Mingzhang Yin
- Assistant Professor
Location
- Warrington College of Business
- Marketing Department
- Stuzin Hall 260
Mingzhang Yin is an Assistant Professor of Marketing at the Warrington College of Business at the University of Florida. His primary research focuses on the areas of probabilistic machine learning, Bayesian methods, causal inference, with a focus on applications in online marketing, advertising, user generated content, and data-driven consumer analysis.
Expertise and interest areas
- Bayesian Methods
- Causal Inference
- Marketing Analytics
- Probabilistic machine learning
News
Loud budgeting | Mingzhang Yin – WalletHub
Meet Warrington’s new faculty for 2022 – September 2, 2022 – The Warrington College of Business is proud to welcome 11 new faculty members to campus in the 2022-2023 academic year. Learn more about these outstanding…
Courses taught
- Individual Work (MAR6905)
- Marketing Analytics 2 (MAR6669)
- Special Topics in Marketing (MAR6930)
- Supervised Research (MAR6910)
Education
- Ph.D, Statistics, General., University of Texas at Austin, 2019
Conference proceeding publications
- Score Identity Distillation: Exponentially Fast Distillation Of Pretrained Diffusion Models For One-Step Generation
- Journal: International Conference on Machine Learning (ICML)
- Status: Published
- Date: 2024
- Authors: Huangjie Zheng, Zhendong Wang, Mingyuan Zhou, Mingzhang Yin, Hai Huang
- Sel-Bald: Deep Bayesian Active Learning With Selective Labels
- Journal: Advances in Neural Information Processing Systems
- Status: Published
- Date: 2023
- Authors: Mingzhang Yin, Maytal Saar-Tsechansky, Ruijiang Gao
- Probabilistic Conformal Prediction Using Conditional Random Samples
- Journal: International Conference on Artificial Intelligence and Statistics (AISTATS)
- Status: Published
- Date: 2023
- Authors: Ruijiang Gao, David Blei, Zhendong Wang, Mingzhang Yin, Mingyuan Zhou
Journal article publications
- Probabilistic Machine Learning: New Frontiers For Modeling Consumers And Their Choices
- Journal: International Journal of Research in Marketing
- Status: Published
- Date: 2026
- Authors: Ryan Thomas. Dew, Nicolas Padilla, Lan E. Luo, Shin Oblander, Asim M. Ansari, Khaled Boughanmi, Michael Howard. Braun, Fred M. Feinberg, Jia Liu, Thomas Otter, Longxiu Tian, Yixin Wang, Mingzhang Yin
- Unraveling Multifaceted User Preferences On Digital Platforms: A Bayesian Deep-Learning Approach
- Journal: Marketing Science
- Status: Published
- Date: 2026
- Authors: Mingzhang Yin, Ziwei Cong, Jia Liu
- Unraveling Multifaceted User Preferences On Content Platforms: A Bayesian Deep Learning Approach
- Journal: Marketing Science
- Status: Published
- Date: 2026
- Authors: Mingzhang Yin, Ziwei Cong, Jia Liu
- Permutative Preference Alignment From Listwise Ranking Of Human Judgments
- Journal: Empirical Methods in Natural Language Processing
- Status: Published
- Date: 2025
- Authors: Yang Zhao, Yixin Wang, Mingzhang Yin
- Confounding-Robust Deferral Policy Learning
- Journal: Proceedings of the AAAI Conference on Artificial Intelligence
- Status: Published
- Date: 2025
- Authors: Ruijiang Gao, Mingzhang Yin
- Adjusting Regression Models For Conditional Uncertainty Calibration
- Journal: Machine Learning
- Status: Published
- Date: 2024
- Authors: Ruijiang Gao, Mingzhang Yin, James Mcinerney, Nathan Kallus
- Conformal Sensitivity Analysis For Individual Treatment Effects
- Journal: Journal of the American Statistical Association
- Status: Published
- Date: 2024
- Authors: Mingzhang Yin, Claudia Shi, Yixin Wang, David Meir. Blei
- Gradient Estimation For Binary Latent Variables Via Gradient Variance Clipping
- Journal: Proceedings of the AAAI Conference on Artificial Intelligence
- Status: Published
- Date: 2023
- Authors: Russell Z. Kunes, Mingzhang Yin, Max Land, Doron Haviv, Dana Pe'er, Simon Tavare
- Optimization-Based Causal Estimation From Heterogenous Environments
- Journal: Journal of Machine Learning Research
- Status: Published
- Date: 2023
- Authors: Mingzhang Yin, Yixin Wang, David Blei