Muxuan Liang, Ph.D.
Department of Biostatistics, Division of Discovery Science
About Dr. Muxuan Liang
I am an Assistant Professor in the Department of Biostatistics at MD Anderson Cancer Center. Previously, I was an Assistant Professor with the Artificial Intelligence Initiative in the Department of Biostatistics at the University of Florida. I obtained my Ph.D. degree in statistics from the University of Wisconsin-Madison in 2018. After graduation, I briefly worked as a Data Scientist at Google. Then, I joined Fred Hutchinson Cancer Research Center as a post-doctoral research fellow working on biostatistics methodology and applications. My research goal is to realize data-driven personalized/individualized decision-making through innovative methods combining statistical and machine learning techniques. My methodological research focuses on personalized decision-making, causal inference, and novel AI/ML topics, including transfer and multi-modal learning. This expertise also leads to a rich spectrum of collaborations with researchers in biomedical informatics (e.g., electronic health records) and physicians in clinical research.
Present Title & Affiliation
Primary Appointment
Assistant Professor, Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas
Education & Training
Degree-Granting Education
| 2018 | University of Wisconsin-Madison, Madison, WI, US, Statistics, Ph.D |
| 2014 | Tsinghua University, Beijing, Beijing, CN, Pure and Applied Mathematics, B.S |
Postgraduate Training
| 2019-2022 | Postdoctoral Research Fellow, Biostatistics, Fred Hutchinson Cancer Center, Seattle, Washington |
Experience & Service
Faculty Academic Appointments
Assistant Professor, Biostatistics, University of Florida, Gainesville, Florida, 2022 - 2025
Administrative Appointments/Responsibilities
Co-lead of AI Working Group, UF Health Cancer Center, Gainesville, Florida, 2024 - 2025
Intramural Institutional Committee Activities
Member, DSMC, The University of Texas MD Anderson Cancer Center, 2026 - Present
Honors & Awards
| 2023 | Dean’s Citation Award, University of Florida |
| 2018 | ASA Biometrics section travel award |
Selected Presentations & Talks
National Presentations
- 2026. Multi-task Learning for Semiparametric Models with Nuisance Parameters Fusion. Invited. SLDS 2026. Alexandria, Virginia, US.
- 2026. AI-Model Calibration for Covariate Adjustment: Beyond a One-Number Digital Twin. Invited. Madison, WI, US.
- 2026. AI-Powered Medical Decision-making: Learning under Outcome Misclassification. Invited. Houston, Texas, US.
- 2026. A General Framework for Incorporating Identification Uncertainty in Individualized Treatment Rules. Invited. JSM 2026. Alexandria, Virginia, US.
- 2026. Multi-task Learning for Semiparametric Models with Nuisance Parameters Fusion. Invited. The 2026 ICSA Applied Statistics Symposium. Washington, DC, US.
- 2026. AI-Powered Medical Decision-making: Learning under Outcome Misclassification. Invited. Iowa City, Iowa, US.
- 2026. A General Framework for Incorporating Identification Uncertainty in Individualized Treatment Rules. Invited. ENAR 2026. Indianapolis, Indiana, US.
International Presentations
- 2026. A General Framework for Incorporating Identification Uncertainty in Individualized Treatment Rules. Invited. The 9th International Conference on Econometrics and Statistics. Kyoto, JP.
