H. Jia, Y. Kwon, A. Orsino, T. Dang, D. Talia, and C. Mascolo

TinyTTA: Efficient Test-time Adaptation via Early-exit Ensembles on Edge Devices

NeurIPS 2024

X. Wang, T. Dang, V. Kostakos, and H. Jia

Efficient and Personalized Mobile Health Event Prediction via Small Language Models

MobiCom Workshop EIFCom 2024

J. Wu, T. Dang, V. Sethu, and E. Ambikairajah

Emotion Recognition Systems Must Embrace Ambiguity

ACII Satellite Workshop EASE 2024

Y. Wu, T. Dang, D. Spathis, H. Jia, C. Mascolo

StatioCL: Contrastive Learning for Time Series via Non-Stationary and Temporal Contrast

ACM International Conference on Information and Knowledge Management (CIKM) 2024

Y. Hu, S. Zhang, T. Dang, H. Jia, FD. Salim, W. Hu, and AJ. Quigley

Exploring Large-Scale Language Models to Evaluate EEG-Based Multimodal Data for Mental Health

UbiComp Workshop WellComp 2024

J. Wu, T. Dang, V. Sethu, and E. Ambikairajah

Dual-Constrained Dynamical Neural ODEs for Ambiguity-aware Continuous Emotion Prediction

INTERSPEECH 2024

I. Shahid, K. Al-Naimi, T Dang, Y. Liu, F. Kawsar, A. Montanari

Towards Enabling DPOAE Estimation on Single-Speaker Earbuds

ICASSP 2024

Z. Nan, T. Dang, V. Sethu, B. Ahmed

Variational connectionist temporal classification for order-preserving sequence modeling

ICASSP 2024

J. Romero, A. Ferlini, D. Spathis, T. Dang, K. Farrahi, F. Kawsar, A. Montanari

OptiBreathe: An Earable-based PPG System for Continuous Respiration Rate, Breathing Phase, and Tidal Volume Monitoring

HotMobile 2024

T. Xia, T. Dang, J. Han, L. Qendro, C. Mascolo

Uncertainty-aware Health Diagnostics via Class-balanced Evidential Deep Learning

IEEE Journal of Biomedical and Health Informatics

D. Ma, T. Dang, M. Ding, R. Balan

ClearSpeech: Improving Voice Quality of Earbuds Using Both In-Ear and Out-Ear Microphones

UbiComp, 2024

BU. Demirel, T. Dang, K. Al-Naimi, F. Kawsar, A. Montanari

Unobtrusive Air Leakage Estimation for Earables with In-ear Microphones

UbiComp, 2024

J. Wu, T. Dang, V. Sethu, and E. Ambikairajah

Belief Mismatch Coefficient (BMC): A Novel Interpretable Measure of Prediction Accuracy for Ambiguous Emotion States.

Affective Computing and Intelligent Interaction (ACII), 2023.

🏆 Best paper award

T. Dang, A. Ghosh, D. Spathis, C. Mascolo

Human-centered AI for mobile health sensing: challenges and opportunities

Royal Society Open Science

2023

Special selection

T. Dang, J. Han*, T. Xia*, E. Bondareva, C. Brown, J. Chauhan, A. Grammenos, D. Spathis, P. Cicuta, and C. Mascolo

Conditional Neural ODE Processes for Individual Disease Progression Forecasting: A Case Study on COVID-19

ACM SIGKDD on Knowledge Discovery and Data Mining (KDD) 2023.

[Promotion video]

K. Butkow, T. Dang, A. Ferlini, D. Ma, and C. Mascolo

hEARt: Motion-resilient Heart Rate Monitoring with In-ear Microphones

IEEE International Conference on Pervasive Computing and Communications (PerCom) 2023

B. Wickramasinghe, E. Ambikairajah, V. Sethu, J. Epps, H. Li, T. Dang

EDNN controlled adaptive front-end for replay attack detection systems

Speech Communication

154, 102973, 2023.

J. Wu, T. Dang, V. Sethu, E. Ambikairajah.

From Interval to Ordinal: A HMM based Approach for Emotion Label Conversion

Interspeech 2023

Dang, T., Dimitriadis, A., Wu, J., Sethu, V., and Ambikairajah, E.

Constrained dynamical neural ode for time series modelling: A case study on continuous emotion prediction.

ICASSP, 2023.

[Poster]

🏆 Top 3% paper award

J. Han, M. Montagna, A. Grammenos, T. Xia, E. Bondareva, C. Brown, J. Chauhan, T. Dang, D. Spathis, A. Floto, P. Cicuta, and C. Mascolo.

