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Research Interests:
Research Interests:
A/B tests and online controlled experiments
Uncertainty quantification, design and modeling of computer experiments
Bayesian Optimization
Adaptive Design for User Preference Elicitation
A/B tests and online controlled experiments
A/B tests and online controlled experiments
Network A/B Tests
Network A/B Tests
Zhang, Q. (2025), Rerandomization Algorithms for Optimal Designs of Network A/B Tests. Technometrics. Accepted. [Preprint][slides][Supp]
A/B tests with network and covariates
A/B tests with network and covariates
Zhang, Q. and Kang, L. (2022), Locally Optimal Design for A/B Tests in the Presence of Covariates and Network Dependence. Technometrics. 64.3: 358-369. [code]
Collaborative Experiments (CoE)
Collaborative Experiments (CoE)
Fisher, W*, Zhang, Q., Kang, L, and Deng, X, Collaborative Design of Controlled Experiments in the Presence of Subject Covariates.
Zhang, Q., Kang, L., and Deng, X. (2025) Collaborative Analysis for Paired A/B Testing Experiments. Statistica Sinica. Accepted.
A/B tests for Personalized Decisions
A/B tests for Personalized Decisions
Zhang, Q., Khademi, A. and Song, Y. (2022), Min-Max Optimal Design of Two-Armed Trials with Side Information. INFORMS Journal on Computing. 34:1, 165-182. [code]
Uncertainty quantification, design and modeling of computer experiments
Uncertainty quantification, design and modeling of computer experiments
Zhang, Q. , Qian, P. Z. G. (2013), Designs for crossvalidating approximation models. Biometrika. 100(4), 997-1004.
Zhang, Q., Chien, P. Z. G., Liu, Q., Xu, L., Hong, Y. (2021), Mixed-input Gaussian process emulators for computer experiments with a large number of categorical levels. Journal of Quality Technology, 53(4), 410-420.
Zhang, T.* and Zhang, Q. (2021), On the Interface Between Nested Designs and the Multi-step Interpolator. Journal of Statistical Theory and Practice, 15 (4): 1-19.
Li, Y.*, Zhang, Q. Limaye, M., and Li, G., Uncertainty Estimation of the Optimal Decision with Application to Cure Process Optimization.
Bayesian optimization
Bayesian optimization
Zhang, Q., and Hwang, Y. (2020), Sequential Model-based Optimization for Continuous Inputs with Finite Decision Space. Technometrics, 62.4: 486-498.
Wang, B., Zhang, Q., Xie, W. (2019), Bayesian Sequential Data Collection for Stochastic Simulation Calibration, European Journal of Operational Research, 277 (1), 300-316.
Chen, Y., Zhang, Q., Li, M., Cai, W. (2022), Sequential Selection for Accelerated Life Testing via Approximate Bayesian Inference. Naval Research Logistics. 69 (2), 336-351.
Kerfonta, C.*, Kim, S., Chen, Y., Zhang, Q., Jiang, M. (2024) Sequential Selection for Minimizing the Variance with Application to Crystallization Experiments. The American Statistician. 78 (4), 391-400.
Adaptive design for user preference elicitation
Adaptive design for user preference elicitation
Fisher, W.*, Zhang, Q., Song, Y, Gorsich, D, Hartman, G. and Skowronska, A. (2022), Bayesian Sequential Preference Elicitation: A Tradespace Exploration Framework with Application in Vehicle Concept Design, Proceedings of IISE Annual Conference and Expo, 2022, 894-899. (Winner, Best Paper Award of the Operations Research Track, IISE Annual Conference & Expo 2022)
Fisher, W.*, Zhang, Q., and Song, Y. (2024), Batch Sequential Designs in Bayesian Preference Elicitation with Application to Tradespace Exploration. Journal of Quality Technology, 57 (2), 115-134.
Fisher, W*, Zhang, Q., and Song. Y. (2025), Approximate Dynamic Programming Methods in Bayesian Preference Elicitation. Quality Engineering, 37 (3), 475-492.
Selected Funded Projects:
Selected Funded Projects:
Experimental Design, Uncertainty Quantification and Decision Making for Complex Systems, NSF, PI, 2024-2027.
NRT-AI: Harnessing AI for Inverse Design Training in Advanced and Sustainable Composites (IDeAS Composites), NSF, senior personnel, 2023-2028.
Statistical Experimental Design for Modern Information Collection, Simons Foundation, PI, 2022-2027.
Artificially Intelligent Manufacturing Paradigm for Composites (AIM for Composites), DOE, co-PI, 2022-2026.
Data-driven Optimal Compensation for 3D Printing, ORAU Ralph E Powe Junior Faculty Enhancement Award, PI, 2020-2021.
Statistical Aspects of Computer Experiments, AMS-Simons Travel Grant, Simons foundation, PI, 2018-2020.
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