Grant & Contract Support
| Date: | 2027 - 2029 |
| Title: | Reaction-Diffusion Modeling of Pretreatment Lymph Node Biopsies to Predict Neoadjuvant lmmunotherapy Response in Melanoma |
| Funding Source: | US DOD |
| Role: | Key |
| ID: | GRANT14777550 |
| Date: | 2027 - 2032 |
| Title: | Developing Quantitative Models of Achievable Alternatives and Clinical Preferences for Decision Making in Radiotherapy Planning |
| Funding Source: | NIH |
| Role: | Co-I |
| ID: | R01CA3275831 |
| Date: | 2027 - 2029 |
| Title: | Neural Mechanisms of Motor Fatigability: Insights from Essential Tremor and Deep Brain Stimulation |
| Funding Source: | University of Florida |
| Role: | PI |
| Date: | 2025 - 2027 |
| Title: | Neurophysiology of locomotor adaptation and freezing of gait in Parkinson's Disease |
| Funding Source: | NIH |
| Role: | Co-I |
| Title: | Developing Quantitative Models of Achievable Alternatives and Clinical Preferences for Decision Making in Radiotherapy Planning |
| Funding Source: | NIH |
| Role: | Co-I |
| ID: | R01CA3275831 |
| Title: | Spectral Connectomic Mapping of Locomotor Adaptation |
| Funding Source: | University of Florida |
| Role: | PI |
| Title: | Role of Tumor Fructose Metabolism and the Gut Microbiome in Sugar-Sweetened Beverage-Driven Colorectal Cancer |
| Funding Source: | NIH |
| Role: | Co-I |
| ID: | 1R01CA322411-01 |
| Title: | High-Fructose Corn Syrup Promotes Colorectal Cancer Progression through Inflammation and Ceramide Signaling |
| Funding Source: | American Cancer Society |
| Role: | Key |
| Title: | Graph Learning from Multimodal Biomedical Data for Physiologic Trajectory Modeling and Clinical Decision Support |
| Funding Source: | University of Florida |
| Role: | PI |
| Title: | Targeting DHODH-Mediated Ferroptosis Defense to Overcome Radiation and Immunotherapy Resistance in Oligoprogressive NonSmall Cell Lung Cancer |
| Funding Source: | US DOD |
| Role: | Key |
| ID: | LC260493 |
| Title: | Advance Individualized Medical Decision-making Integrating Multi-Modality Information, Uncertainty Quantification, and Complex Outcomes |
| Funding Source: | NIH |
| Role: | PI |
| ID: | 1R01LM015923-01 |
| Title: | Advancing Individualized Treatment Learning for Critical Care: Clinically Targeted, Privacy- Preserving, and Trial-Grounded Methods |
| Funding Source: | University of Wisconsin-Madison |
| Role: | PI |
| Title: | Advancing efficient inference in platform trials using AI, Historical Data, and Federated Learning |
| Funding Source: | NIH |
| Role: | PI |
| ID: | 1R01LM016067-01 |
Selected Publications
Peer-Reviewed Articles
- Imran M, Krebs JR, Sivaraman VB, Zhang T, Kumar A, Ueland WR, Fassler MJ, Wang C, Huang J, Sun X, Wang L, Shi P, Rokuss M, Baumgartner M, Kirchhof Y, Maier-Hein KH, Isensee F, Liu S, Han B, Nguyen BT, Shin DJ, Ji-Woo P, Choi M, Uhm KH, Ko SJ, Lee C, Chun J, Kim JS, Zhang M, Zhang H, You X, Gu Y, Pan Z, Liu X, Liang X, Tiefenthaler M, Almar-Munoz E, Schwab M, Kotyushev M, Epifanov R, Wodzinski M, Muller H, Qayyum A, Mazher M, Niederer SA, Wang Z, Yang K, Ren J, Korreman SS, Gao Y, Zeng H, Zheng H, Zheng R, Yue J, Zhou F, Liu B, Cosman A, Liang M, Zhao C, Upchurch GR Jr, Zhou Y, Cooper MA, Shao W. Multi-class segmentation of aortic branches and zones in computed tomography angiography: The AortaSeg24 challenge. Med Image Anal 113:104188, 2026. e-Pub 2026. PMID: 42413466.
- Dong X, Goyal A, Liang M, Brusko A. M, Brusko M. T, Bacher R. Bootstrap-enhanced regularization addressing multicollinearity and skewness in highdimensional immunophenotyping data. BMC Bioinformatics, 2026. e-Pub 2026.
