Effective Clustering of Dense and Concentrated Online Communities. - Phan Nhat Hai; Hyoseop Shin (APWeb, 2010)

Adaptive combination of tag and link-based user similarity in flickr. - Phan Nhat Hai; Van Duc Thong Hoang; Hyoseop Shin (ACM Multimedia, 2010)

Moving objects: Combining gradual rules and spatio-temporal patterns. - Phan Nhat Hai; Pascal Poncelet; Maguelonne Teisseire (ICSDM, 2011)

Mining Fuzzy Moving Object Clusters. - Phan Nhat Hai; Dino Ienco; Pascal Poncelet; Maguelonne Teisseire (ADMA, 2012)

Mining time relaxed gradual moving object clusters. - Phan Nhat Hai; Dino Ienco; Pascal Poncelet; Maguelonne Teisseire (SIGSPATIAL/GIS, 2012)

GeT_Move: An Efficient and Unifying Spatio-temporal Pattern Mining Algorithm for Moving Objects. - Phan Nhat Hai; Pascal Poncelet; Maguelonne Teisseire (IDA, 2012)

How to Extract Relevant Knowledge from Tweets? - Flavien Bouillot; Phan Nhat Hai; Nicolas Béchet; Sandra Bringay; Dino Ienco; Stan Matwin; Pascal Poncelet; Mathieu Roche; Maguelonne Teisseire (ISIP, 2012)

Extracting Trajectories through an Efficient and Unifying Spatio-temporal Pattern Mining System. - Phan Nhat Hai; Dino Ienco; Pascal Poncelet; Maguelonne Teisseire (ECML/PKDD (2), 2012)

Mining Representative Movement Patterns through Compression. - Phan Nhat Hai; Dino Ienco; Pascal Poncelet; Maguelonne Teisseire (PAKDD (1), 2013)

Get_Move : fouille de données d'objets mobiles. - Phan Nhat Hai; Pascal Poncelet; Maguelonne Teisseire (Ingénierie des Systèmes d Inf., 2013)

Mining Object Movement Patterns from Trajectory Data. (Une approche unifiée pour extraire des motifs à partir de données de trajectoires). - NhatHai Phan (2013)

Analysis of Physical Activity Propagation in a Health Social Network. - NhatHai Phan; Dejing Dou; Xiao Xiao; Brigitte Piniewski; David Kil (CIKM, 2014)

Social Restricted Boltzmann Machine: Human Behavior Prediction in Health Social Networks. - NhatHai Phan; Dejing Dou; Brigitte Piniewski; David Kil (ASONAM, 2015)

Ontology-based deep learning for human behavior prediction in health social networks. - NhatHai Phan; Dejing Dou; Hao Wang 064; David Kil; Brigitte Piniewski (BCB, 2015)

Mining Multi-Relational Gradual Patterns. - NhatHai Phan; Dino Ienco; Donato Malerba; Pascal Poncelet; Maguelonne Teisseire (SDM, 2015)

Differential Privacy Preservation for Deep Auto-Encoders: an Application of Human Behavior Prediction. - NhatHai Phan; Yue Wang 009; Xintao Wu; Dejing Dou (AAAI, 2016)

Characterizing Physical Activity in a Health Social Network. - Javid Ebrahimi; NhatHai Phan; Dejing Dou; Brigitte Piniewski; David Kil (Digital Health, 2016)

Interaction Network Representations for Human Behavior Prediction. - Amnay Amimeur; NhatHai Phan; Dejing Dou; David Kil; Brigitte Piniewski (ICMLA, 2016)

Topic-Aware Physical Activity Propagation in a Health Social Network. - NhatHai Phan; Javid Ebrahimi; David Kil; Brigitte Piniewski; Dejing Dou (IEEE Intell. Syst., 2016)

All in One: Mining Multiple Movement Patterns. - NhatHai Phan; Pascal Poncelet; Maguelonne Teisseire (Int. J. Inf. Technol. Decis. Mak., 2016)

Dynamic socialized Gaussian process models for human behavior prediction in a health social network. - Yelong Shen; NhatHai Phan; Xiao Xiao; Ruoming Jin; Junfeng Sun; Brigitte Piniewski; David Kil; Dejing Dou (Knowl. Inf. Syst., 2016)

A deep learning approach for human behavior prediction with explanations in health social networks: social restricted Boltzmann machine (SRBM+). - NhatHai Phan; Dejing Dou; Brigitte Piniewski; David Kil (Soc. Netw. Anal. Min., 2016)

