I am currently an associate researcher (副研究员) at School of Statistics and Data Science, Southeast University in Nanjing, Jiangsu, China. Previously, I was a postdoctoral scholar at Department of Computational Medicine, UCLA, working with Dr. Kenneth Lange and Dr. Hua Zhou. Prior to that, I received my Ph.D. from North Carolina State University, where I primarily worked with Dr. Eric C. Chi. My current research interests include statistical genomics, numerical optimization, and computational biology.

Undergraduate and graduate students at Southeast University interested in doing a thesis with me are welcome to email me at heng.qiang6@gmail.com.

📝 Preprints & In Preparation

• Discovering and Dissecting Heterogeneous Associations with Genome-wide Smoothed Quantile Regression
  Heng et al.
  In Preparation

• Integrated Quantile Knockoffs
  Heng et al.
  In Preparation

• An Interpretable and Scalable Framework for Evaluating Large Language Models
  Xinhao Qu, Qiang Heng, Hao Zeng, Xiaoqian Liu
  Under Review

• Improved Statistical Analysis for Spectral Algorithms under General Conditions: Optimality and Robustness
  Caixing Wang, Qiang Heng, Qi Kuang, Xingdong Feng
  Major revision, Journal of American Statistical Association

• Inertial Quadratic Majorization Minorization with Application to Kernel Regularized Learning
  Qiang Heng, Caixing Wang
  Under Review

📝 Selected Publications

• Tactics for Improving Least Squares Estimation
  Qiang Heng, Hua Zhou, Kenneth Lange
  Statistical Science (accepted, 2026+)
  [code] [arXiv]

• A Stability Framework for Parameter Selection in the Minimum Covariance Determinant Problem
  Qiang Heng, Hui Shen, Kenneth Lange
  Journal of Computational and Graphical Statistics, 2026
  [paper] [code] [arXiv]

• Robust Low-rank Tensor Decomposition with the L2 Criterion
  Qiang Heng, Eric C. Chi, Yufeng Liu
  Technometrics, 2023
  [paper] [code] [arXiv]

• Bayesian Trend Filtering via Proximal Markov Chain Monte Carlo
  Qiang Heng, Hua Zhou, Eric C. Chi
  Journal of Computational and Graphical Statistics, 2023
  [paper] [code] [arXiv]

📝 Other Publications

• Anderson Accelerated Operator Splitting Methods for Convex-nonconvex Regularized Problems
  Qiang Heng, Xiaoqian Liu, Eric C. Chi
  IEEE Open Journal of Signal Processing, 2025
  [paper] [code]

• Bootstrap Estimation of the Proportion of Outliers in Robust Regression Models
  Qiang Heng, Kenneth Lange
  Statistics and Computing, 2025
  [paper] [code]

• Proximal MCMC for Bayesian Inference of Constrained and Regularized Estimation
  Xinkai Zhou, Qiang Heng, Eric C. Chi, Hua Zhou
  The American Statistician, 2024
  [paper]

• FreeMatch: Self-adaptive Thresholding for Semi-supervised Learning
  Yidong Wang, Hao Chen, Qiang Heng, Wenxin Hou, Yue Fan, Zhen Wu, Jindong Wang, Marios Savvides, Takahiro Shinozaki, Bhiksha Raj, Bernt Schiele, Xing Xie
  The Eleventh International Conference on Learning Representations (ICLR 2023)
  [arXiv]

📖 Educations

• 2019.08 - 2023.12, Ph.D. Statistics, North Carolina State University.
• 2015.09 - 2019.06, B.S. Statistics, Shanghai University of Finance and Economics.