- Diaz-Rincon R, Liang M, Ramirez-Zamora A, Shickel B. CASCADE Conformal Prediction: Uncertainty-Adaptive Prediction Intervals for Two-Stage Clinical Decision Support. ICML Workshops, 2026. e-Pub 2026.
- Huang, Y, Li, Y, Lou, X, Islam, J, Liang, M, George, TJ, Bian, J, Guo, Y. Breast cancer screening and cancer prognosis in patients with Alzheimer disease and related dementias. JNCI Cancer Spectr 10(2), 2026. e-Pub 2026. PMID: 41761572.
- Yang S, Wu Y, Liu M, Bian J, Liang M, Guo Y. Adjusting Covariate Misclassification in Electronic Health Records-Based Machine Learning Prediction Models. AMIA Annu Symp Proc 2025:1444–1453, 2026. e-Pub 2026.
- Li D, Yao Z, Liang M, Liu M. DeepJ: Graph Convolutional Transformers with Differentiable Pooling for Patient Trajectory Modeling. AMIA Annu Symp Proc 2025:734–743, 2026. e-Pub 2026.
- Liang, M, Ning, Y, Smith, MA, Zhao, YQ. Inference with non-differentiable surrogate loss in a general high-dimensional classification framework. J Mach Learn Res 27, 2026. e-Pub 2026.
- Park, J, Guo, S, Liang, M, Zhong, X. Investigation of the causal relationship between patient portal utilization and patient’s self-care self-efficacy and satisfaction in care among patients with cancer. BMC Med Inform Decis Mak 25(1), 2025. e-Pub 2025. PMID: 39780146.
- Yang, S, Liang, M, Mehta, HJ, Salloum, RG, Braithwaite, D, Wu, Y, Islam, J, Zhang, X, Shih, YT, Huo, J, Bian, J, Guo, Y. Patient and nodule characteristics associated with adherence to lung cancer screening in a large integrated healthcare system. Sci Rep 15(1), 2025. e-Pub 2025. PMID: 40783586.
- Du H, Liang M, Zhong X. A Data-Driven Graph Model Approach to Critical Care Patient Clinical Trajectory Prediction. IEEE Robot Autom Lett, 2025. e-Pub 2025.
- Hernández-Ríos, M, Wu, R, Polcz, VE, Burnside, RD, Yonker, LM, Irimia, D, Xiao, F, Rincon, JC, Loftus, TJ, Moldawer, LL, Maile, R, Efron, PA, Liang, M. Monocyte Anisocytosis Can Discriminate between Sepsis and Sterile Inflammation, but not Mortality, in Critically Ill Surgical/Trauma Patients. Crit Care Explor 7(9):e1309, 2025. e-Pub 2025. PMID: 40924914.
- Liang, M, Zhao, YQ, Lin, DW, Cooperberg, MR, Zheng, Y. Estimating optimally tailored active surveillance strategy under interval censoring. Biometrics 81(2), 2025. e-Pub 2025. PMID: 40445115.
- Jiang, H, Imran, M, Zhang, T, Zhou, Y, Liang, M, Gong, K, Shao, W. Fast-DDPM: Fast Denoising Diffusion Probabilistic Models for Medical Image-to-Image Generation. IEEE J Biomed Health Inform 29(10):7326-7335, 2025. e-Pub 2025. PMID: 40293895.
- Du, H, Liang, M, Zhong, X. A Data-Driven Graph Model Approach to Critical Care Patient Clinical Trajectory Prediction. IEEE Robot Autom Lett 10(11):11768-11775, 2025. e-Pub 2025.
- Park, J, Liang, M, Zhao, YQ, Zhong, X. Efficient surrogate-assisted inference for patient-reported outcome measures with complex missing mechanism. Electron J Stat 19(1):1-53, 2025. e-Pub 2025.
