Twitter data clustering and visualization. - Andrei Sechelea; Tien Do Huu; Evangelos Zimos; Nikos Deligiannis (ICT, 2016)

Multiview Deep Learning for Predicting Twitter Users' Location. - Tien Huu Do; Duc Minh Nguyen; Evaggelia Tsiligianni; Bruno Cornelis; Nikos Deligiannis (CoRR, 2017)

Twitter User Geolocation Using Deep Multiview Learning. - Tien Huu Do; Duc Minh Nguyen; Evaggelia Tsiligianni; Bruno Cornelis; Nikos Deligiannis (ICASSP, 2018)

Twitter data analysis for studying communities of practice in the media industry. - Marlen Komorowski; Tien Do Huu; Nikos Deligiannis (Telematics Informatics, 2018)

Rumour Detection Via News Propagation Dynamics and User Representation Learning. - Tien Huu Do; Xiao Luo; Duc Minh Nguyen; Nikos Deligiannis (DSW, 2019)

Matrix Completion with Variational Graph Autoencoders: Application in Hyperlocal Air Quality Inference. - Tien Huu Do; Duc Minh Nguyen; Evaggelia Tsiligianni; Angel Lopez Aguirre; Valerio Panzica La Manna; Frank J. Pasveer; Wilfried Philips; Nikos Deligiannis (ICASSP, 2019)

BRUBIKE: A Dataset of Bicycle Traffic and Weather Conditions for Predicting Cycling Flow. - Steven Vanden Broucke; Luis Manuel Vidal Piña; Tien Huu Do; Nikos Deligiannis (ISC2, 2019)

Fake News Detection using Deep Markov Random Fields. - Duc Minh Nguyen; Tien Huu Do; A. Robert Calderbank; Nikos Deligiannis (NAACL-HLT (1), 2019)

Context-Based Analysis of Urban Air Quality Using an Opportunistic Mobile Sensor Network. - Xuening Qin; Ljiljana Platisa; Tien Huu Do; Evaggelia Tsiligianni; Jelle Hofman; Valerio Panzica La Manna; Nikos Deligiannis; Wilfried Philips (SmartCity360°, 2019)

Graph Auto-Encoder for Graph Signal Denoising. - Tien Huu Do; Duc Minh Nguyen; Nikos Deligiannis (ICASSP, 2020)

Spatiotemporal Air Quality Inference of Low-Cost Sensor Data; Application on a Cycling Monitoring Network. - Jelle Hofman; Tien Huu Do; Xuening Qin; Esther Rodrigo Bonet; Martha E. Nikolaou; Wilfried Philips; Nikos Deligiannis; Valerio Panzica La Manna (ICPR Workshops (6), 2020)

Mapping Air Quality in IoT Cities: Cloud Calibration and Air Quality Inference of Sensor Data. - Jelle Hofman; Martha E. Nikolaou; Tien Huu Do; Xuening Qin; Esther Rodrigo Bonet; Wilfried Philips; Nikos Deligiannis; Valerio Panzica La Manna (IEEE SENSORS, 2020)

Graph-Deep-Learning-Based Inference of Fine-Grained Air Quality From Mobile IoT Sensors. - Tien Huu Do; Evaggelia Tsiligianni; Xuening Qin; Jelle Hofman; Valerio Panzica La Manna; Wilfried Philips; Nikos Deligiannis (IEEE Internet Things J., 2020)

Street-level Air Quality Inference Based on Geographically Context-aware Random Forest Using Opportunistic Mobile Sensor Network. - Xuening Qin; Tien Huu Do; Jelle Hofman; Esther Rodrigo Bonet; Valerio Panzica La Manna; Nikos Deligiannis; Wilfried Philips (ICIAI, 2021)

Context-Aware Deep Markov Random Fields for Fake News Detection. - Tien Huu Do; Marc Berneman; Jasabanta Patro; Giannis Bekoulis; Nikos Deligiannis (IEEE Access, 2021)

Graph convolutional neural networks with node transition probability-based message passing and DropNode regularization. - Tien Huu Do; Duc Minh Nguyen; Giannis Bekoulis; Adrian Munteanu 001; Nikos Deligiannis (Expert Syst. Appl., 2021)

Conditional Variational Graph Autoencoder for Air Quality Forecasting. - Esther Rodrigo Bonet; Tien Huu Do; Xuening Qin; Jelle Hofman; Valerio Panzica La Manna; Wilfried Philips; Nikos Deligiannis (EUSIPCO, 2022)

Spatiotemporal air quality inference of low-cost sensor data: Evidence from multiple sensor testbeds. - Jelle Hofman; Tien Huu Do; Xuening Qin; Esther Rodrigo Bonet; Wilfried Philips; Nikos Deligiannis; Valerio Panzica La Manna (Environ. Model. Softw., 2022)

Fine-Grained Urban Air Quality Mapping from Sparse Mobile Air Pollution Measurements and Dense Traffic Density. - Xuening Qin; Tien Huu Do; Jelle Hofman; Esther Rodrigo Bonet; Valerio Panzica La Manna; Nikos Deligiannis; Wilfried Philips (Remote. Sens., 2022)

Explaining Graph Neural Networks With Topology-Aware Node Selection: Application in Air Quality Inference. - Esther Rodrigo Bonet; Tien Huu Do; Xuening Qin; Jelle Hofman; Valerio Panzica La Manna; Wilfried Philips; Nikos Deligiannis (IEEE Trans. Signal Inf. Process. over Networks, 2022)

Deep Learning-based Prediction of Clinical Trial Enrollment with Uncertainty Estimates. - Tien Huu Do; Antoine Masquelier; Nae Eoun Lee; Jonathan Crowther (CoRR, 2025)