Hello, thanks for checking out my website.

I’m Leo Duan. I’m a statistician and an assistant professor working at University of Florida since 2018. Prior to that, I obtained my PhD in Mathematics at University of Cincinnati in 2015 under the supervision of Rhonda Szczesniak and Xia Wang, worked a year as a “data scientist” in the tech sector, and spent two years as a postdoc working with David Dunson at Johns Hopkins and Duke University.

Research Interests

My recent research focuses on the following areas (with some representative works):

1. Optimization & Bayes:

   • Maoran Xu, Hua Zhou, Yujie Hu and Leo L. Duan. Bayesian Inference using the Proximal Mapping: Uncertainty Quantification under Varying Dimensionality. (revision submitted to JASA 2022) https://arxiv.org/abs/2108.04851
   • Maoran Xu and Leo L. Duan. Bayesian Inference with the l1-ball Prior: Solving Combinatorial Problems with Exact Zeros. (revision submitted to JRSSB 2022) https://arxiv.org/abs/2006.01340
   • Leo L. Duan. High-Accuracy Posterior Approximation via Random Transport. JASA, 2021.
   • Leo L. Duan. Latent Simplex Position Model. JMLR, 2020.
   • Leo L. Duan, Alex Young, Akihiko Nishimura, and David B. Dunson. Bayesian Constraint Relaxation. Biometrika 2019.
   • Leo L. Duan, James E. Johndrow, and David B. Dunson. Scaling up Data Augmentation MCMC via Calibration. JMLR, 2018.

2. Graph, Clustering & Bayes:

   • Leo L. Duan, George Michailidis and Mingzhou Ding. Spiked Laplacian Graph. JMLR, 2022. http://arxiv.org/abs/1910.02471
   • Leo L. Duan and Arkaprava Roy. Spectral Clustering, Spanning Forest, and Bayesian Forest Process. 2022+ https://arxiv.org/abs/2202.00493
   • Cheng Zeng, Jeffrey Miller and Leo L. Duan. Quasi-Bernoulli Stick-breaking: Infinite Mixture with Cluster Consistency. (revision at JMLR 2022) https://arxiv.org/abs/2008.09938
   • Leo L. Duan and David B. Dunson. Bayesian Spanning Tree: Estimating the Backbone of the Dependence Graph. 2022+. https://arxiv.org/abs/2106.16120
   • Zeyu Yuwen, George Michailidis, Zhengwu Zhang and Leo L. Duan. Bayesian Vector Autoregression using the Tree Rank Prior. 2022+ https://arxiv.org/abs/2204.01573
   • Leo L. Duan and David B. Dunson. Bayesian Distance Clustering. JMLR, 2021.

Current and Former PhD students

Maoran Xu (Graduated 2022),

Eleni Dilma,

Cheng Zeng,

Yu Zheng,

Yaozhi Yang

Contact Info

PhD student interested in working with us? Send me an email! li dot duan at ufl dot edu

Academic Services

Associate Editor of

Data Science in Science

Reviewer for

AISTATS, Bayesian Analysis, Bernoulli, Biometrics, Journal of Machine Learning Research, Journal of the American Statistical Association, Statistics in Medicine, Statistical Sinica, NeurIPS

Publications

For the up-to-date list of publications and pre-prints, see https://scholar.google.com/citations?user=4i5UQLAAAAAJ&hl=en