- Ying, C, Jin, J, Guo, Y, Li, X, Liang, M, Zhao, J. Towards the Efficient Inference by Incorporating Automated Computational Phenotypes under Covariate Shift. ICML 267:72505-72534, 2025. e-Pub 2025.
- Diaz-Rincon, R, Liang, M, Ramirez-Zamora, A, Shickel, B. Uncertainty-Aware Prediction of Parkinson’s Disease Medication Needs: A Two-Stage Conformal Prediction Approach. MLHC 298, 2025. e-Pub 2025.
- Balch, JA, Ruppert, MM, Guan, Z, Buchanan, TR, Abbott, KL, Shickel, B, Bihorac, A, Liang, M, Upchurch, GR, Tignanelli, CJ, Loftus, TJ. Risk-Specific Training Cohorts to Address Class Imbalance in Surgical Risk Prediction. JAMA Surg 159(12), 2024. e-Pub 2024. PMID: 39382865.
- Liang, M, Park, J, Lu, Q, Zhong, X. Robust and flexible learning of a high-dimensional classification rule using auxiliary outcomes. Biometrics 80(4), 2024. e-Pub 2024. PMID: 39671275.
- Hou, T, Shen, X, Zhang, S, Liang, M, Chen, L, Lu, Q. AIGen: an artificial intelligence software for complex genetic data analysis. Brief Bioinform 25(6), 2024. e-Pub 2024. PMID: 39550221.
- Polcz, VE, Barrios, EL, Cox, MC, Rocha, I, Liang, M, Hawkins, RB, Darden, D, Ungaro, R, Dirain, M, Mankowski, R, Mohr, AM, Moore, FA, Moldawer, LL, Efron, PA, Brakenridge, S, Loftus, TJ. Severe trauma leads to sustained muscle loss, induced frailty, and distinct temporal changes in myokine and chemokine profiles of older patients. Surgery (United States) 176(5):1516-1524, 2024. e-Pub 2024. PMID: 39179433.
- Imran, M, Nguyen, B, Pensa, J, Falzarano, S, Sisk, AE, Liang, M, DiBianco, JM, Su, LM, Zhou, Y, Joseph, JP, Brisbane, WG, Shao, W. Image registration of in vivo micro-ultrasound and ex vivo pseudo-whole mount histopathology images of the prostate. Biomed Signal Process Control 96, 2024. e-Pub 2024.
- Ungaro, R, Xu, J, Kucaba, TA, Rao, M, Bergmann, CB, Brakenridge, S, Efron, PA, Goodman, MD, Gould, RW, Hotchkiss, RS, Liang, M, Mazer, MB, McGonagill, PW, Moldawer, LL, Remy, KE, Turnbull, IR, Caldwell, CC, Badovinac, VP, Griffith, TS. Development and optimization of a diluted whole blood ELISpot assay to test immune function. J Immunol Methods 533, 2024. e-Pub 2024. PMID: 39147231.
- Jiang, H, Imran, M, Muralidharan, P, Patel, A, Pensa, J, Liang, M, Benidir, T, Grajo, JR, Joseph, JP, Terry, R, DiBianco, JM, Su, LM, Zhou, Y, Brisbane, WG, Shao, W. MicroSegNet: A deep learning approach for prostate segmentation on micro-ultrasound images. Comput Med Imaging Graph 112, 2024. e-Pub 2024. PMID: 38211358.
- Li, D, Yao, Z, Liang, M, Liu, M. DeepJ: Graph Convolutional Transformers with Differentiable Pooling for Patient Trajectory Modeling. AMIA Annu Symp Proc 2024:734-743, 2024. e-Pub 2024. PMID: 41726469.
