Home » AI Researchs » Research Team » Intelligent Communication Networks

Introduction

Today, with many IoT devices and the development of Internet technologies, both wired and wireless connectivity play a crucial role in offering a wide range of services to end-users. Moreover, such communication and networking technologies have influenced individuals, institutions, governments, and industries. As a result, communication technologies have become an indispensable part of daily life. Recently, Machine Learning (ML) technologies have achieved breakthrough advances. When combined with communication technologies, the achievement in AI has created unique applications such as smart cities, self-driving cars, etc.

Our research group focuses on the study and development of high-speed, dependable, and flexible networking technologies, using theoretical and practical techniques to incorporate social, information, device, and energy factors. We study to leverage AI in enhancing and optimizing network performance. We’re also looking into solutions for analyzing and mining data collected by IoT devices. See the slides here for more detail.

Contact: Dr. Nguyen Phi Le, Email: lenp@soict.hust.edu.vn

Group website: http://icn.bkai.ai/

Research Directions

  • Network optimization: Exploiting machine learning, deep learning, reinforcement learning, meta-heurisctic techniques to optimize network performance.
  • Data mining in IoT networks: Focusing on processing, analyzing and mining data collected from IoT devices.
  • AI in networking: Applying various machine learning and deep learning techniques including graph networks, deep reinforcement learning, etc., to analyze and predict the network behavior. Leveraging AI in controlling network operations.
  • Distributed systems: Addressing different problems in distributed systems such as Synchronization, Replication and Consistency, Fault tolerance, etc.
  • New generation network: Solving problems of NGN in expanding the existing access network infrastructure into networks capable of satisfying the user’s requirements.
  • QoS-QoE: Proposing adaptive mechanisms to predict and optimize QoS/QoE in network systems.
  • Internet of Things: Addressing different issues of IoT systems such as security problems, lack of regulation, limited bandwidth, etc.

Research problems

  • Optimization problems in Wireless Rechargeable Sensor Networks: We focus on a new wireless charging paradigm that considers a variety of factors such as charging path, charging time, target coverage, and connectivity. Furthermore, our system considers various optimization goals, including minimizing the number of mobile chargers, optimizing the depot placement, and extending the network lifetime. To solve the problem, we go from theoretical modeling to applying state-of-the-art technologies. Specifically, we leverage reinforcement learning and deep reinforcement learning, fuzzy logic, genetic algorithms to propose novel charging algorithms for wireless rechargeable IoT networks.
  • Mobile air quality monitoring network: This research topic, part of the VinIF-funded Fi-Mi project (http://fi-mi.vn), presents a new mobile air quality monitoring network based on vehicle-mounted sensors. We explore various research issues, such as resource allocation, effective communication, data analysis, and data mining. The resource allocation problem is solved using optimization techniques such as reinforcement learning, fuzzy logic, and meta-heuristics. A mathematical model for opportunistic communication in mobile air quality monitoring networks is also proposed. We then leverage deep reinforcement learning for offloading data from devices to the servers. Finally, we use machine learning methodologies to calibrate the acquired data and propose deep learning models for spatiotemporal prediction problems.
  • Satellite precipitation calibration: We investigate a fascinating research problem that is how to calibrate the satellite precipitation data. Our method uses deep learning techniques to blend satellite data that is fine-grained but inaccurate with the coarse-but-accurate data from ground-based monitoring stations. We then leverage graph neural networks to model the spatial correlation between the ground-based monitoring stations. Besides, recurrent neural networks are utilized to capture the data’s temporal properties.
  • Prediction of water levels on rivers in Vietnam: This study focuses on data mining regarding river discharge and water levels in Vietnam. For hydrological research and flood prediction, forecasting river discharge and water levels have long been necessary. However, existing machine learning-based methods cope with severe flaws such as a lack of training data, noise in the obtained data, and the difficulty of altering the model’s hyper-parameters. In this research, we address at the same time these three challenges. Specifically, we apply data preprocessing techniques such as SSA to clean the data before feeding it into the forecasting models. Furthermore, we propose novel deep learning models that employ ensemble learning techniques and graph neural networks to capture both temporal and spatial correlation and extract relevant information from historical data. Furthermore, optimization techniques like metaheuristics are used to obtain the optimal hyper-parameters automatically.
  • Traffic prediction and intelligent routing: In this research, we study how to learn and predict networks’ future behavior dynamically. From that, we design algorithms to control the network operations efficiently and intelligently. Several research problems are taking into account, such as exploiting the Graph Neural Networks to capture the spatial relation of the network and then leveraging deep learning to predict the network traffic; using reinforcement learning to guide the packets; utilizing metaheuristic algorithms and linear programming to optimize the routing paths. We perform experiments on network simulators such as OMNET, NS2, and real datasets such as Brain, Abilene, and Geant.
  • Applying ML to Software-Defined Network =>  Knowledge-defined Network: Applying AI to the management of computer networks, making it to be a self-adaptive one. This means every network node will be an AI node, which is able to make decisions automatically. However, these network nodes have only a local view and a local control, hence, applying Artificial Intelligence to each network node is not trivial. For this purpose, a centralized control architecture, e.g. Software-defined Network (SDN), is a promising candidate. In this work, we decide to develop a knowledge layer on top of the SDN architecture, forming a Knowledge-defined Network.
  • Replication and consistency in heterogeneous and Distributed SDN networks: Proposing an East-West interface, called SINA, to provide the interoperability of a heterogeneous and distributed SDN network. In addition, a novel Reinforcement Learning-based consistency algorithm is introduced for an adaptive Quorum-based replication mechanism.
  • Applying Federated Learning to SDN: The learning phase of a multi-domain SDN network must address the following problems: both solutions of 1) learning separately in each domain and 2) collecting all data from different controllers and launching the training phase in a centralized server are not efficient due to the computational cost, training time, and the accuracy. That motivates us to apply Federated Learning, in which distributed SDN controllers cooperatively train a centralized learning model while do not share the training data for preserving data privacy.

