Xiaofeng Liu
Assistant Professor of Radiology and Biomedical Imaging and of Biomedical Informatics and Data ScienceDownloadHi-Res Photo
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Assistant Professor, Biomedical Engineering, Yale School of Engineering & Applied Science
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Appointments
Additional Titles
Assistant Professor, Biomedical Engineering, Yale School of Engineering & Applied Science
Contact Info
Appointments
Additional Titles
Assistant Professor, Biomedical Engineering, Yale School of Engineering & Applied Science
Contact Info
About
Titles
Assistant Professor of Radiology and Biomedical Imaging and of Biomedical Informatics and Data Science
Assistant Professor, Biomedical Engineering, Yale School of Engineering & Applied Science
Biography
Xiaofeng joined Yale on 03/2024 as an Assistant Professor in traditional tenure track, and an Associate Member at the Broad Institute of MIT and Harvard (forward related email to: liuxiaof@broadinstitute.org). He is also actively serving as Associate Editor of IEEE Transactions on Neural Networks and Learning Systems (TNNLS) and Journal of Medical Internet Research (JMIR), Area Chair of MICCAI and ISBI, and NIH reviewer panels (Computational, Modeling, and Biodata Management – MCST (14), (16), etc).
Prior to this, he was an Assistant Professor (2023-2024), Instructor (2021-2023), and Post/Pre-Doctorial Fellow (2019-2021) at MGH/BIDMC of Harvard Medical School.
His research interests are centered around the convergence of trustworthy AI/deep learning, medical imaging, and data science to advance the diagnosis, prognosis, and treatment monitoring of various diseases.
Last Updated on May 18, 2025.
Appointments
Radiology & Biomedical Imaging
Assistant ProfessorPrimaryBiomedical Informatics & Data Science
Assistant ProfessorSecondary
Other Departments & Organizations
- Bioimaging Sciences
- Biomedical Informatics & Data Science
- Center for Brain & Mind Health
- Computational Biology and Biomedical Informatics
- Magnetic Resonance Research Center
- PET Core
- Radiology & Biomedical Imaging
- Xiaofeng Liu Lab
- Yale Biomedical Imaging Institute
- Yale Combined Program in the Biological and Biomedical Sciences (BBS)
- Yale Institute for Global Health
- Yale-BI Biomedical Data Science Fellowship
Education & Training
- Assistant Professor
- Harvard Medical School (2024)
- Affiliate Faculty
- Harvard Data Science Initiative, Kempner Institute for Natural and Artificial Intelligence, Dana-Farber/Harvard Cancer Center . (2024)
- Research Staff
- Massachusetts General Hospital (2024)
- Instructor
- Harvard Medical School (2023)
- Post-doctoral Research Fellow (Radiology)
- Massachusetts General Hospital/Harvard Medical School (2021)
- Post-doctoral Research Fellow (Neurology)
- Beth Israel Deaconess Medical Center/Harvard Medical School (2020)
- PhD
- University of Chinese Academy of Sciences, Mechatronics
- Pre-doctoral Research Fellow
- Beth Israel Deaconess Medical Center (2019)
- Non Degree Program
- Carnegie Mellon University, Electrical and Computer Engineering (2018)
- BA
- University of Science and Technology of China, Communication (2014)
- BE
- University of Science and Technology of China, Automation [Wang-Daheng Elite Class] (2014)
- Non Degree Program
- University of Science and Technology of China, Life Sciences/Biology (2011)
Research
Overview
Medical Research Interests
Artificial Intelligence; Deep Learning; Image Processing, Computer-Assisted; Information Science; Neural Networks, Computer
Public Health Interests
Aging; Cancer; Cardiovascular Diseases; Mental Health; Bayesian Statistics; Survival Analysis; Health Informatics
ORCID
0000-0002-4514-2016- View Lab Website
XLiu Lab
Research at a Glance
Yale Co-Authors
Frequent collaborators of Xiaofeng Liu's published research.
Research Interests
Research topics Xiaofeng Liu is interested in exploring.