- Price, AD, Becker, ER, Barrios, EL, Mazer, MB, McGonagill, PW, Bergmann, CB, Goodman, MD, Gould, RW, Rao, M, Polcz, VE, Kucaba, TA, Walton, AH, Miles, S, Xu, J, Liang, M, Loftus, TJ, Efron, PA, Remy, KE, Brakenridge, S, Badovinac, VP, Griffith, TS, Moldawer, LL, Hotchkiss, RS, Caldwell, CC. Surviving septic patients endotyped with a functional assay demonstrate active immune responses. Front Immunol 15, 2024. e-Pub 2024. PMID: 39469706.
- Barrios, EL, Mazer, MB, McGonagill, PW, Bergmann, CB, Goodman, MD, Gould, RW, Rao, M, Polcz, VE, Davis, R, Del Toro, DE, Dirain, M, Dram, A, Hale, LO, Heidarian, M, Kim, CY, Kucaba, TA, Lanz, J, McCray, AE, Meszaros, S, Miles, S, Nelson, CR, Rocha, I, Silva, EE, Ungaro, R, Walton, AH, Xu, J, Zeumer-Spataro, L, Drewry, AM, Liang, M, Bible, LE, Loftus, TJ, Turnbull, IR, Efron, PA, Remy, KE, Brakenridge, S, Badovinac, VP, Griffith, TS, Moldawer, LL, Hotchkiss, RS, Caldwell, CC. Adverse outcomes and an immunosuppressed endotype in septic patients with reduced IFN-γ ELISpot. JCI Insight 9(2), 2024. e-Pub 2024. PMID: 38100268.
- Yang, S, Wu, Y, Liu, M, Bian, J, Liang, M, Guo, Y. Adjusting Covariate Misclassification in Electronic Health Records-Based Machine Learning Prediction Models. AMIA Annu Symp Proc 2024:1444-1453, 2024. e-Pub 2024. PMID: 41726448.
- Liang, M, Yu, M. Relative contrast estimation and inference for treatment recommendation. Biometrics 79(4):2920-2932, 2023. e-Pub 2023. PMID: 36645310.
- Mafee, M, Buhalog, B, Liang, M, Yu, M, Aylward, JL, Xu, YG. Length-to-width ratio in Mohs defects. Arch Dermatol Res 315(7):2163-2165, 2023. e-Pub 2023. PMID: 36877309.
- Yang, D, Wheeler, M, Karanth, SD, Aduse-Poku, L, Leeuwenburgh, C, Anton, SD, Guo, Y, Bian, J, Liang, M, Yoon, HS, Akinyemiju, TF, Braithwaite, D, Zhang, D. Allostatic load and risk of all-cause, cancer-specific, and cardiovascular mortality in older cancer survivors. Aging Cancer 4(2):74-84, 2023. e-Pub 2023. PMID: 37576467.
- Zhang, D, Spiropoulos, KA, Wijayabahu, A, Christou, DD, Karanth, SD, Anton, SD, Leeuwenburgh, C, Liang, M, Wheeler, M, Yang, D, Livingstone, AP, Mankowski, R, Cheng, TD, Zhang, H, Siegel, EM, Penedo, F, Licht, J, Braithwaite, D. Low muscle mass is associated with a higher risk of all–cause and cardiovascular disease–specific mortality in cancer survivors. Nutrition 107, 2023. e-Pub 2023. PMID: 36563433.
- Wang Z, Receveur JP, Pu J, Cong H, Richards C, Liang M, Chung H. Desiccation resistance differences in Drosophila species can be largely explained by variations in cuticular hydrocarbons. Elife 11, 2022. e-Pub 2022. PMID: 36473178.
- Liang M, Yu M. A semiparametric approach to model effect modification. J Am Stat Assoc, 2022. e-Pub 2022.
- Vardar BU, Meram E, Karaoglu K, Liang M, Yu M, Laeseke P, Ozkan OS. Radioembolization Followed by Transarterial Chemoembolization in Hepatocellular Carcinoma. Cureus 14(4):e23783, 2022. e-Pub 2022. PMID: 35518553.
