Aleksandr Y. Aravkin

WENDY: Covariance Dynamics Based Gene Regulatory Network Inference

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.

Trimmed Constrained Mixed Effects Models: Formulations and Algorithms.

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.

Fast and simple comparison of semi-structured data, with emphasis on electronic health records

The paper introduces a fast hashing method for comparing semi-structured data, demonstrating its use on electronic health records for duplicate detection and clustering.

Computer Assisted Localization of a Heart Arrhythmia

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

Learning Nonlinear Brain Dynamics: van der Pol Meets LSTM

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.