Team Members

Dr. Nguyen Phi Le
Team Leader

Dr. Tran Hai Anh
Member

Assoc. Prof. Do Phan Thuan
Member

Dr. Nguyen Thanh Hung
Member

Assoc. Prof. Tran Quang Duc
Member

Projects and Solutions

[VINIF2020] Fi-Mi: A Fine-grained AI-based Mobile Air Quality Monitoring and Forecasting System

Latest Publications

Publications in 2026

  1. . .

Publications in 2025

  1. Van Tong, Lam Tran, Hung Pham, Tung Bui , Duc Tran. Reducing Communication Overhead in Federated Learning using Deep Reinforcement Learning. Proceedings of the 3rd ACM Workshop on Secure and Trustworthy Deep Learning Systems. 21-30. Hanoi, Vietnam. 26/08/2025
  2. Phạm Thanh Huyền, Nguyễn Thị Anh Thư, Nguyễn Thanh Hùng, Nguyễn Xuân Quyền. Học bổng thu hút sinh viên giỏi học các ngành khoa học cơ bản, kỹ thuật, công nghệ – Bài học từ các quốc gia phát triển và giải pháp cho Việt Nam. Hội thảo khoa học chính sách xét cấp học bổng, chi phí sinh hoạt cho người học các ngành khoa học cơ bản, kỹ thuật then chốt và công nghệ chiến lược. 52-58. Trường Đại học Sư phạm kỹ thuật TP HCM. 20/06/2025
  3. Hai-Anh Tran; Cong-Son Duong; Trong-Duc Bui; Van Tong; Huynh Thi Thanh Binh. GAMR: Revolutionizing Multi-Objective Routing in SDN Networks With Dynamic Genetic Algorithms. IEEE Transactions on Emerging Topics in Computational Intelligence. 3147-3161. 15/02/2025
  4. Duc Long Nguyen, Duc Tien Du , Xuan Manh Nguyen, Ngoc Tu Nguyen, Khanh Hung Mai, Dinh Quan Dang, Gia Nam Hoang, Anh Duc Tran, Thanh Hung Nguyen, Diep N. Nguyen, Phi Le Nguyen, Van Khiem Mai. Enhancing Tropical Cyclone Intensity Forecasting over the Bien Dong Sea with Foundation Model and Prompt Tuning. Engineering Applications of Artificial Intelligence Journal. 29/09/2025
  5. Cui Wei, Ullah Ismat, Lin Weiming, Zhang Jupei, Chen Zhaowei, Yang Shuyi, Peng Wei, Zhuang Yin, Chen Wenjin, Cao Yi, Zhang Shujun, Jin Shengyang, Yang Liang. Multifunctional Sr2+/Zn2+ Co‐Doped Mesoporous Silica Nanoparticles in Injectable Hydrogel for Ameliorating Osteoporotic Osseointegration. Advanced Healthcare Materials. 15/06/2025
  6. Nguyen Quang H., Tran Hoang V., Nguyen Huu Tien, Le Phuong T. M., Nguyen Phi Le, Nguyen Binh P.. AIM: an accurate and explainable model for ATAC to GEX translation and pathway analysis. Memetic Computing. 1-12. 22/02/2025
  7. Thai Nguyen, Trung Thanh NGUYEN, Tien Nguyen, Trung Nguyen Thanh, Hieu Pham, Thanh Hung Nguyen, Truong Thao Nguyen, Phi Le Nguyen. CT to PET Translation: A Large-scale Dataset and Domain-Knowledge-Guided Diffusion Approach. IEEE/CVF Winter Conference on Applications of Computer Vision. 28/02/2025
  8. Trong Bang Nguyen, Phi Le Nguyen, Simon Lucey, Minh Hoai. Region-Level Data Attribution for Text-to-Image Generative Models. International Conference on Computer Vision, ICCV 2025. 21/10/2025
  9. Thu Hang Phung, Manh Duong Nguyen, Thanh Trung Huynh, Quoc Viet Hung Nguyen, Trong Nghia Hoang, Phi Le Nguyen. Federated Prompt-Tuning with Heterogeneous and Incomplete Multimodal Client Data. International Conference on Computer Vision, ICCV 2025. 21/10/2025
  10. 5. Manh Cuong Dao, The Hung Tran, Phi Le Nguyen, Thao Nguyen Truong, Trong Nghia Hoang,. ROOT: Rethinking Offline Optimization as Distributional Translation via Probabilistic Bridge. The Thirty-ninth Annual Conference on Neural Information Processing Systems (Neurips 2025). 02/12/2025
  11. Tran Giang, Hoang Anh, Bui Tung, Tong Van, Tran Duc. A Deep Learning Approach to Early Identification of Remote Access Trojans. Symposium on Information and Communication Technology. 445-456. 13/12/2024
  12. Dong Le, Anh Nguyen, Hung Nguyen, Duc Tran, Giang Nguyen, Van Tong. Enhancing Automated Penetration Testing Using Reasoning Large Language Model. Hội nghị Khoa học Quốc gia về Nghiên cứu cơ bản và Ứng dụng công nghệ thông tin. 308-314. Đại học Công nghiệp Hà Nội (HAUI). 21/08/2025
  13. Nguyen Manh Duong, Huy Pham Nguyen Dang, Nguyen Phi Le, Do Minh N.. A Semi-Supervised Learning Framework with Cross-Magnification Attention for Glioma Mitosis Classification. 2025 IEEE 22nd International Symposium on Biomedical Imaging (ISBI). 1-4. 14/04/2025
