Hello, thanks for checking out my website.

I’m Leo Duan. I’m a statistician and an Associate Professor at the University of Florida.

My research focuses on the interface between optimization and Bayes.

The goal of our research group is to develop new statistical and machine learning toolboxes that just work – which means simple implementation, fast computation, and principled uncertainty quantification.

Achieving this goal is not trivial, which is why we’ve been working to show how one can borrow strengths from two communities: Bayes, who are good at probabilistic modeling, and optimization, who are good at efficient computing. Check out our work below on building optimization-based priors, optimization-based likelihoods, and optimization-based generative models, and feel free to reach out with any questions.

My statisical interest is largely motivated by ongoing collaborative work in neuroscience, engineering, and transportation science.

** My CV can be found** here (updated 2025 May)

Some annoucements!

• Lab openning: I’m looking to advise new doctoral students to work on optimization and diffusion models. If you are currently enrolled in UF graduate program & are interested in doing research with me, send an email to li dot duan at ufl dot edu.

Research Interests

Selected forthcoming work (please email me for latest manuscript):

• Zitian Wu, Arkaprava Roy and Leo L. Duan. Model-based Inference for Persistent Homology.

Selected recent work (pre-print and accepted):

• Yu Zheng, Malay Ghosh and Leo L. Duan. Statistical Modeling of Combinatorial Response Data. (Under Review at JASA).
• Cheng Zeng, Eleni Dilma, Jason Xu and Leo L. Duan. Bridged Posterior: Optimization, Profile Likelihood and a New Approach for Generalized Bayes. (Revision at JASA)
• Cheng Zeng, Yaozhi Yang, Jason Xu and Leo L. Duan. Gradient-Bridged Posterior: Bayesian Inference for Models with Implicit Function.
• Edric Tam, David B. Dunson and Leo L. Duan. Exact Sampling of Spanning Trees via Fast-forwarded Random Walks. Biometrika 2025.
• Leo L. Duan and Anirban Bhattacharya. Graph-accelerated Markov Chain Monte Carlo. (Accepted by JMLR pending minor revision).
• Yu Zheng and Leo L. Duan. Gibbs Sampling using Anti-correlation Gaussian Data Augmentation, with Applications to L1-ball-type Models. JCGS 2025.
• Yu Zheng, Leo L. Duan and Arkaprava Roy. Consistency of Graphical Model-based Clustering: Robust Clustering using Bayesian Spanning Forest 2025. (Under Review at Bernoulli)
• Leo L. Duan and David B. Dunson. Bayesian Spanning Tree: Estimating the Backbone of the Dependence Graph. JMLR 2024.
• Maoran Xu and Leo L. Duan. Bayesian Inference with the L1-ball Prior: Solving Combinatorial Problems with Exact Zeros. JRSS-B, 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 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.
• 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

2024 UF CLAS Fellowship for Doctoral Student Supervised

2023-2026 NSF-ATD: Geospatial Modeling and Risk Mitigation for Human Movement Dynamics under Hurricane Threats (PI)

2022 UF CLAS Faculty Travel Award

2022-2023 UFII SEED Funding Award

2021 UF Statistics Faculty Award for Doctoral Student Supervised

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:

August 2025, EcoSta, Tokyo Japan

August 2025, Joint Statistical Meetings, Nashville TN

June 2025, BayesComp, Singapore

May 2025, Statistical Methods in Imaging Conference, Houston, TX

Current PhD Students

Yu Zheng (Expected to graduate in Fall 2025)

Past Trainees

Cheng Zeng

Zeyu Yuwen (Co-advised with George Michailidis)

Edric Tam (Currently postdoctoral fellow at Stanford University)

Eleni Dilma (Co-advised with Brenda Betancourt, first job placement: Food and Drug Administration)

Maoran Xu (Assistant Professor, first job placement: Indiana University)