Peng Zheng

WENDY infers gene regulatory networks from single-cell gene expression data with time-course interventions by modeling covariance dynamics, showing good performance on synthetic and experimental data.

This paper introduces Trimmed Constrained Mixed Effects Models with efficient algorithms and an open-source Python package, showing improved accuracy and computational efficiency in handling outliers and nonlinear data.

The paper develops an optimization algorithm to locate heart arrhythmias using catheter data and validates it with simulations.

The paper introduces a nonlinear differential equation model for brain dynamics using van der Pol oscillators and improves LSTM performance through model-specific data augmentation.