  14. Minh Hai Vu , Thanh Trung Nguyen, Thi Ha Ly Dinh, Thanh-Hung Nguyen, Phi Le Nguyen, Kien Nguyen, Hiroo Sekiya. Evaluating MPQUIC Schedulers in Dynamic Wireless Networks with 2D and 3D Mobility. Computer Networks Journal. 03/09/2025
  15. Nguyen Son Dinh, Tuan Dung Nguyen, Duc Tri Tran, Nguyen Dang Huy Pham, Thuan Hieu Tran, Ngoc Anh Tong, Quang Huy Hoang, and Phi Le Nguyen. Sign Language Recognition: A Large-scale Multi-view Dataset and Comprehensive Evaluation. WACV 2025– IEEE/CVF Winter Conference. 7876-7886. 28/01/2025
  16. Vu Bach, Nguyen Hoang, Nguyen Quang Minh, Le Duong, Pham Hieu, Le Nguyen Phi, Nguyen Lam M.. Foundation Model and Temporal Priors-guided Transductive Few-shot Action Recognition. 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2025). 1-5. 05/04/2025
  17. Manh Cuong Dao a , Phi Le Nguyen a , Huy Hieu Pham, Thanh Hung Nguyen , Peng Chen , Mohamed Wahib, Thao Nguyen Truong. Noisy Data-based Attack: a New Type of Untargeted Attack in Federated Learning and Its Countermeasures. Future Generation Computer Systems. 02/05/2025
  18. Tran Hai Anh. ULNet: Federated Unlearning for SDN Control-Plane Anomaly Detection. IEEE Networking Letters. 1-1. 13/12/2025
  19. Ta Duc Huy, Duy Anh Huynh, Yutong Xie, Yuankai Qi, Qi Chen, Phi Le Nguyen, Sen Kim Tran, Son Lam Phung, Anton van den Hengel, Zhibin Liao, Minh-Son To, Johan W. Verjans, Vu Minh Hieu Phan. Seeing the Trees for the Forest: Rethinking Weakly-Supervised Medical Visual Grounding. International Conference on Computer Vision. 21/10/2025
  20. Pham Cuong M., Nguyen Phi Le, Nguyen Thanh Trung , Phan Vu Minh Hieu , Nguyen Binh P. |. Unleashing SAM for Few-Shot Medical Image Segmentation with Dual-Encoder and Automated Prompting. Medical Image Computing and Computer Assisted Intervention – MICCAI 2025 (MICCAI 2025). 23/09/2025
  21. Nam Duong Tran, Nam Nguyen Phuong, Hieu H. Pham, Phi Le Nguyen, My T. Thai. ConstStyle: Robust Domain Generalization with Unified Style Transformation. IEEE International Conference on Computer Vision (ICCV). 25/06/2025
  22. Thanh Tam Nguyen, Thanh Trung Huynh, Zhao Ren, Phi Le Nguyen, Alan Wee-Chung Liew, Hongzhi Yin, Quoc Viet Hung Nguyen. A Survey of Machine Unlearning. ACM Transactions on Intelligent Systems and Technology. 27/09/2025
  23. Tue M. Cao, Nhat X. Hoang, Hieu H. Pham, Phi Le Nguyen, My T. Thai. NEURFLOW: INTERPRETING NEURAL NETWORKSTHROUGH NEURON GROUPS AND FUNCTIONAL IN-TERACTIONS. ICLR 2025. null. 24/04/2025
  24. 2. Trung Kien Pham, Hoang Minh Vu, Anh Duc Chu, Dac Thai Nguyen, Trung Thanh Nguyen, Thao Nguyen Truong, Mai Hong Son, Thanh Trung Nguyen, Phi Le Nguyen. PADM: A Physics-aware Diffusion Model for Attenuation Correction. The IEEE/CVF Winter Conference on Applications of Computer Vision 2026. 06/03/2026
  25. Cuong Dao, Van Tong, Hai Anh Tran, Duc Tran, Giang Nguyen. POSTER: Multimodal Graph Networks for Systematic Generalization in Code Clone Detection. The 20th ACM ASIA Conference on Computer and Communications Security (ACM ASIACCS 2025). Hanoi, Vietnam. 25/08/2025
  26. Tran Hai Anh, Hoang Nam-Thang. Towards Efficient and Adaptive Traffic Classification: A Knowledge Distillation-Based Personalized Federated Learning Framework. IEEE Transactions on Network and Service Management. 1-1. 01/11/2025
  27. Tran Truong X., Himes Ryan E., Tran Hai Anh. Context-Enriched Dynamic Graph Word Embeddings for Robust NLP Applications. Informatica (Slovenia). 30/08/2025
  28. Tran Hai Anh, Binh Huynh Thi Thanh, Mellouk Abdelhamid. Federated Learning for Network Traffic Classification: A Knowledge Consolidation Approach. IEEE Transactions on Network Science and Engineering. 797-814. 05/07/2025
  29. 1. Nang Hung Nguyen, Phi Le Nguyen, Thao Nguyen Truong, Trong Nghia Hoang, Masashi Sugiyama. Causal Graph Learning via Distributional Invariance of Cause-Effect Relationship. Transactions on Machine Learning Research (TMLR). 19/12/2025
  30. Hai Anh Tran, Van Tong. ECODI: a novel evolutionary coreset distillation with LLM-assisted fitness evaluation for encrypted network traffics.. International Journal of Machine Learning and Cybernetics. 03/03/2025