Evaluating Listening Performance for COVID-19 Detection between Clinicians and Machine Learning: A Comparative Study

Journal of Medical Internet Research, 2023

J. Wu, T. Dang, V. Sethu, and E. Ambikairajah.

Multimodal Affect Models: An investigation of relative salience of audio and visual cues for emotion prediction

Frontiers in Computer Science

2021.

C. Hu, X. Ma, D. Ma, T. Dang

Lightweight and Non-invasive User Authentication on Earables

HotMobile 2023

T. Dang, J. Han, T. Xia, D. Spathis, E. Bondareva, C. Brown, J. Chauhan, A. Grammenos, A. Hasthanasombat, A. Floto, P. Cicuta, and C. Mascolo.

Exploring longitudinal cough, breath, and voice data for COVID-19 progression prediction via sequential deep learning: model development and validation.

Journal of Medical Internet Research, 2023

Media Coverage

T. Xia, J. Han, L. Qendro, T. Dang, and C. Mascolo.

Hybrid-EDL: Improving Evidential Deep Learning for Uncertainty Quantification on Imbalanced Data

NeurIPS Workshop TSRML 2022

T. Dang, T. Quinnell, and C. Mascolo.

Exploring Semi-supervised Learning for Audio-based COVID-19 Detection using FixMatch

INTERSPEECH 2022

J. Wu, T. Dang, V. Sethu, J. Epps, E. Ambikairajah.

A Novel Sequential Monte Carlo Framework for Predicting Ambiguous Emotion States

ICASSP 2022

Han, J., Xia, T., Spathis, D., Bondareva, E., Brown, C., Chauhan, J., Dang, T., Grammenos, A., Hasthanasombat, A., Floto, A. and Cicuta, P., Mascolo, C.

Sounds of COVID-19: exploring realistic performance of audio-based digital testing.

NPJ digital medicine, 2022

Media Coverage

Xia, T., Spathis, D., Ch, J., Grammenos, A., Han, J., Hasthanasombat, A., Bondareva, E., Dang, T., Floto, A., Cicuta, P. and Mascolo, C.

COVID-19 Sounds: A Large-Scale Audio Dataset for Digital COVID-19 Detection

NeurIPS Datasets and Benchmarks Track, 2021

T. Xia, J. Han, L. Qendro, T. Dang, and C. Mascolo

Uncertainty-Aware COVID-19 Detection from Imbalanced Sound Data

Interspeech 2021

D. B., T. Dang, V. Sethu, E. Ambikairajah, and S. Fernando

A Novel Bag-of-Optimised-Clusters Front-End for Speech based Continuous Emotion Prediction

Affective Computing and Intelligent Interaction(ACII), 2019

A. Ouyang, T. Dang, V. Sethu, and E. Ambikairajah

Speech Based Emotion Prediction: Can a Linear Model Work?

Interspeech 2019

T. Dang, V. Sethu, and E. Ambikairajah

Compensation techniques for speaker variability in continuous emotion prediction

IEEE Transaction on Affective Computing

2018.

T. Dang, V. Sethu, and E. Ambikairajah

Dynamic multi-rater Gaussian Mixture Regression incorporating temporal dependencies of emotion uncertainty using kalman filters

ICASSP 2018

T. Dang, V. Sethu, J. Epps, and E. Ambikairajah

An investigation of Emotion Prediction Uncertainty Using Gaussian Mixture Regression

Interspeech 2017

T. Dang, B. Stasak, Z. Huang, S. Jayawardena, M. Atcheson, M. Hayat, P. Le, V. Sethu, R. Goecke, and J. Epps

Investigating Word affect Features and Fusion of Probabilistic Predictions Incorporating Uncertainty in AVEC 2017

the 7th Annual Workshop on Audio/Visual Emotion Challenge, ACM Multimedia, 2017

T. Dang, V. Sethu, and E. Ambikairajah

Factor Analysis Based Speaker Normalisation for Continuous Emotion Prediction

Interspeech 2016

Z. Huang, B. Stasak, T. Dang, K. Wataraka Gamage, P. Le, V. Sethu, and J. Epps

Staircase Regression in OA RVM, Data Selection and Gender Dependency in AVEC 2016

In Proceedings of the 6th International Workshop on Audio/Visual Emotion Challenge, ACM Multimedia, 2015

Z. Huang, T. Dang, N. Cummins, B. Stasak, P. Le, V. Sethu, and J. Epps

An investigation of annotation delay compensation and output-associative fusion for multi-modal continuous emotion prediction

the 5th International Workshop on Audio/Visual Emotion Challenge, ACM Multimedia, 2015