- Liang M, Choi YG, Ning Y, Smith MA, Zhao YQ. Estimation and inference on high-dimensional individualized treatment rule in observational data using split-and-pooled de-correlated score. J Mach Learn Res 23, 2022. e-Pub 2022. PMID: 38098839.
- Li Y, Liang M, Mao L, Wang S. Robust estimation and variable selection for the accelerated failure time model. Stat Med 40(20):4473-4491, 2021. e-Pub 2021. PMID: 34031919.
- Park J, Liang M, Alpert JM, Brown RF, Zhong X. The Causal Relationship Between Portal Usage and Self-Efficacious Health Information-Seeking Behaviors: Secondary Analysis of the Health Information National Trends Survey Data. J Med Internet Res 23(1):e17782, 2021. e-Pub 2021. PMID: 33502334.
- Zhong X, Park J, Liang M, Shi F, Budd PR, Sprague JL, Dewar MA. Characteristics of Patients Using Different Patient Portal Functions and the Impact on Primary Care Service Utilization and Appointment Adherence: Retrospective Observational Study. J Med Internet Res 22(2):e14410, 2020. e-Pub 2020. PMID: 32130124.
- Liang M, Ye T, Fu H. Estimating individualized optimal combination therapies through outcome weighted deep learning algorithms. Stat Med 37(27):3869-3886, 2018. e-Pub 2018. PMID: 30014497.
- Zhong X, Liang M, Sanchez R, Yu M, Budd PR, Sprague JL, Dewar MA. On the effect of electronic patient portal on primary care utilization and appointment adherence. BMC Med Inform Decis Mak 18(1):84, 2018. e-Pub 2018. PMID: 30326876.
- Huling JD, Yu M, Liang M, Smith M. Risk prediction for heterogeneous populations with application to hospital admission prediction. Biometrics 74(2):557-565, 2018. e-Pub 2018. PMID: 29073325.
- Coriano CG, Liu F, Sievers CK, Liang M, Wang Y, Lim Y, Yu M, Xu W. A Computational-Based Approach to Identify Estrogen Receptor alpha/beta Heterodimer Selective Ligands. Mol Pharmacol 93(3):197-207, 2018. e-Pub 2018. PMID: 29295894.
- Liang M, Li Z, Chen T, Zeng J. Integrative Data Analysis of Multi-Platform Cancer Data with a Multimodal Deep Learning Approach. IEEE/ACM Trans Comput Biol Bioinform 12(4):928-37, 2015. e-Pub 2015. PMID: 26357333.
- Chen Y, Bhattacharya S, Liang M. Multi-task Learning for Semiparametric Models with Nuisance Parameters Fusion. J Am Stat Assoc.
- Radwan RM, Ser SE, Bian J, Bjarnadottir RI, Buchan IE, Collins GS, Dai H, Gerstenberg T, Groenwold RHH, Guo Y, Huntington-Klein N, Liang M, Lucero RJ, Nguyen T, Pan W, Sperrin M, Wang F, Xu H, Xu J, Zang C, Guo J, Prosperi M. The PREdiCtion of potential Outcomes under interventions Guideline (PRECOG). BMJ.
Review Articles
- Verma, H, Mistry, S, Jayam, KV, Shrestha, P, Adkins, L, Liang, M, Fares, A, Zarrinpar, A, Braithwaite, D, Karanth, SD. Artificial Intelligence in Oncology: A 10-Year ClinicalTrials. gov-Based Analysis Across the Cancer Control Continuum. Cancers 17(21), 2025. e-Pub 2025. PMID: 41228330.
- Liang M, Zhao YQ. Discussion of Kallus (2020) and Mo et al.(2020). J Am Stat Assoc, 2021. e-Pub 2021.
Book Chapters
- Liang M, Zhao YQ. Estimation and Inference for Individualized Treatment Rules Using Efficient Augmentation and Relaxation Learning. In: Statistics in Precision Health: Theory, Methods and Applications. Springer International Publishing.
Patient Reviews
CV information above last modified November 08, 2026