  31. Thanh Tam Nguyen, Zhao Ren, Trinh Pham, Phi Le Nguyen, Quoc Viet Hung Nguyen, Hongzhi Yin. A review of instruction-guided image editing. Engineering Applications of Artificial Intelligence. 22/10/2025
  32. Nguyen Manh Duong, Nguyen Dac Thai, Nguyen Trung Viet, Yamada Homi, Pham Huy Hieu, Le Nguyen Phi. Bridging Classification and Segmentation in Osteosarcoma Assessment via Foundation and Discrete Diffusion Models. 2025 IEEE 22nd International Symposium on Biomedical Imaging (ISBI). 1-5. 13/04/2024
  33. Nang Hung Nguyen; Truong Thao Nguyen; Trong Nghia Hoang; Hieu H. Pham; Thanh Hung Nguyen; Phi Le Nguyen. SAFA: Handling Sparse and Scarce Data in Federated Learning with Accumulative Learning. IEEE Transactions on Computers. 28/02/2025
  34. Yunfei Wang, Yeqin Zhang, Yuyang Wu, Liang Lu, Phi Le Nguyen, Xiaoliang Wang, Cam-Tu Nguyen. MLAlgo-Bench: Can Machines Implement Machine Learning Algorithms?. The Association for Computational Linguistics: EMNLP 2025. 04/11/2025
  35. Huu Tien Nguyen, Dac Thai Nguyen, Duc Nguyen The Minh, Trung Thanh Nguyen, Thao Nguyen Truong, Hieu Pham, Johan Barthelemy, Tran Minh Quan, Quoc Viet Hung Nguyen, Thanh Tam Nguyen, Mai Hong Son, Chau Quynh Anh, Thanh Trung Nguyen, Phi Le Nguyen. Toward a Vision-Language Foundation Model for Medical Data: Multimodal Dataset and Benchmarks for Vietnamese PET/CT Report Generation. The Thirty-ninth Annual Conference on Neural Information Processing Systems (NeurIPS 2025). 02/12/2025
  36. Tran Hai Anh, Ta Cuong, Tran Truong X.. FedImp: Enhancing Federated Learning Convergence with Impurity-Based Weighting. IEEE Transactions on Artificial Intelligence. 1-13. 30/08/2025
  37. . .
  38. Dung Nguyen, Minh Khoi Ho, Huy Ta, Thanh Tam Nguyen, Qi Chen, Kumar Rav, Quy Duong Dang, Satwik Ramchandre, Son Lam Phung, Zhibin Liao, Minh-Son To, Johan Verjans, Phi Le Nguyen, Vu Minh Hieu Phan. Localizing Before Answering: A Benchmark for Grounded Medical Visual Question Answering. Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence (IJCAI). 16/08/2025
  39. Thanh Trung Nguyen, Minh Hai Vu, Phi Le Nguyen, Kien Nguyen. Analysis and visualization of QUIC protocol deployment in Vietnam. IEICE Communications Express. 12/08/2025
  40. Ta Duc Huy1() , Abin Shoby1 , Sen Tran, Yutong Xie5 , Qi Chen1 , Phi Le Nguyen4 , Akshay Gole1 , Lingqiao Liu1 , Antonios Perperidis1 , Mark Friswell3 , Rebecca Linke3 , Andrea Glynn3 , Minh-Son To2 , Anton van den Hengel1 , Johan Verjans1 , Zhibin Liao1 , Minh Hieu Phan1. PedCLIP: A Vision-Language model for Pediatric X-rays with Mixture of Body part Experts. Medical Image Computing and Computer Assisted Intervention – MICCAI 2025. 23/09/2025
  41. Nguyen Tran Tri Dung, Do Thi Thuy Nga, Hoang Quang Huy, Nguyen Phi Le, Tran Anh Vu. M3-SLR: Self-Supervised Pretraining with MaxFlow MaskFeat for Improved Multi-View Sign Language Representation. IEEE Access. 148170-148191. 17/08/2025
  42. Ryan E. Himes, Hai Anh Tran, Truong X. Tran. Leveraging Dynamic Graph Word Embedding for Efficient Contextual Representations. International Symposium on Information and Communication Technology (SOICT24). Da Nang, Vietnam. 13/12/2024
  43. Van Tong; Cuong Dao; Hai Anh Tran; Duc Tran; Huynh Thi Thanh Binh; Nam-Thang Hoang. Encrypted Traffic Classification Through Deep Domain Adaptation Network With Smooth Characteristic Function. IEEE Transactions on Network and Service Management. 331-343. 24/01/2025
  44. Manh Duong Nguyen, Trong Nghia Hoang, Thanh Trung Huynh, Quoc Viet Hung Nguyen, Phi Le Nguyen. Learning Reconfigurable Representations for Multimodal Federated Learning with Missing Data. The Thirty-Ninth Annual Conference on Neural Information Processing Systems (Neurips 2025). 02/12/2025
  45. Son Duong, Truong X. Tran, Hai Anh Tran. ICARE: cross-domain text classification with incremental class-aware representation and distillation learning.. International Journal of Machine Learning and Cybernetics.. 15/02/2025
  46. Thanh Trung Huynh, Trong Bang Nguyen, Thanh Toan Nguyen, Phi Le Nguyen, Hongzhi Yin, Quoc Viet Hung Nguyen, Thanh Tam Nguyen. Certified Unlearning for Federated Recommendation. ACM Transactions on Information Systems. 17/01/2025