• Badea, Alexandra, Jacques A. Stout, Robert J. Anderson, Gary P. Cofer, Leo L. Duan, and Joshua T. Vogelstein. “Imaging Biomarkers for Alzheimer’s Disease Using Magnetic Resonance Microscopy.” Magnetic Resonance Microscopy: Instrumentation and Applications in Engineering, Life Science, and Energy Research (2022).
• Zeyu Yuwen, George Michailidis, Zhengwu Zhang and Leo L. Duan. Bayesian Vector Autoregression using the Tree Rank Prior. 2022+ https://arxiv.org/abs/2204.01573
• Leo L. Duan and Arkaprava Roy. Spectral Clustering, Spanning Forest, and Bayesian Forest Process. 2022+ https://arxiv.org/abs/2202.00493
• Maoran Xu, Hua Zhou, Yujie Hu and Leo L. Duan. Bayesian Inference using the Proximal Mapping: Uncertainty Quantification under Varying Dimensionality. 2021+ https://arxiv.org/abs/2108.04851
• Maoran Xu and Leo L. Duan. Bayesian Inference with the l1-ball Prior: Solving Combinatorial Problems with Exact Zeros. 2022+ https://arxiv.org/abs/2006.01340
• Leo L. Duan and David B. Dunson. Bayesian Spanning Tree: Estimating the Backbone of the Dependence Graph. 2022+. https://arxiv.org/abs/2106.16120
• Maoran Xu, Meng Li and Leo L. Duan. Bayesian Multi-scale Modeling of Factor Matrix without using Partition Tree. 2022+ https://arxiv.org/abs/2002.09606
• Leo L. Duan, George Michailidis and Mingzhou Ding. Spiked Laplacian Graph. 2022+. http://arxiv.org/abs/1910.02471
• Leo L. Duan. High-Accuracy Posterior Approximation via Random Transport. Journal of the American Statistical Association, 2021.
• Leo L. Duan and David B. Dunson. Bayesian Distance Clustering. Journal of Machine Learning Research, 2021.
• Leo L. Duan. Latent Simplex Position Model. Journal of Machine Learning Research, 2020.
• Tikhonov, Gleb, Leo L. Duan, Nerea Abrego, Graeme Newell, Matt White, David Dunson, and Otso Ovaskainen. Computationally efficient joint species distribution modeling of big spatial data. Ecology 101, no. 2 (2020): e02929.
• Szczesniak, Rhonda D., Teresa Pestian, Leo L. Duan, Dan Li, Sophia Stamper, Brycen Ferrara, Elizabeth Kramer, John P. Clancy, and Daniel Grossoehme. Data driven decision making to characterize clinical personas of parents of children with cystic fibrosis: a mixed methods study. BMC pulmonary medicine 20, no. 1 (2020): 1-14.
• Leo L. Duan, Alex Young, Akihiko Nishimura, and David B. Dunson. Bayesian Constraint Relaxation. Biometrika 2019.
• Yue Bai and Leo L. Duan. Tuning-Free Disentanglement via Projected Variational Autoencoder 2019.
• Leo L. Duan, Rhonda D. Szczesniak, and Xia Wang. Mixed-Stationary Gaussian Process for Flexible Non-Stationary Modeling of Spatial Outcomes. 2018.
• Leo L. Duan, James E. Johndrow, and David B. Dunson. Scaling up Data Augmentation MCMC via Calibration. Journal of Machine Learning Research, 2018.
• Leo L. Duan and Jeffrey W. Miller. Distribution-based Clustering using Characteristic Function. NeurIPS Bayesian Nonparametrics Workshop 2018.
• Leo L. Duan, Rhonda D. Szczesniak, and Xia Wang. Functional Inverted-Wishart for Bayesian Multivariate Spatial Modeling with Application to Regional Climatology Model Data. Environmetrics, 2017.
• Leo L. Duan, John P. Clancy, and Rhonda D. Szczesniak. Bayesian Ensemble Trees for Clustering and Prediction in Heterogeneous Data. Journal of Computational and Graphical Statistics, 25(3):748–761, 2016.
• Otso Ovaskainen, Gleb Tikhonov, Anna Norberg, F. Guillaume Blanchet, Leo L. Duan, David B. Dunson, Tomas Roslin, and Nerea Abrego. How to Make More Out of Community Data? A Conceptual Framework and Its Implementation as Models and Software. Ecology Letters, 20(5):561–576, 2017.
• Leo L. Duan, John P. Clancy, and Rhonda D. Szczesniak. Joint Hierarchical Gaussian Process Model with Application to forecast in Medical Monitoring. STAT 2017.
• Judith W Dexheimer, Eric S Kirkendall, Michal Kouril, Philip A Hagedorn, Thomas Minich, Leo L. Duan, Monifa Mahdi, Rhonda D. Szczesniak, S andrew Spooner, et al. The Effects of Medication Alerts on Prescriber Response in a Pediatric Hospital. Applied Clinical Informatics, 8(2):491–501, 2016.
• Rhonda D. Szczesniak, Dan Li, Leo L. Duan, Mekibib Altaye, Menachem Miodovnik, and Jane C Khoury. Longitudinal Patterns of Glycemic Control and Blood Pressure in Pregnant Women with Type 1 Diabetes Mellitus: Phenotypes From Functional Data Analysis. American Journal of Perinatology, 33(13):1282–1290, 2016.
• Kavitha Kotha, Rhonda D. Szczesniak, Anjaparavanda P Naren, Matthew C Fenchel, Leo L. Duan, Gary L McPhail, and John P. Clancy. Concentration of Fractional Excretion of Nitric Oxide: A Potential Airway Biomarker of Restored Cftr Function. Journal of Cystic Fibrosis, 14(6):733–740, 2015.
• Rhonda D. Szczesniak, Leo L. Duan, Gary L McPhail, Barbara B. Chini, Laurie Kahill, Maurizio Macaluso, Raouf S. Amin, and John P. Clancy. Determinants for the Early Onset of Rapid FEV1 Decline in Cystic Fibrosis. Pediatric Pulmonology, 48:368, 2013.
• Rhonda D. Szczesniak, Gary L. McPhail, Leo L. Duan, Maurizio Macaluso, Raouf S Amin, and John P. Clancy. A Semiparametric Approach to Estimate Rapid Lung Function Decline in Cystic Fibrosis. Annals of Epidemiology, 23(12):771–777, 2013.