I am currently a tenure-track associate researcher (副研究员) at School of Mathematics at 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. I am currently interested in statistics from a computational perspective, theory and practise for continuous convex/nonconvex optimization algorithms, and problems in modern large-scale genomic analyses.

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

Sparse Quantile Regression at the Biobank Scale

Qiang Heng, Xiaoqian Liu, Xiang Zhan

In Preparation

Efficent Kernel Regularized Learning via Quadratic Majorization Minorization with Exrapolation

Qiang Heng, Caixing Wang

In Preparation

Tactics for Improving Least Squares

Qiang Heng, Hua Zhou, Kenneth Lange

Under Review

Anderson Accelerated Operator Splitting Methods for Convex-nonconvex Regularized Problems

Qiang Heng, Xiaoqian Liu, Eric C. Chi

Under Review

📝 Selected Publications

JCGS

A Stability Framework for Parameter Selection in the Minimum Covariance Determinant Problem

Qiang Heng, Hui Shen, Kenneth Lange

Journal of Computational and Graphical Statistics (2025+)

• [paper][code][arXiv]

Tech

Robust Low-rank Tensor Decomposition with the L2 Criterion

Qiang Heng, Eric C. Chi, Yufeng Liu

Technometrics, 2023

• [paper][code][arXiv]

JCGS

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

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

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

• FreeMatch: Self-adaptive Thresholding for Semi-supervised Learning [arXiv] 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).

📖 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.