Publications in 2024

  1. Vedant S. Lanjewar; Hai-Anh Tran; Truong X. Tran. Layer-Wise Adaptive Weighting for Faster Convergence in Federated Learning. Information Reuse and Integration for Data Science (IRI 2024). San Jose, CA, USA. 07/08/2024
  2. Abhinav Vij, Hai-Anh Tran, Truong X. Tran. Trustable Network Intrusion Detection System Through Wisdomnet and Uncertainty Measures. Local Computer Networks Conference (LCN). Caen, Normandy, France. 08/10/2024
  3. Thanh Trung Huynh, Trong Bang Nguyen, Thanh Toan Nguyen, Phi Le Nguyen, Hongzhi Yin, Quoc Viet Hung Nguyen, Thanh Tam Nguyen. Certified Unlearning for Federated Recommendation. ACM Transactions on Information Systems. 21/11/2024
  4. Van Tong, Cuong Dao, Hai-Anh Tran, Truong X. Tran, Sami Souihi. Enhancing BERT-based Language Model for Multi-Label Vulnerability Detection of Smart Contract in Blockchain. Journal of Network and Systems Management. 10/05/2024
  5. Manh Duong Nguyen, Trung Thanh Nguyen, Huy Hieu Pham, Trong Nghia Hoang, Phi Le Nguyen and Thanh Trung Huynh. FedMAC: Tackling Partial-Modality Missing in Federated Learning with Cross-Modal Aggregation and Contrastive Regularization. International Symposium on Network Computing and Applications (NCA). 23/10/2024
  6. Duy A. Nguyen, Trang H. Tran, Huy Hieu Pham, Phi Le Nguyen, Lam M. Nguyen. Improving Time Series Encoding with Noise-Aware Self-Supervised Learning and an Efficient Encoder. IEEE International Conference on Data Mining. 09/12/2024
  7. Van Tong, Sami Souihi, Hai Anh Tran, Abdelhamid Mellouk. Troubleshooting Solution for Traffic Congestion Control. Journal of Network and Computer Applications. 16/06/2024
  8. Duong Nguyen, Phi Le Nguyen, Truong Nguyen, Hieu Pham, and Duc Tran. FedBlock: A Blockchain Approach to Federated Learning against Backdoor Attacks. IEEE BigData. 15/12/2024
  9. Tuan Dung Nguyen; Ngoc Anh Tong; Binh P. Nguyen; Quoc Viet Hung Nguyen; Phi Le Nguyen; Thanh Trung Huynh. Hierarchical Federated Learning in MEC Networks with Knowledge Distillation. 2024 International Joint Conference on Neural Networks (IJCNN). 1-8. Yokohama, Japan. 30/06/2024
  10. Nguyen Trung Thanh, Le Nguyen Phi, Kawanishi Yasutomo, Komamizu Takahiro, Ide Ichiro. Zero-Shot Pill-Prescription Matching With Graph Convolutional Network and Contrastive Learning. IEEE Access. 55889-55904. 17/04/2024
  11. Minh Hieu Nguyen, Thanh Trung Huynh, Thanh Toan Nguyen, Phi Le Nguyen, Hien Pham, Jun Jo, Thanh Tam Nguyen. On-Device Diagnostic Recommendation with Heterogeneous Federated BlockNets. Science China Information Sciences. 1-17. 14/09/2024
  12. Son Duong, Tuan Nguyen, Nam-Thang Hoang, Van Tong, Hai-Anh Tran, Giang Nguyen, Abdelhamid Mellouk, Truong Tran. Server and Route Selection Optimization for Knowledge-defined Distributed Network Based on Gambling Theory and LSTM Neural Networks. IEEE Global Communications Conference. 04/12/2023
  13. Dong Duc Anh Nguyen, Minh Hieu Nguyen, Phi Le Nguyen, Jun Jo, Hongzhi Yin, Thanh Tam Nguyen. Multi-task Learning of Heterogeneous Hypergraph Representations in LBSNs. The 20th International Conference on Advanced Data Mining and Applications 2024. 15/12/2024