Topic-Aware Physical Activity Propagation with Temporal Dynamics in a Health Social Network. - NhatHai Phan; Javid Ebrahimi; David Kil; Brigitte Piniewski; Dejing Dou (ACM Trans. Intell. Syst. Technol., 2016)

Enabling Real-Time Drug Abuse Detection in Tweets. - NhatHai Phan; Soon Ae Chun; Manasi Bhole; James Geller (ICDE, 2017)

Importance Sketching of Influence Dynamics in Billion-Scale Networks. - Hung T. Nguyen 003; Tri P. Nguyen; NhatHai Phan; Thang N. Dinh (ICDM, 2017)

Adaptive Laplace Mechanism: Differential Privacy Preservation in Deep Learning. - NhatHai Phan; Xintao Wu; Han Hu 007; Dejing Dou (ICDM, 2017)

Time-Sensitive Behavior Prediction in a Health Social Network. - Amnay Amimeur; NhatHai Phan; Dejing Dou; David Kil; Brigitte Piniewski (ICMLA, 2017)

Ontology-based deep learning for human behavior prediction with explanations in health social networks. - NhatHai Phan; Dejing Dou; Hao Wang 064; David Kil; Brigitte Piniewski (Inf. Sci., 2017)

Preserving differential privacy in convolutional deep belief networks. - NhatHai Phan; Xintao Wu; Dejing Dou (Mach. Learn., 2017)

Deep Self-Taught Learning for Detecting Drug Abuse Risk Behavior in Tweets. - Han Hu 007; NhatHai Phan; James Geller; Huy T. Vo; Manasi Bhole; Xueqi Huang; Sophie Di Lorio; Thang Dinh; Soon Ae Chun (CSoNet, 2018)

Deep Learning Model for Classifying Drug Abuse Risk Behavior in Tweets. - Han Hu 007; Pranavi Moturu; Kannan Dharan; James Geller; Sophie Iorio; Hai Phan 001; Huy T. Vo; Soon Ae Chun (ICHI, 2018)

Recursive Structure Similarity: A Novel Algorithm for Graph Clustering. - Yixin Fang; Ruoming Jin; Wei Xiong; Xiaoning Qian; Dejing Dou; Hai Phan 001 (ICTAI, 2018)

DPNE: Differentially Private Network Embedding. - Depeng Xu 001; Shuhan Yuan; Xintao Wu; NhatHai Phan (PAKDD (2), 2018)

A 3D Atrous Convolutional Long Short-Term Memory Network for Background Subtraction. - Zhihang Hu; Turki Turki; NhatHai Phan; Jason T. L. Wang (IEEE Access, 2018)

Improving Object Detection from Scratch via Gated Feature Reuse. - Zhiqiang Shen; Honghui Shi; Jiahui Yu; Hai Phan 001; Rogério Feris; Liangliang Cao; Ding Liu 001; Xinchao Wang; Thomas S. Huang; Marios Savvides (BMVC, 2019)

Limiting the Neighborhood: De-Small-World Network for Outbreak Prevention. - Ruoming Jin; Yelong Sheng; Lin Liu 001; Xue-wen Chen 001; NhatHai Phan (CSoNet, 2019)

Scalable Self-taught Deep-Embedded Learning Framework for Drug Abuse Spatial Behaviors Detection. - Wuji Liu; Xinyue Ye; Hai Phan 001; Han Hu 007 (CSoNet, 2019)

DrugTracker: A Community-focused Drug Abuse Monitoring and Supporting System using Social Media and Geospatial Data (Demo Paper). - Han Hu 007; NhatHai Phan; Xinyue Ye; Ruoming Jin; Kele Ding; Dejing Dou; Huy T. Vo (SIGSPATIAL/GIS, 2019)

Heterogeneous Gaussian Mechanism: Preserving Differential Privacy in Deep Learning with Provable Robustness. - NhatHai Phan; Minh N. Vu; Yang Liu; Ruoming Jin; Dejing Dou; Xintao Wu; My T. Thai (IJCAI, 2019)

An Ensemble Deep Learning Model for Drug Abuse Detection in Sparse Twitter-Sphere. - Han Hu 007; NhatHai Phan; James Geller; Stephen Iezzi; Huy T. Vo; Dejing Dou; Soon Ae Chun (MedInfo, 2019)

Extracting API tips from developer question and answer websites. - Shaohua Wang 002; NhatHai Phan; Yan Wang 014; Yong Zhao (MSR, 2019)

