Huazhu FU

Principal Scientist
Institute of High Performance Computing (IHPC)
Agency for Science, Technology and Research (A*STAR), Singapore.

Email: hzfu(AT)ieee(DOT)org

[Recent News] - [Professional Activities] - [Recognitions] - [Highlighted Publications] - [Grants] - [Google Scholar]
I am a principal scientist at IHPC, A*STAR. I received my Ph.D. from Tianjin University in 2013. Previously, I were a Research Fellow (2013-2015) at Nanyang Technological University (NTU), Singapore, a Research Scientist (2015-2018) at Institute for Infocomm Research (I2R), A*STAR, Singapore, and a Senior Scientist (2018-2021) at Inception Institute of Artificial Intelligence (IIAI), UAE.
Major focuses on:
  • AI for Healthcare: Medical Image Analysis, Medical Efficient Learning, ⚡Medical Vision-language Model, ⚡Medical Foundation Model.
  • Trustworthy AI: Responsible AI, ⚡Uncertainty Estimation, ⚡Federated Learning.

  • PhD Scholarships: Singapore International Graduate Award (SINGA) Scholarship supports international students who wish to pursue their PhDs, collaborated with Singapore Universities (NUS, NTU, and SUTD).
  • Visiting PhD Student: A*STAR Research Attachment Programme (ARAP) supports PhD students from overseas universities to spend a minimum of one to a maximum of two years at A*STAR Research Institutes under the joint supervision.
  • Chinese PhD Student: (Only available for Year 2024) We are also looking for visiting PhD students from China to spend a minimum of one year at IHPC, under Chinese CSC Scholarship.

  • Recent News:

    • [Call For Papers] IEEE JBHI (IF: 7.7) Special Issue on "Foundation Models in Medical Imaging". Submission Deadline: 15 March 2024.

    • [12/2023] Our iChallenge datasets receive the Achievement Award of 2023 TOP 100 Benchmarks & Evaluation by International Open Benchmark Council.
    • [11/2023] 1 paper accepted by IEEE TMI: "Enhancing and Adapting in the Clinic: Source-free Unsupervised Domain Adaptation for Medical Image Enhancement".
    • [11/2023] 1 paper accepted by IEEE TNNLS: "Federated Noisy Client Learning".
    • [11/2023] 1 paper accepted by IEEE TMI: "MG-Trans: Multi-scale Graph Transformer with Information Bottleneck for Whole Slide Image Classification".
    • [10/2023] Happy to receive the Best Paper Award of Distributed, Collaborative and Federated Learning (DeCAF) Workshop in MICCAI 2023: "Federated Model Aggregation via Self-Supervised Priors for Highly Imbalanced Medical Image Classification".
    • [10/2023] 1 paper accepted by Nature Communications: "Uncertainty-inspired Open Set Learning for Retinal Anomaly Identification".
    • [09/2023] 1 paper accepted by NeurIPS 2023: "Fairness-guided Few-shot Prompting for Large Language Models".
    • [09/2023] 1 paper accepted by IEEE TMI: "Edge-guided Contrastive Adaptation Network for Arteriovenous Nicking Classification Using Synthetic Data".
    • [08/2023] 1 paper accepted by MedIA: "A Generic Fundus Image Enhancement Network Boosted by Frequency Self-supervised Representation Learning".
    • [08/2023] 1 GAMMA Challenge summary paper accepted by MedIA: "GAMMA Challenge: Glaucoma grAding from Multi-Modality imAges".
    • [06/2023] 1 papers accepted by ICCV 2023.
    • [06/2023] 16 papers accepted by MICCAI 2023.
    • [04/2023] 3 papers accepted by ICML 2023.
    • [04/2023] 1 paper accepted by Nature Machine Intelligence: "Federated Benchmarking of Medical Artificial Intelligence with MedPerf".
    • [03/2023] 1 survey paper accepted by MedIA: "Transformers in Medical Imaging: A Survey".
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