  14. Quang Ha Pham, Nguyen Nang Hung, Hieu Pham, Nguyen Thanh-Hung, Truong Thao Nguyen, Phi Le Nguyen. SEM: A Simple Yet Efficient Model-agnostic Local Training Mechanism to Tackle Data Sparsity and Scarcity in Federated Learning. The Eleventh International Symposium on Computing and Networking (CANDAR). 27/11/2024
  15. Thanh Trung Huynh, Trong Bang Nguyen, Phi Le Nguyen, Thanh Tam Nguyen, Matthias Weidlich, Quoc Viet Hung Nguyen, Karl Aberer. Fast-FedUL: A Training-Free Federated Unlearning with Provable Skew Resilience. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2024). 55-72. Vilnius, Lithuania. 08/09/2024
  16. Sakong Darnbi, Vu Viet Hung, Huynh Thanh Trung, Nguyen Phi Le, Yin Hongzhi, Nguyen Quoc Viet Hung, Nguyen Thanh Tam. Higher-order knowledge-enhanced recommendation with heterogeneous hypergraph multi-attention. Information Sciences. 121165. 01/10/2024
  17. Cong-Son Duong, Hai-Anh Tran, Truong X. Tran. Continuous Select-And-Prune Incremental Learning for Encrypted Traffic Classification in Distributed SDN Networks. Local Computer Networks Conference (LCN). Normandy, France. 08/10/2024
  18. Nguyen Anh Duy, Phung Thu Hang, Nguyen Thuy Dung, Pham Huy Hieu, Nguyen Kien, Nguyen Phi Le. GAMMA: A universal model for calibrating sensory data of multiple low-cost air monitoring devices. Engineering Applications of Artificial Intelligence. 107591. 01/02/2024
  19. Thanh Trung Nguyen, Minh Hai Vu, Thi Ha Ly Dinh, Thanh Hung Nguyen, Phi Le Nguyen, Kien Nguyen. FQ-SAT: A fuzzy Q-learning-based MPQUIC scheduler for data transmission optimization. Computer Communications. 107924. 08/08/2024
  20. Van Tong, Dong Le Van, Quynh Anh Vu, Tuan Anh Ngo, Tri Duc Phung, Van Trong Nguyen, Duc Tran. VNeSafe: Machine Learning-Assisted System for Detecting Malicious URLs and Spam Calls. Journal of Science and Technology Technical Universities. 010-017. 14/03/2024
  21. Nguyen Minh Hieu, Nguyen Huu Tien, Nguyen Trung Thanh, Nguyen Manh Duong, Hoang Trong Nghia, Nguyen Truong Thao, Nguyen Phi Le. FedCert: Federated Accuracy Certification. The 22nd International Symposium on Network Computing and Applications. 254-261. 23/10/2024
  22. Tue Minh Cao, Nhat Hoang-Xuan, Hieu Pham, Phi Le Nguyen, My T. Thai. NeurFlow: Interpreting Neural Networks through Critical Neuron Groups and Functional Interactions. The Thirteenth International Conference on Learning Representations, ICLR 2025. 23/08/2024
  23. Tuan Nguyen, Hoang Ngo, Trung Pham, Nam-Thang Hoang, Van Tong, Hai-Anh Tran, Giang Nguyen, Abdelhamid Mellouk, Truong Tran. Multi Service-Oriented Routing Mechanism for Heterogeneous Multi-Domain Software-Defined Networking. IEEE Global Communications Conference. Kuala Lumpur, Malaysia. 04/12/2023
  24. Quang Huy Do, Sami Souihi, Van Tong, Hai Anh Tran, Sara Tucci-Piergiovanni. An Adaptive Sharding-based Blockchain for Network Slicing in 5G. IEEE Global Communications Conference. Kuala Lumpur. 04/12/2023
  25. Nguyen Thanh Trung, Vu Minh Hai, Ly Dinh Thi Ha, Nguyen Phi Le, Nguyen Kien. MuLeS: A Multi-Client Learning-Based MPQUIC Scheduler. Proceedings - IEEE Consumer Communications and Networking Conference, CCNC. 656-661. 05/01/2025
