A fuller list of publications can be found in my Google Scholar.

Selected Published Papers

• Localized LoRA: A Structured Low-Rank Approximation for Efficient Fine-Tuning
  International Conference on Machine Learning and Applications (IEEE ICMLA), 2025 PDF deep-learning optimization
• Stochastic Regret Guarantees for Online Zeroth- and First-Order Bilevel Optimization
  Neural Information Processing Systems (NeurIPS), 2025 PDF optimization bilevel-programming
• Covariate-dependent Graphical Model Estimation via Neural Networks with Statistical Guarantees
  Transactions on Machine Learning Research (TMLR), 2025 PDF · Code deep-learning graphical-models
• Inference for Change Points in High-dimensional Mean Shift Models
  Statistica Sinica, 2025 PDF change-points
• A Penalty-based Method for Communication-Efficient Decentralized Bilevel Programming
  Automatica, 2025 PDF bilevel-programming optimization
• Joint Learning of Linear Time-Invariant Dynamical Systems
  Automatica, 2024 PDF dynamical-systems
• A High-dimensional Approach to Measure Connectivity in the Financial Sector
  Annals of Applied Statistics (AoAS), 2024 PDF time-series high-dimensional-statistics
• High Dimensional Logistic Regression Under Network Dependence
  Journal of Machine Learning Research (JMLR), 2024 PDF high-dimensional-statistics
• Axiomatic Effect Propagation in Structural Causal Models
  Journal of Machine Learning Research (JMLR), 2024 PDF attribution
• A Functional Coefficients Network Autoregressive Model
  Statistica Sinica, 2024 PDF high-dimensional-statistics time-series
• A VAE-based Framework for Learning Multi-Level Neural Granger-Causal Connectivity
  Transactions on Machine Learning Research (TMLR), 2024 PDF · Code time-series deep-learning dynamical-systems
• Structural Discovery with Partial Ordering Information for Time-Dependent Data with Convergence Guarantees
  Journal of Computational and Graphical Statistics (JCGS), 2024 PDF · Code time-series high-dimensional-statistics optimization
• A General Modeling Framework for Network Autoregressive Processes
  Technometrics, 2023 PDF high-dimensional-statistics time-series
• Low Tree-rank Bayesian Vector Autoregression Models
  Journal of Machine Learning Research (JMLR), 2023 PDF high-dimensional-statistics time-series
• A Multi-Task Encoder-Dual-Decoder Framework for Mixed Frequency Data Prediction
  International Journal of Forecasting, 2023 PDF · Code time-series mixed-frequency-data deep-learning
• A Bayesian Framework for Sparse Estimation in High-dimensional Mixed Frequency Vector Autoregressive Models
  Statistica Sinica, 2023 PDF time-series mixed-frequency-data bayesian-methods
• The Bayesian Nested Lasso for Mixed Frequency Regression Models
  Annals of Applied Statistics (AoAS), 2023 PDF time-series mixed-frequency-data bayesian-methods
• Inference on the Change Point under a High Dimensional Covariance Shift
  Journal of Machine Learning Research (JMLR), 2023 PDF change-points
• Estimation of Gaussian Directed Acyclic Graphs using Partial Ordering Information with Applications to DREAM3 Networks and Dairy Cattle Data
  Annals of Applied Statistics (AoAS), 2023 PDF high-dimensional-statistics graphical-models
• Multiple Change Point Detection in Reduced Rank High Dimensional Vector Autoregressive Models
  Journal of the American Statistical Association (JASA), 2023 PDF change-points
• Bayesian Spiked Laplacian Graphs
  Journal of Machine Learning Research (JMLR), 2023 PDF network-modeling bayesian-methods
• DAdam: A Consensus-Based Distributed Adaptive Gradient Method for Online Optimization
  IEEE Transactions on Signal Processing (TSP), 2022 PDF optimization distributed-algorithms
• A Novel Data-Driven Approach for Solving the Electric Vehicle Charging Station Location-Routing Problem
  IEEE Transactions on Intelligent Transportation Systems, 2022 PDF routing-algorithms
• Regularized and Smooth Double Core Tensor Factorization for Heterogeneous Data
  Journal of Machine Learning Research (JMLR), 2022 PDF optimization tensor-decomposition high-dimensional-statistics
• Regularized high dimension low tubal-rank tensor regression
  Electronic Journal of Statistics (EJS), 2022 PDF optimization tensor-decomposition high-dimensional-statistics
• A Generalized Likelihood-based Bayesian Approach for Scalable Joint Regression and Covariance Selection in High Dimensions
  Statistics and Computing, 2022 PDF bayesian-methods high-dimensional-statistics
• Optimal Routing for Electric Vehicle Charging Systems with Stochastic Demand: A Heavy Traffic Approximation Approach
  European Journal of Operational Research, 2022 PDF routing-algorithms
• Fast and Scalable Algorithm for Detection of Structural Breaks in Big VAR Models
  Journal of Computational and Graphical Statistics (JCGS), 2022 PDF change-points high-dimensional-statistics
• Joint Estimation and Inference for Data Integration Problems based on Multiple Multi-layered Gaussian Graphical Models
  Journal of Machine Learning Research (JMLR), 2022 PDF · Code high-dimensional-statistics graphical-models

Selected Preprints

• Joint Learning of Panel VAR models with Low Rank and Sparse Structure
  Under Review, 2025 PDF high-dimensional-statistics time-series optimization
• Normalizing Flow to Augmented Posterior: Conditional Density Estimation with Interpretable Dimension Reduction for High Dimensional Data
  Under Review, 2025 PDF high-dimensional-statistics
• Neural Network-Based Change Point Detection for Large-Scale Time-Evolving Data
  Under Review, 2025 PDF deep-learning time-series change-points
• Deep Learning-based Approaches for State Space Models: A Selective Review
  Under Review, 2024 PDF deep-learning time-series
• A Generalized Bayesian Approach for High-dimensional Robust Regression with Serially Correlated Errors and Predictors
  Under Review, 2024 PDF high-dimensional-statistics bayesian-methods
• Bayesian Methodology for Adaptive Sparsity and Shrinkage in Regression
  Under Review, 2024 PDF high-dimensional-statistics bayesian-methods