Georges El Fakhri, PhD, DABR
Jinsong Ouyang, PhD
Thibault Marin, PhD
Chao Ma, PhD
Ruth Lim, MD
Maeva Dhaynaut
Neural Networks, Computer
Deep Learning
Image Processing, Computer-Assisted
Publications
Featured Publications
Subtype-Aware Dynamic Unsupervised Domain Adaptation
Liu X, Xing F, You J, Lu J, Kuo C, Fakhri G, Woo J. Subtype-Aware Dynamic Unsupervised Domain Adaptation. IEEE Transactions On Neural Networks And Learning Systems 2024, 35: 2820-2834. PMID: 35895653, DOI: 10.1109/tnnls.2022.3192315.Peer-Reviewed Original ResearchCitationsConceptsTarget domainSource domain to target domainUnsupervised domain adaptationWithin-class compactnessHeart disease dataPseudo-labelsDomain adaptationClass centersLatent spaceCluster centroidsConditional alignmentLabel shiftTransfer knowledgeQueueing frameworkLocal proximityAlternative processing schemesSubtype labelsExperimental resultsProcessing schemeSubtype structureDomainNetVisDADisease dataDomainLabelingAttentive continuous generative self-training for unsupervised domain adaptive medical image translation
Liu X, Prince J, Xing F, Zhuo J, Reese T, Stone M, El Fakhri G, Woo J. Attentive continuous generative self-training for unsupervised domain adaptive medical image translation. Medical Image Analysis 2023, 88: 102851. PMID: 37329854, PMCID: PMC10527936, DOI: 10.1016/j.media.2023.102851.Peer-Reviewed Original ResearchCitationsMeSH Keywords and ConceptsConceptsUnsupervised domain adaptationImage translationProblem of domain shiftSelf-trainingImage modality translationLabeled source domainTarget domain dataSelf-attention schemeAlternating optimization schemeHeterogeneous target domainContinuous value predictionPseudo-labelsDomain adaptationUDA methodsDomain shiftSoftmax probabilitiesSource domainTarget domainVariational BayesBackground regionsTranslation tasksTraining processDomain dataGeneration taskOptimization schemeMemory consistent unsupervised off-the-shelf model adaptation for source-relaxed medical image segmentation
Liu X, Xing F, El Fakhri G, Woo J. Memory consistent unsupervised off-the-shelf model adaptation for source-relaxed medical image segmentation. Medical Image Analysis 2022, 83: 102641. PMID: 36265264, PMCID: PMC10016738, DOI: 10.1016/j.media.2022.102641.Peer-Reviewed Original ResearchCitationsMeSH Keywords and ConceptsConceptsUnsupervised domain adaptationUnsupervised domain adaptation methodsSource domain dataBN statisticsTarget domainLabeled source domain dataDomain dataLabeled source domainSelf-training strategyPatient data privacyHeterogeneous target domainBrain tumor segmentationPseudo-labelsDomain adaptationUnsupervised adaptationData privacySegmentation taskSource domainImage segmentationVital protocolAdaptation frameworkDecay strategyBoost performanceModel adaptationTumor segmentationSeverity-Aware Semantic Segmentation with Reinforced Wasserstein Training
Liu X, Ji W, You J, Fakhri G, Woo J. Severity-Aware Semantic Segmentation with Reinforced Wasserstein Training. 2020, 00: 12563-12572. DOI: 10.1109/cvpr42600.2020.01258.Peer-Reviewed Original ResearchCitationsConceptsSemantic segmentationCARLA simulatorCross-entropyGround distance matrixWasserstein training frameworkAlternating optimization schemeCityscapes datasetDNN architecturesCE lossTraining frameworkSemantic classesGround metricInter-class correlationAutonomous vehiclesSuperior performanceOptimization schemeDNNCARLADistance matrixSurgery systemCamVidDeepLabSimulationCityscapesPixelDomain Generalization under Conditional and Label Shifts via Variational Bayesian Inference
Liu X, Hu B, Jin L, Han X, Xing F, Ouyang J, Lu J, El Fakhri G, Woo J. Domain Generalization under Conditional and Label Shifts via Variational Bayesian Inference. 2021, 881-887. DOI: 10.24963/ijcai.2021/122.Peer-Reviewed Original ResearchCitationsConceptsDomain generalizationDomain-invariant feature learningVariational Bayesian inference frameworkLabel shiftCross-domain accuracyLabeled source domainVariational Bayesian inferenceFeature learningBayesian inference frameworkLatent spaceSource domainTarget domainDistribution matchingTransfer knowledgeInference frameworkSuperior performanceP(x|yBayesian inferenceLabelingDomainFrameworkGeneralizationBenchmarksPosterior alignmentLearningAdversarial Unsupervised Domain Adaptation with Conditional and Label Shift: Infer, Align and Iterate
Liu X, Guo Z, Li S, Xing F, You J, Kuo C, Fakhri G, Woo J. Adversarial Unsupervised Domain Adaptation with Conditional and Label Shift: Infer, Align and Iterate. 2021, 00: 10347-10356. DOI: 10.1109/iccv48922.2021.01020.Peer-Reviewed Original ResearchCitationsConceptsUnsupervised domain adaptationDomain adaptationLabel shiftUnsupervised domain adaptation methodsAdversarial unsupervised domain adaptationAlternating optimization schemeUDA methodsTarget domainTraining stageOptimization schemeTesting stageExperimental resultsDistribution w.AdversaryP(x|yP(y|xDomainSchemeClassificationMethodInferenceAdaptation