  26. Manh Cuong Dao, Phi Le Nguyen, Thao Nguyen Truong, Trong Nghia Hoang. Incorporating Surrogate Gradient Norm to Improve Offline Optimization Techniques. The Thirty-eighth Annual Conference on Neural Information Processing Systems, NeurIPS 2024. 10/12/2024
  27. Nguyen Thanh Tam, Huynh Thanh Trung, Ren Zhao, Nguyen Thanh Toan, Nguyen Phi Le, Yin Hongzhi, Nguyen Quoc Viet Hung. Privacy-preserving explainable AI: a survey. Science China Information Sciences. 01/01/2025
  28. T. K. Lai, and I. L. Ngo. An investigation on the thermo-electrohydraulic performance of novel ECF micro-pump.. International Journal of Heat and Mass Transfer. 29/09/2024
  29. Manh Cuong Dao, Phi Le Nguyen, Thao Nguyen Truong, Trong Nghia Hoang. Boosting Offline Optimizers with Surrogate Sensitivity. ICML. 1-10. áo. 21/07/2024
  30. Minh Khiem Pham, Phi Le Nguyen, Viet Hung Vu, Thao Nguyen Truong, Hoa Vo-Van, Thanh Ngo-Duc. A Data-driven Approach for High Accurate Spatiotemporal Precipitation Estimation", Neural Computing and Applications Journal. Neural Computing and Applications. 6099–6118. 13/12/2023
  31. Sikandar Ali Qalati, MengMeng Jiang, Samuel Gyedu, and Emmanuel Kwaku Manu. Do Strong Innovation Capability and Environmental Turbulence Influence the Nexus Between Customer Relationship Management and Business Performance?. Business Strategy and the Environment. 02/07/2024
  32. Van An Le, Nam Duong Tran, Phuong Nam Nguyen, Thanh Hung Nguyen, Phi Le Nguyen, Truong Thao Nguyen, Yusheng Ji. Enhancing the Generalization of Personalized Federated Learning with Multi-head Model and Ensemble Voting. 38th IEEE International Parallel & Distributed Processing Symposium (IPDPS 2024). 205-216. Mỹ. 27/05/2024
  33. Viet Hung Vu, Duc Long Nguyen, Thanh Hung Nguyen, Nguyen Quoc Viet Hung, Phi Le Nguyen, Huynh Thanh Trung. Self-supervised air quality estimation with graph neural network assistance and attention enhancement. Neural Computing and Applications. 11171–11193. 21/02/2024
  34. Minh Hai Vu, Thanh Trung Nguyen, Thi Ha Ly Dinh, Phi Le Nguyen, Kien Nguyen. LoGra: an LSTM-DDPG Integrated MPQUIC Scheduler for Mobile Video Streaming. 2024 IEEE 100th Vehicular Technology Conference (VTC2024-Fall). 1-5. Washington, DC, USA. 07/10/2024
  35. JYE Tin, WW Tan, AA Bakar, MS Mahali, FF Lothai, NF Mohammad, SSA Hassan & KF Chin. A Conceptual Design of Sustainable Solar Photovoltaic (PV) Powered Corridor Lighting System with IoT Application. ICREEM 2022. 09/03/2024
  36. . .
  37. Van An Le, Duc Long Nguyen, Phi Le Nguyen, Yusheng Ji. Traffic Engineering in Large-scale Networks via Multi-Agent Deep Reinforcement Learning with Joint-Training. 2024 33rd International Conference on Computer Communications and Networks (ICCCN). 1-9. Kailua-Kona, HI, USA. 29/07/2024
  38. Trinh Thi Ha, Nguyen Trung Dung, Nguyen Thanh Huong, Tran Trong An, Pham Van Tuan, Vu Ngoc Hung, Chu Manh Hoang. Investigating the coupling length of two triangle hybrid gap plasmonic waveguides. The International Conference on Advanced Materials and Technology (ICAMT 2024). 10-13. Hanoi. 09/10/2024
