing: Investigating advanced signal processing and machine learning techniques for speech and related applications.
- Time Series Modelling: Enhancing representation learning for time series in real-world challenges.
- Trustworthy Deep Learning (DL): Improving the interpretability and generalization of DL models for more reliable health outcome predictions.
- Wearable Sensing: Examining novel sensing opportunities for health monitoring using new forms of resource-constrained IoT wearable devices.
Opportunities
Seeking motivated PhD students to join our team!
- Send your CV, transcripts, and a short research proposal aligning with our expertise.
- CSC students and visiting scholars with relevant backgrounds are also welcome.
News
2026/03: One paper titled "Multi-Scale Diffusion for Bio-topological Representation Learning on Multimodal Brain Graphs" accepted by ACM Transactions on Intelligent Systems and Technology.
2026/01: Five papers accepted at ICASSP 2026.
2025/11: Call for Papers: "Post-Training of Speech Foundation Models" and "Child Home Interaction & Language Dynamics: Speech, Psychology, Affect, Computation & Environments " at INTERSPEECH 2026 Special Sessions.
2025/11: Awarded Google Fund for "Benchmarking Auditory Cognitive Reasoning in Audio-Language Models".
2025/11: Joined Editorial Board of IEEE Transactions on Affective Computing.
2025/09: Two papers and two workshop papers accepted at NeurIPS 2025.
2025/09: One paper accepted by SenSys 2026, titled 'From Cheap to Chic: Enhancing Music Playback Quality of Budget Earphones via Hardware-Aware Learning'.
2025/09: One paper accepted by IEEE Transactions on Affective Computing, titled 'How many raters do we need? Analyses of uncertainty in estimating ambiguity-aware emotion labels'.
2025/09: One paper accepted by ACM Transactions on Computing for Healthcare, titled 'Data-Efficient Psychiatric Disorder Detection via Self-supervised Learning on Frequency-enhanced Brain Networks'.
2025/08: Shortlisted as the Finalist for the Rising Star (Academics) STEM Women in Color Award 2025.
2025/08: Two papers accepted at APSIPA ASC 2025.
2025/08: One paper accepted at ACII LBR Track titled 'Beyond Scale: Small Language Models are Comparable to GPT-4 in Mental Health Understanding'.
2025/07: Senior PC of AAAI 2026.
2025/07: Two papers accepted at UbiComp/ISWC 2025 workshops.
2025/06: Call for papers: ESPRESSO: Special Session on Scalable and Efficient Signal Processing for Multimodal AI Systems at APSIPA ASC 2025.
2025/05: Two papers accepted at INTERSPEECH 2025.
2025/04: Joined the Editorial Board of Computer Speech and Language.
2025/04: One paper titled 'Speech Emotion Recognition Via CNN Transforemr and Multidimensional Attention Mechanism' is accepted by Speech Communication.
2025/04: Call for papers: Special Issue on State of the Art in Wearable Sensors for Health Monitoring @ Sensors
2025/03: Two US patents are granted.
2025/02: One paper titled 'SQUIREDL: Sparse Sequence-to-Sequence Uncertainty Estimation in Evidential Deep Learning' is accepted by ACM Transactions on Computing for Healthcare.
2024/12: Two papers are accepted by IEEE ICASSP 2025.
2024/12: One US patent titled 'Cancellation of Ultrasonic Signals' is granted.
2024/11: One paper titled 'Multimodal Large Language Models in Human-centered Health: Practical Insights' is accepted by IEEE Pervasive Computing.
2024/10: Served as the Area Chair for ICASSP 2024.
2024/09:One paper titled 'TinyTTA: Efficient Test-time Adaptation via Early-exit Ensembles on Edge Devices' is accepted by NeurIPS 2024.
2024/09: One paper titled 'Efficient and Personalized Mobile Health Event Prediction via Small Language Models' is accepted by MobiCom Workshop EIFCom 2024.
2024/08: Call for Papers: Workshop on Multi-Biological Sensing Data for Speech and Language Deterioration Prediction ACM MM Asia.
2024/07: One paper titled 'StatioCL: Contrastive Learning for Time Series via Non-Stationary and Temporal Contrast' is accepted by CIKM 2024.
2024/07: One paper titled 'Emotion Recognition Systems Must Embrace Ambiguity' is accepted by ACII Satellite Workshop EASE 2024.
2024/07: One paper titled 'Exploring Large-Scale Language Models to Evaluate EEG-Based Multimodal Data for Mental Health' is accepted by UbiComp Workshop WellComp 2024.
2024/07: Invited talk at University of New South Wales and University of Sydney.
2024/06: One paper titled 'Dual-Constrained Dynamical Neural ODEs for Ambiguity-aware Continuous Emotion Prediction' is accepted by Interspeech 2024.
2024/05: Joined the Editorial Board of IEEE Pervasive Computing.
2024/04: Co-organizing WellComp workshop at UbiComp 2024.
2024/03: Co-charing industry perspectives at MobileHCI 2024.
2024/03: One paper titled "An evaluation of heart rate monitoring with in-ear microphones under motion" is accepted by Pervasive and Mobile Computing.
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).
2023/10: One review paper titled "Human-centered AI for mobile health sensing: challenges and opportunities" is accepted by Royal Society Open Science!
2023/09: Best paper award from ACII 2023!
2023: Papers accepted by INTERSPEECH, ICASSP, ACII, KDD, IMWUT, JMIR, Speech Communication, etc!