Preserving Differential Privacy in Adversarial Learning with Provable Robustness. - NhatHai Phan; Ruoming Jin; My T. Thai; Han Hu 007; Dejing Dou (CoRR, 2019)

Evaluating Explainers via Perturbation. - Minh N. Vu; Truc D. T. Nguyen; NhatHai Phan; Ralucca Gera; My T. Thai (CoRR, 2019)

Binarizing MobileNet via Evolution-Based Searching. - Hai Phan 001; Zechun Liu; Dang Huynh; Marios Savvides; Kwang-Ting Cheng; Zhiqiang Shen (CVPR, 2020)

Scalable Differential Privacy with Certified Robustness in Adversarial Learning. - NhatHai Phan; My T. Thai; Han Hu 007; Ruoming Jin; Tong Sun 005; Dejing Dou (ICML, 2020)

Ontology-based Interpretable Machine Learning for Textual Data. - Phung Lai; NhatHai Phan; Han Hu 007; Anuja Badeti; David Newman; Dejing Dou (IJCNN, 2020)

MoBiNet: A Mobile Binary Network for Image Classification. - Hai Phan 001; Dang Huynh; Yihui He; Marios Savvides; Zhiqiang Shen (WACV, 2020)

Classification of Ecological Data by Deep Learning. - Shaobo Liu; Frank Y. Shih; Gareth Russell; Kimberly Russell; Hai Phan 001 (Int. J. Pattern Recognit. Artif. Intell., 2020)

A Synergetic Attack against Neural Network Classifiers combining Backdoor and Adversarial Examples. - Guanxiong Liu; Issa Khalil; Abdallah Khreishah; NhatHai Phan (IEEE BigData, 2021)

c-Eval: A Unified Metric to Evaluate Feature-based Explanations via Perturbation. - Minh N. Vu; Truc D. T. Nguyen; NhatHai Phan; Ralucca Gera; My T. Thai (IEEE BigData, 2021)

Social and Motivational Factors for the Spread of Physical Activities in a Health Social Network. - NhatHai Phan; David Kil; Brigitte Piniewski; Dejing Dou (CSoNet, 2021)

Continual Learning with Differential Privacy. - Pradnya Desai; Phung Lai; NhatHai Phan; My T. Thai (ICONIP (6), 2021)

FLSys: Toward an Open Ecosystem for Federated Learning Mobile Apps. - Han Hu 007; Xiaopeng Jiang; Vijaya Datta Mayyuri; An M. Chen; Devu M. Shila; Adriaan Larmuseau; Ruoming Jin; Cristian Borcea; NhatHai Phan (CoRR, 2021)

User-Entity Differential Privacy in Learning Natural Language Models. - Phung Lai; NhatHai Phan; Tong Sun 005; Rajiv Jain; Franck Dernoncourt; Jiuxiang Gu; Nikolaos Barmpalios (IEEE Big Data, 2022)

Heterogeneous Randomized Response for Differential Privacy in Graph Neural Networks. - Khang Tran; Phung Lai; NhatHai Phan; Issa Khalil; Yao Ma 001; Abdallah Khreishah; My T. Thai; Xintao Wu (IEEE Big Data, 2022)

Lifelong DP: Consistently Bounded Differential Privacy in Lifelong Machine Learning. - Phung Lai; Han Hu 007; Hai Phan 001; Ruoming Jin; My T. Thai; An M. Chen (CoLLAs, 2022)

Un-Fair Trojan: Targeted Backdoor Attacks Against Model Fairness. - Nicholas Furth; Abdallah Khreishah; Guanxiong Liu; NhatHai Phan; Yaser Jararweh (SDS, 2022)

Model Transferring Attacks to Backdoor HyperNetwork in Personalized Federated Learning. - Phung Lai; NhatHai Phan; Abdallah Khreishah; Issa Khalil; Xintao Wu (CoRR, 2022)

OnML: an ontology-based approach for interpretable machine learning. - Pelin Ayranci; Phung Lai; NhatHai Phan; Han Hu 007; Alexander Kolinowski; David Newman; Deijing Dou (J. Comb. Optim., 2022)

XRand: Differentially Private Defense against Explanation-Guided Attacks. - Truc D. T. Nguyen; Phung Lai; Hai Phan 001; My T. Thai (AAAI, 2023)

Active Membership Inference Attack under Local Differential Privacy in Federated Learning. - Truc D. T. Nguyen; Phung Lai; Khang Tran; NhatHai Phan; My T. Thai (AISTATS, 2023)

