Bianisotropic Effective Parameters of Optical Metamagnetics and Negative-Index Materials. - Alexander V. Kildishev; Joshua D. Borneman; Xingjie Ni; Vladimir M. Shalaev; Vladimir P. Drachev (Proc. IEEE, 2011)

Numerical Modeling of Plasmonic Nanoantennas with Realistic 3D Roughness and Distortion. - Alexander V. Kildishev; Joshua D. Borneman; Kuo-Ping Chen; Vladimir P. Drachev (Sensors, 2011)

Subwavelength optics with hyperbolic metamaterials: Waveguides, scattering, and optical topological transitions. - Satoshi Ishii; Viktoriia E. Babicheva; Mikhail Y. Shalaginov; Alexandra Boltasseva; Alexander V. Kildishev; Evgenii Narimanov (ICTON, 2016)

A high-order accurate scheme for Maxwell's equations with a generalized dispersive material model. - Jordan B. Angel; Jeffrey W. Banks; William D. Henshaw; Michael J. Jenkinson; Alexander V. Kildishev; Gregor Kovacic; Ludmila J. Prokopeva; Donald W. Schwendeman (J. Comput. Phys., 2019)

Intelligent Computing with Photonic Memories. - Mario Miscuglio; Omer Yesiliurt; Jiawei Meng; Ludmila J. Prokopeva; Yifei Zhang; Armin Mehrabian; Juejun Hu; Alexander V. Kildishev; Volker J. Sorger (OFC, 2020)

A high-order accurate scheme for Maxwell's equations with a Generalized Dispersive Material (GDM) model and material interfaces. - Jeffrey W. Banks; Benjamin Brett Buckner; William D. Henshaw; Michael J. Jenkinson; Alexander V. Kildishev; Gregor Kovacic; Ludmila J. Prokopeva; Donald W. Schwendeman (J. Comput. Phys., 2020)

Gaussian dispersion analysis in the time domain: Efficient conversion with Padé approximants. - Ludmila J. Prokopeva; Samuel Peana; Alexander V. Kildishev (Comput. Phys. Commun., 2022)

High-order accurate schemes for Maxwell's equations with nonlinear active media and material interfaces. - Qing Xia 006; Jeffrey W. Banks; William D. Henshaw; Alexander V. Kildishev; Gregor Kovacic; Ludmila J. Prokopeva; Donald W. Schwendeman (J. Comput. Phys., 2022)

Optimal Poloidal Multipole Expansion Centres. - Alexander V. Kildishev; Karim Achouri; Daria Smirnova (ICTON, 2024)

PearSAN: A Machine Learning Method for Inverse Design using Pearson Correlated Surrogate Annealing. - Michael Bezick; Blake Wilson; Vaishnavi Iyer; Yuheng Chen; Vladimir M. Shalaev; Sabre Kais; Alexander V. Kildishev; Alexandra Boltasseva; Brad Lackey (CoRR, 2024)

Machine-Learning-Assisted Photonic Device Development: A Multiscale Approach from Theory to Characterization. - Yuheng Chen; Alexander Montes McNeil; Taehyuk Park; Blake Wilson; Vaishnavi Iyer; Michael Bezick; Jae-Ik Choi; Rohan Ojha; Pravin Mahendran; Daksh Kumar Singh; Geetika Chitturi; Peigang Chen; et al. (CoRR, 2025)