AIMS Lab
Human-Centered AI for Health Modeling and Sensing
Advancing AI for speech, audio, and physiological sensing in mobile and ubiquitous health.
Advancing AI for speech, audio, and physiological sensing in mobile and ubiquitous health.
The AIMS (Human-Centered AI for Health Modeling and Sensing) Lab is based at the University of Melbourne and is led by Dr. Ting Dang. Our team focuses on human-centered AI and sensing for health delivery. We develop AI models that leverage audio signals (such as speech and breathing) and physiological signals (like PPG and EEG), together with other ubiquitous and wearable sensing data, to detect and monitor health conditions. The lab collaborates closely with clinicians, industry, and interdisciplinary partners to translate algorithms into real-world impact.
Ting Dang is currently a Senior Lecturer at the University of Melbourne, actively leading research at the intersection of human-centered artificial intelligence and health sensing. Previously, she was 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), where she also earned her Ph.D.
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!