Differential Privacy in HyperNetworks for Personalized Federated Learning. - Vaisnavi Nemala; Phung Lai; NhatHai Phan (CIKM, 2023)

Zone-based Federated Learning for Mobile Sensing Data. - Xiaopeng Jiang; Thinh On; NhatHai Phan; Hessamaldin Mohammadi; Vijaya Datta Mayyuri; An M. Chen; Ruoming Jin; Cristian Borcea (PERCOM, 2023)

FairDP: Certified Fairness with Differential Privacy. - Khang Tran; Ferdinando Fioretto; Issa Khalil; My T. Thai; NhatHai Phan (CoRR, 2023)

PromSec: Prompt Optimization for Secure Generation of Functional Source Code with Large Language Models (LLMs). - Mahmoud Nazzal; Issa Khalil; Abdallah Khreishah; NhatHai Phan (CCS, 2024)

Demo: SGCode: A Flexible Prompt-Optimizing System for Secure Generation of Code. - Khiem Ton; Nhi Nguyen; Mahmoud Nazzal; Abdallah Khreishah; Cristian Borcea; NhatHai Phan; Ruoming Jin; Issa Khalil; Yelong Shen (CCS, 2024)

Multi-Instance Adversarial Attack on GNN-Based Malicious Domain Detection. - Mahmoud Nazzal; Issa Khalil; Abdallah Khreishah; NhatHai Phan; Yao Ma 001 (SP, 2024)

FLSys: Toward an Open Ecosystem for Federated Learning Mobile Apps. - Xiaopeng Jiang; Han Hu 007; Thinh On; Phung Lai; Vijaya Datta Mayyuri; An M. Chen; Devu M. Shila; Adriaan Larmuseau; Ruoming Jin; Cristian Borcea; NhatHai Phan (IEEE Trans. Mob. Comput., 2024)

FairDP: Achieving Fairness Certification with Differential Privacy. - Khang Tran; Ferdinando Fioretto; Issa Khalil; My T. Thai; Linh Thi Xuan Phan; NhatHai Phan (SaTML, 2025)

A Novel Adaptive Data Transformation for Contrastive Learning. - Yucong Shen; Hai Phan 001; Frank Y. Shih (Int. J. Pattern Recognit. Artif. Intell., 2025)

Operationalizing a Threat Model for Red-Teaming Large Language Models (LLMs). - Apurv Verma; Satyapriya Krishna; Sebastian Gehrmann; Madhavan Seshadri; Anu Pradhan; John A. Doucette; David Rabinowitz; Leslie Barrett; Tom Ault; Hai Phan 001 (Trans. Mach. Learn. Res., 2025)

Knowledge Consultation for Semi-Supervised Semantic Segmentation. - Thuan Than; Nhat-Anh Nguyen-Dang; Dung Nguyen; Salwa K. Al Khatib; Ahmed Elhagry; Hai Phan 001; Yihui He; Zhiqiang Shen; Marios Savvides; Dang Huynh (CoRR, 2025)

FedX: Adaptive Model Decomposition and Quantization for IoT Federated Learning. - Phung Lai; Xiaopeng Jiang; Hai Phan 001; Cristian Borcea; Khang Tran; An M. Chen; Vijaya Datta Mayyuri; Ruoming Jin (CoRR, 2025)

A Client-level Assessment of Collaborative Backdoor Poisoning in Non-IID Federated Learning. - Phung Lai; Guanxiong Liu; NhatHai Phan; Issa Khalil; Abdallah Khreishah; Xintao Wu (CoRR, 2025)

Watermarking Degrades Alignment in Language Models: Analysis and Mitigation. - Apurv Verma; NhatHai Phan; Shubhendu Trivedi (CoRR, 2025)

SoK: Are Watermarks in LLMs Ready for Deployment? - Kieu Dang; Phung Lai; NhatHai Phan; Yelong Shen; Ruoming Jin; Abdallah Khreishah; My T. Thai (CoRR, 2025)

ViGText: Deepfake Image Detection with Vision-Language Model Explanations and Graph Neural Networks. - Ahmad Albarqawi; Mahmoud Nazzal; Issa Khalil; Abdallah Khreishah; NhatHai Phan (CoRR, 2025)

FedChip: Federated LLM for Artificial Intelligence Accelerator Chip Design. - Mahmoud Nazzal; Khoa Nguyen; Deepak Vungarala; Ramtin Zand; Shaahin Angizi; NhatHai Phan; Abdallah Khreishah (CoRR, 2025)