Leo Duan's Research Website

View My GitHub Profile

Hello, thanks for checking out my website.

I’m Leo Duan. I’m a statistician and an assistant professor at University of Florida since 2018.

Our research lab aims to build new statistical methods, theory and computational toolboxes for addressing motivating application problems in neuroscience, engineering, and transportation science. The main statistical interest is in modeling the combinatorial objects that are routinely used in science and engineering (e.g., tree graphs, clustering, signal pathways, integer flow networks, etc.). Our research generates interesting solutions at the intersection between combinatorics, optimization, and Bayesian statistics.


Research Interests

My recent research focuses on the following areas (listing recent works):

  1. Graph, Clustering & Bayes:
    • Yu Zheng and Leo L. Duan. An Elementary Proof of the Extended Aldous-Broder Theorem (2024+)
    • Leo L. Duan and Arkaprava Roy. High-dimensional Model-based Clustering using Uncountable Mixtures (2024+)
    • Edric Tam, David B. Dunson and Leo L. Duan. Exact Sampling of Spanning Trees via Fast-forwarded Random Walks (2024+)
    • Leo L. Duan and Anirban Bhattacharya. Graph-accelerated Markov Chain Monte Carlo. (2024+)
    • Leo L. Duan and David B. Dunson. Bayesian Spanning Tree: Estimating the Backbone of the Dependence Graph. JMLR 2024.
    • Leo L. Duan and Arkaprava Roy. Spectral Clustering, Spanning Forest, and Bayesian Forest Process. JASA, 2023.
    • Cheng Zeng, Jeffrey Miller and Leo L. Duan. Quasi-Bernoulli Stick-breaking: Infinite Mixture with Cluster Consistency. JMLR, 2023
    • Leo L. Duan, Zeyu Yuwen, George Michailidis and Zhengwu Zhang. Bayesian Vector Autoregression using the Tree Rank Prior. JMLR, 2023
    • Leo L. Duan, George Michailidis and Mingzhou Ding. Spiked Laplacian Graph. JMLR, 2022.
    • Leo L. Duan and David B. Dunson. Bayesian Distance Clustering. JMLR, 2021.
  2. Optimization & Bayes:

    • Leo L. Duan and Arkaprava Roy. Hierarchical Combinatorial Modeling using Polytope Priors. (2024+)
    • Yu Zheng and Leo L. Duan. Gibbs Sampling using Anti-correlation Gaussian Data Augmentation, with Applications to L1-ball-type Models. 2024+
    • Cheng Zeng, Eleni Dilma, Jason Xu and Leo L. Duan. Bridged Posterior: Optimization, Profile Likelihood and a New Approach for Generalized Bayes. * Joint first authors. 2024+
    • Maoran Xu and Leo L. Duan. Bayesian Inference with the L1-ball Prior: Solving Combinatorial Problems with Exact Zeros. JRSSB, 2023.
    • Maoran Xu, Hua Zhou, Yujie Hu and Leo L. Duan. Bayesian Inference using the Proximal Mapping: Uncertainty Quantification under Varying Dimensionality. JASA, 2023.
    • 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.

Selected Fundings and Awards

2023-2026 NSF Funding Award (PI)

2022 UF CLAS Faculty Travel Award

2022-2023 UFII SEED Funding Award

2021 UF Statistics Faculty Award for the Supervised Student (Maoran Xu)

2018 NeurIPS Bayesian Non-parametrics Award

2015 ASA Paper Competition Award in Section on Bayesian Statistical Science

2014 Woodside Foundation Award for Contribution in Biostatistics and Epidemiology Research

Recent and Upcoming Talks:

May 2023, Seminar Talk at Harvard University, Department of Biostatistics

January 2023, Seminar Talk at Texas A&M University, Department of Statistics

October 2022, International Conference on Bayesian Nonparametrics in Puerto Varas, Chile

Current and Former PhD students

Yaozhi Yang

Yu Zheng

Cheng Zeng

Eleni Dilma (Graduated 2024)

Maoran Xu (Graduated 2022)

Contact Info

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


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