CV

Education

• Ph.D. student, Statistics & Data Science — Carnegie Mellon University, 2025–present
  Advisors: Prof. Shixiang Zhu and Prof. Holly Wiberg
• M.S., Statistics — University of Southern California, 2022–2024
  Advisor: Prof. Paromita Dubey
• M.S., Statistics — University of Wisconsin–Madison, 2020–2022
  Advisors: Prof. Kris Sankaran and Prof. Keith Levin
• B.S., Statistics; B.S., Applied Mathematics — Renmin University of China, 2017–2021

Research interests

Conformal prediction and inference; uncertainty quantification; reliable and secure machine learning; scientific AI; human–AI collaboration and decision-making.

Publications

Generative Conformal Prediction with Optimized Coverage Allocation

Accepted to NeurIPS 2026Conference paper

Cite the current arXiv version: Minxing Zheng and Shixiang Zhu. (2024). "Generative Conformal Prediction with Vectorized Non-Conformity Scores." arXiv:2410.13735. Current arXiv preprint

Beyond Predicting Responses: Conformal Inference for Latent Distributional Parameters

PreprintarXiv preprint

Citation: Minxing Zheng, Wenbin Zhou, and Shixiang Zhu. (2026). "Beyond Predicting Responses: Conformal Inference for Latent Distributional Parameters." arXiv:2608.03607. Paper

Learning to Test: Physics-Informed Representation for Dynamical Instability Detection

PreprintarXiv preprint

Citation: Minxing Zheng, Zewei Deng, Liyan Xie, and Shixiang Zhu. (2026). "Learning to Test: Physics-Informed Representation for Dynamical Instability Detection." arXiv:2604.10967. Paper

MISLEADER: Defending against Model Extraction with Ensembles of Distilled Models

PreprintarXiv preprint

Citation: Xueqi Cheng, Minxing Zheng, Shixiang Zhu, and Yushun Dong. (2025). "MISLEADER: Defending against Model Extraction with Ensembles of Distilled Models." arXiv:2506.02362. Paper

Change Point Inference for Non-Euclidean Data Sequences using Distance Profiles

PreprintarXiv preprint; revised 2026

Citation: Paromita Dubey and Minxing Zheng. (2023; revised 2026). "Change Point Inference for Non-Euclidean Data Sequences using Distance Profiles." arXiv:2311.16025. Paper

Interactive Visualization and Representation Analysis Applied to Glacier Segmentation

JournalISPRS International Journal of Geo-Information

Citation: Minxing Zheng, Xinran Miao, and Kris Sankaran. (2022). "Interactive Visualization and Representation Analysis Applied to Glacier Segmentation." ISPRS International Journal of Geo-Information, 11(8), 415. Paper

Research projects

• Deciding When to Decide: Decision-Focused Testing under Distributional Shift — working paper, 2025–present
  A decision-focused testing framework for assessing whether a decision optimized in one domain remains approximately optimal after a context or feature distribution shift.
• Learning to Test: Physics-Informed Representation for Dynamical Instability Detection — 2025–present
  Physics-informed representation learning for efficient reliability testing under exogenous distribution shifts.
• Generative Conformal Prediction with Optimized Coverage Allocation (ORCA) — accepted to NeurIPS 2026
  Adaptive conformal uncertainty sets for multimodal targets with finite-sample validity. Cite the current arXiv preprint until the proceedings appear. Project page and interactive demo.
• Derandomized Multiple Change Point Detection with FDR Control using Distance Profiles — 2025–present
  Nonparametric change-point inference for metric-space objects, including extensions to multiple changes and false-discovery-rate control.
• Asymptotic Behavior of the Maximum Degree Distribution under Graphon Models — 2021–2022
  Bootstrap inference for maximum-degree distributions under latent graphon models.

Service & honors

• Reviewer: AISTATS, NeurIPS, ICLR, and ICML
• University of Southern California Marshall School Fellowship, 2022–2024

Selected methods & applications

Distribution-free inference, generative modeling, hypothesis testing under distribution shift, model security, representation analysis, geospatial machine learning, and statistical network analysis.

Professional links

Google Scholar · GitHub · arXiv · Email