Nguyen Phi Le

AI4Life Coordinator
Lecturer, Department Of Computer Science

Ph.D. (Department of Informatics, School of Multidisciplinary Sciences, SOKENDAI, National institute of Informatics, Japan, 2019)
M.S. (Department of Frontier Informatics, Graduate School of Frontier Sciences, The university of Tokyo, 2010)
B.S. (Department of Information and Communication Engineering, The university of Tokyo, 2007)

Email: lenp@soict.hust.edu.vn
Website: https://ai4life.hust.edu.vn/lenp/

• Wireless Sensor network and IoT
• Mobile edge computing
• Optimization of network protocol
• Optimization of network deployment
• Network resource management
• Reinforcement learning

• Optimization of routing protocols in WSNs
• Optimization of sensor node deployment for coverage and connectivity
• Task offloading in Mobile edge computing
• Network lifetime optimization in WSNs
• Charging schedule for wireless rechargeable WSNs
• Machine learning for network optimization and resource management

Phi Le Nguyen obtained her Bachelor of Engineering and Master of Science degrees from the University of Tokyo in 2007 and 2010, respectively. In 2019, she earned her doctorate in informatics from The Graduate University for Advanced Studies, National Institute of Informatics in Tokyo, Japan.

Dr. Phi Le Nguyen currently serves as the acting director of the HUST Institute for AI Innovation and Societal Impact (AI4LIFE), and holds the position of associate professor at School of Information and Communication Technology, Hanoi University of Science and Technology (HUST), School of Information and Communication Technology.

She leads a research group comprising over 80 talented students focusing on research on theoretical AI and applying AI in environmental science, climate change and smart healthcare.

With a portfolio of more than 130 articles published in esteemed journals and conferences such as ICML, Neurips, ICLR, EMNLP, IJICAI, Dr. Nguyen has garnered multiple best paper awards, including the best paper awards at ISSNIP’14, ICT-DM’19, CCGrid 2023 and CANDAR 2023. She actively contributes to prestigious conferences as a Technical Program Committee (TPC) member and serves as a reviewer for prominent journals and conferences, including AAAI, ICLR, Neurips, CVPR, ECCV, UAI, ICCV, ToN, and IoTJ.

Her research has been funded by several renowned institutions including VinIF, Nafosted, MOET, MOST, Aus4Innovation.

• 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 2025 (ICCV)
• 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 2025 (ICCV)
• 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 2025 (ICCV)
• Nam Duong Tran, Nam Nguyen Phuong, Hieu Pham, Phi Le Nguyen, My T. Thai, “ConstStyle: Robust Domain Generalization with Unified Style Transformation”, International Conference on Computer Vision 2025 (ICCV)
• Thanh Tam Nguyen, Phi Le Nguyen, Nguyen Quoc Viet Hung et al., “A Survey of Machine Unlearning”, ACM Transactions on Intelligent Systems and Technology 2025.
• Ta Duc Huy, Phi Le Nguyen, Minh Hieu Phan, et al., “Too Tall for the Crib: When Vision-Language Models Outgrow Pediatric X-rays”, Medical Image Computing and Computer Assisted Intervention 2025 (MICCAI)
• Cuong Pham, Phi Le Nguyen, Thanh Trung Nguyen, Minh Hieu Phan, Binh Nguyen, “Unleashing SAM for Few-Shot Medical Image Segmentation with Dual-Encoder and Automated Prompting”, Medical Image Computing and Computer Assisted Intervention 2025 (MICCAI)
• Manh Cuong Dao, Phi Le Nguyen, Huy Hieu Pham, Thanh Hung Nguyen, Peng Chen, Mohamed Wahib and Thao Nguyen Truong, “Noisy Data-based Attack: a New Type of Untargeted Attack in Federated Learning and Its Countermeasures”, Future Generation Computer Systems, 2025
• Nguyen Nang Hung, Truong Thao Nguyen, Trong Nghia Hoang, Hieu H. Pham, Thanh Hung Nguyen, and Phi Le Nguyen, “SAFA: Handling Sparse and Scarce Data in Federated Learning with Accumulative Learning”, IEEE Transactions on Computers.
• 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.
• Bach Vu, Hoang Nguyen, Quang Nguyen, Duong Le, Hieu Pham, Phi Le Nguyen, Lam Nguyen, “Foundation Model and Temporal Priors-guided Transductive Few-shot Action Recognition”, 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2025 Main Tracks).
• 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 (WACV 2025).
• Son Dinh, Dung Nguyen, Duc-Tri Tran, Dang-Huy Pham-Nguyen, Thuan Hieu Tran, Tong Anh, Quang Huy Hoang, Phi Le Nguyen, “Sign Language Recognition: A Large-scale Multi-view Dataset and Comprehensive Evaluation”, IEEE/CVF Winter Conference on Applications of Computer Vision (WACV 2025).
• 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.
• 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”, The 2024 Conference on Empirical Methods in Natural Language Processing, EMNLP.
• 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).
• 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”, The 33rd International Conference on Computer Communications and Networks (ICCCN 2024).

• Best paper award at EUC 2024.
• Best paper award at CANDAR 2024.
• Best lecturer of the year 2023-2024 awarded by HUST.
• Best paper nominated by CCGRID 2023.
• 2023 APEC-Australia Women in Research Fellowship.
• NII best student award in 2018.
• Best paper award at ICT-DM 2018.
• Student award at Japan SINET Ideathon competition, 2018.
• Monbusho (Monbukagakusho) scholarship for a three-year PhD program offered by Japanese Government, 2016.
• Best paper award at SoICT 2015.
• Best paper award at ISSNIP 2014.
• Monbusho (Monbukagakusho) scholarship for a two-year M.S program offered by Japanese Government, 2007.
• Monbusho (Monbukagakusho) scholarship for a four-year B.S program offered by Japanese Government, 2002.

• Information security
• Network security