Use of evolutionary computation techniques for exploration and prediction of helicopter loads. - Catherine Cheung; Julio J. Valdés; Matthew Li (IEEE Congress on Evolutionary Computation, 2012)

Towards conservative helicopter loads prediction using computational intelligence techniques. - Julio J. Valdés; Catherine Cheung; Matthew Li (IJCNN, 2012)

Sensor dynamics in high dimensional phase spaces via nonlinear transformations: Application to helicopter loads monitoring. - Julio J. Valdés; Catherine Cheung; Matthew Li (CIDM, 2014)

Cluster Usage Policy Enforcement Using Slurm Plugins and an HTTP API. - Matthew Li; Nicolas Chan; Viraat Chandra; Krishna Muriki (PEARC, 2020)

Accurate and Robust Deep Learning Framework for Solving Wave-Based Inverse Problems in the Super-Resolution Regime. - Matthew Li; Laurent Demanet; Leonardo Zepeda-Núñez (CoRR, 2021)

Redatuming physical systems using symmetric autoencoders. - Pawan Bharadwaj; Matthew Li; Laurent Demanet (CoRR, 2021)

Using Physics-Informed Generative Adversarial Networks to Perform Super-Resolution for Multiphase Fluid Simulations. - Matthew Li; Christopher McComb (J. Comput. Inf. Sci. Eng., 2022)

Wide-Band Butterfly Network: Stable and Efficient Inversion Via Multi-Frequency Neural Networks. - Matthew Li; Laurent Demanet; Leonardo Zepeda-Núñez (Multiscale Model. Simul., 2022)

A Convolutional Neural Network for Beamforming and Image Reconstruction in Passive Cavitation Imaging. - Hossein J. Sharahi; Christopher N. Acconcia; Matthew Li; Anne Martel; Kullervo Hynynen (Sensors, 2023)

SPADE-S: A Sparsity-Robust Foundational Forecaster. - Malcolm Wolff; Matthew Li; Ravi Kiran Selvam; Hanjing Zhu; Kin G. Olivares; Ruijun Ma; Abhinav Katoch; Shankar Ramasubramanian; Mengfei Cao; Roberto Bandarra; Rahul Gopalsamy; Stefania La Vattiata; et al. (CoRR, 2025)