  39. Tống Văn Vạn, Đồng Gang Thép, Chử Minh Hà, Trần Quang Đức. CẢI THIỆN BÀI TOÁN PHÁT HIỆN LỖ HỔNG ĐA NHÃN TRONG HỢP ĐỒNG THÔNG MINH SỬ DỤNG MÔ HÌNH NGÔN NGỮ LỚN. The National Conference on Fundamental and Applied IT Research (FAIR’2024). HỌC VIỆN CÔNG NGHỆ BƯU CHÍNH VIỄN THÔNG, HÀ NỘI. 08/08/2024
  40. Tuan Dung Nguyen, Thanh Trung Huynh, Minh Hieu Phan, Quoc Viet Hung Nguyen, Phi Le Nguyen. CARER - ClinicAl Reasoning-Enhanced Representation for Temporal Health Risk Prediction. Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing. 10392–10407. 12/11/2024
  41. Van Tong, Dao Viet Cuong, Duc Tran. MULTICLONEBERT: A NOVEL SEMANTIC CODE CLONE DETECTION MECHANISM LEVERAGING GRAPH-BASED LARGE LANGUAGE MODEL. The National Conference on Fundamental and Applied IT Research (FAIR’2024). HỌC VIỆN CÔNG NGHỆ BƯU CHÍNH VIỄN THÔNG, HÀ NỘI. 08/08/2024
  42. Sikandar Ali Qalati, Domitilla Magni, and Faiza Siddiqui. Senior Management's Sustainability Commitment and Environmental Performance: Revealing the Role of Green Human Resource Management Practices.. Business Strategy and the Environment. 02/08/2024
  43. T. K. Lai, and I. L. Ngo. A new design and optimization of VD-ECF micro-pump: Advancements in electrohydraulic performance. Physics of Fluids. 29/07/2024
  44. HUNG PHAM, HUYEN HA, VAN TONG, DUNG HOANG, DUC TRAN, AND TUYEN NGOC LE. MAGECODE: Machine-Generated Code Detection Method Using Large Language Models. IEEE Access Journal. 190186 - 190202. 19/11/2024
  45. Thu Hang Phung; Binh P. Nguyen; Thanh Hung Nguyen; Quoc Viet Hung Nguyen; Phi Le Nguyen; Thanh Trung Huynh. A Contrastive Learning and Graph-based Approach for Missing Modalities in Multimodal Federated Learning. 2024 International Joint Conference on Neural Networks (IJCNN). 1-8. Yokohama, Japan. 30/06/2024
  46. Duc Long Nguyen, Thao Nguyen Truong, Phi Le Nguyen. Combating Quality Distortion in Federated Learning with Collaborative Data Selection. 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2024). 25/04/2024
  47. Van Tong, Cuong Dao, Thep Dong, Hai Anh Tran, Duc Tran and Truong X. Tran. POSTER: Multi-Block Fusion Mechanism for Multi-label Vulnerability Detection in Smart Contracts. The 19th ACM ASIA Conference on Computer and Communications Security (ACM ASIACCS 2024). 1955 - 1957. Singapore. 30/06/2024
  48. Huyen-Trang Le, Hai-Anh Tran, Truong X. Tran. Optimizing Edge-Cloud Server Selection: A Multi-Objective Deep Reinforcement Learning Approach. IEEE Cloud Summit 2024. 101-106. Washington D.C., USA. 27/06/2024
  49. T. K. Lai, and I. L. Ngo. An investigation on the electrohydraulic performance of novel ECF micro-pump with NACAshaped electrodes. Theoretical and Computational Fluid Dynamics. 29/02/2024
  50. Pham Minh Khiem, Nguyen Phi Le, Vu Viet Hung, Truong Thao Nguyen, Vo-Van Hoa, Ngo-Duc Thanh. A data-driven approach for high accurate spatiotemporal precipitation estimation. Neural Computing and Applications. 6099-6118. 01/04/2024
  51. Hai-Anh Tran, Duc Tran. FL4SDN: A Fast-Convergent Federated Learning for Distributed and Heterogeneous SDN. IEEE Intelligent Systems. 1-12. 30/08/2024
  52. Khanh Nguyen Quoc, Van Tong, Cuong Dao, Tuyen Ngoc Le, Duc Tran. Boosted regression for predicting CPU utilization in the cloud with periodicity. Journal of Supercomputing. 26036-26060. 11/08/2024