2025
Vision-language foundation model for generalizable nasal disease diagnosis using unlabeled endoscopic records
Liu X, Gong W, Chen X, Li Z, Liu Y, Wang L, Liu Q, Sun X, Liu X, Chen X, Shi Y, Yu H. Vision-language foundation model for generalizable nasal disease diagnosis using unlabeled endoscopic records. Pattern Recognition 2025, 165: 111646. DOI: 10.1016/j.patcog.2025.111646.BooksCitationsConceptsLabeled dataGeneralization performanceExpert annotationsArtificial intelligencePre-training datasetSuperior generalization performanceState-of-the-artMedical artificial intelligencePerformance of AI modelsNasal endoscopic imagesLearning frameworkAI modelsMultiple imagesSemantic representationDiagnostic tasksFine-tuningTask-specificUniversal representationDatasetExperimental resultsDisease classificationEndoscopic imagesDiagnosis of diseasesAnnotationFoundation modelDendrite cross attention for high-dose-rate brachytherapy distribution planning
Saini S, Liu X. Dendrite cross attention for high-dose-rate brachytherapy distribution planning. Computers In Biology And Medicine 2025, 196: 110902. PMID: 40789235, DOI: 10.1016/j.compbiomed.2025.110902.Peer-Reviewed Original ResearchAltmetricMeSH Keywords and ConceptsConceptsClinical target volumeHDR-BT plansHDR-BTCTV segmentationDose predictionAccurate dose predictionDose prediction accuracyRectum segmentationCTV regionsHigh-dose-rateHigh-dose-rate brachytherapyTreatment planningTarget volumeCT scanPlanner's expertiseCervical cancerGlobal health issueBladderPatient outcomesRectumOARsAnatomical regionsBrachytherapyTreatmentCrossBayesian Posterior Distribution Estimation of Kinetic Parameters in Dynamic Brain PET Using Generative Deep Learning Models
Djebra Y, Liu X, Marin T, Tiss A, Dhaynaut M, Guehl N, Johnson K, Fakhri G, Ma C, Ouyang J. Bayesian Posterior Distribution Estimation of Kinetic Parameters in Dynamic Brain PET Using Generative Deep Learning Models. IEEE Transactions On Medical Imaging 2025, PP: 1-1. PMID: 40663684, PMCID: PMC12318411, DOI: 10.1109/tmi.2025.3588859.Peer-Reviewed Original ResearchAltmetricConceptsPosterior distributions of kinetic parametersEfficiency of deep learningGenerative deep learning modelsConditional variational autoencoderDeep learning modelsComputational efficiencyMetropolis-Hastings MCMCPosterior distributionHyperphosphorylated tauDynamic brain positron emission tomographyWGAN-GPDual decodersWasserstein GANVariational autoencoderKinetic parametersDeep learningComputational needsBayesian inferenceP-tauLearning modelsAlzheimer's diseaseNeurodegenerative diseasesComputation timeMCMC methodsEstimation of kinetic parametersFM-LoRA: Factorized Low-Rank Meta-Prompting for Continual Learning
Yu X, Yang J, Wu X, Qiu P, Liu X. FM-LoRA: Factorized Low-Rank Meta-Prompting for Continual Learning. 2025, 00: 6399-6408. DOI: 10.1109/cvprw67362.2025.00637.Peer-Reviewed Original ResearchConceptsDomain incremental learningClass-incremental learningPre-trained modelsLow-rankContinuous learningSequential tasksLow-rank subspacePredicted class labelImageNet-RCatastrophic forgettingTransformer backboneClass labelsLearning structureStorage costAdaptive methodDiverse tasksModel capacityRobust performanceTaskLearningModel's abilityCIFAR100DomainNetCUB200Parameter growth
Academic Achievements & Community Involvement
Activities
activity IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
2023 - PresentJournal ServiceAssociate Editoractivity International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI)
2023 - PresentMeeting Planning and ParticipationSession ChairDetailsArea Chair of MICCAI 2023, 2024activity Journal of Medical Internet Research (JMIR)
2024 - PresentJournal ServiceAssociate Editoractivity IEEE International Symposium on Biomedical Imaging (ISBI)
2024 - PresentMeeting Planning and ParticipationSession Chairactivity NIH
2025 - PresentPeer Review Groups and Grant Study SectionsReviewerDetailsComputational, Modeling, and Biodata Management – MCST (14)
Honors
honor Robert F. Wagner All-Conference Best Student Paper Finalist Award
02/01/2025International AwardSPIE Medical Imaging 2025honor OpenAI Research Award
01/01/2025National AwardOpenAIhonor Trailblazer R21 Award
05/23/2024National AwardNIBIB/NIHDetailsUnited Stateshonor Google Cloud Research Credits
05/01/2024National AwardGoogleDetailsUnited Stateshonor National Artificial Intelligence Research Resource Pilot Award
04/26/2024National AwardU.S. National Science Foundation (NSF)
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Locations
E169
Academic Office
100 Church Street South, Wing E, Rm 169
New Haven, CT 06519