Catoms: Moving Robots Without Moving Parts. - Brian T. Kirby; Jason Campbell; Burak Aksak; Padmanabhan Pillai; James F. Hoburg; Todd C. Mowry; Seth Copen Goldstein (AAAI, 2005)

Claytronics: highly scalable communications, sensing, and actuation networks. - Burak Aksak; Preethi Srinivas Bhat; Jason Campbell; Michael DeRosa; Stanislav Funiak; Phillip B. Gibbons; Seth Copen Goldstein; Carlos Guestrin; Ashish Gupta 003; Casey Helfrich; James F. Hoburg; Brian T. Kirby; et al. (SenSys, 2005)

A modular robotic system using magnetic force effectors. - Brian T. Kirby; Burak Aksak; Jason Campbell; James F. Hoburg; Todd C. Mowry; Padmanabhan Pillai; Seth Copen Goldstein (IROS, 2007)

Design of prismatic cube modules for convex corner traversal in 3D. - Michael Philetus Weller; Brian T. Kirby; H. Benjamin Brown; Mark D. Gross; Seth Copen Goldstein (IROS, 2009)

Beyond Audio and Video: Using Claytronics to Enable Pario. - Seth Copen Goldstein; Todd C. Mowry; Jason Campbell; Michael P. Ashley-Rollman; Michael DeRosa; Stanislav Funiak; James F. Hoburg; Mustafa Emre Karagozler; Brian T. Kirby; Peter Lee 001; Padmanabhan Pillai; James Robert Reid; et al. (AI Mag., 2009)

Blinky blocks: a physical ensemble programming platform. - Brian T. Kirby; Michael P. Ashley-Rollman; Seth Copen Goldstein (CHI Extended Abstracts, 2011)

Polarization Dependent Loss in Optical Fibers - Does it Help or Ruin Photon Entanglement Distribution? - Daniel E. Jones; Brian T. Kirby; Michael Brodsky (OFC, 2018)

On the experimental feasibility of quantum state reconstruction via machine learning. - Sanjaya Lohani; Thomas A. Searles; Brian T. Kirby; Ryan T. Glasser (CoRR, 2020)

Machine learning assisted quantum state estimation. - Sanjaya Lohani; Brian T. Kirby; Michael Brodsky; Onur Danaci; Ryan T. Glasser (Mach. Learn. Sci. Technol., 2020)

Improving application performance with biased distributions of quantum states. - Sanjaya Lohani; Joseph M. Lukens; Daniel E. Jones; Thomas A. Searles; Ryan T. Glasser; Brian T. Kirby (CoRR, 2021)

Machine learning pipeline for quantum state estimation with incomplete measurements. - Onur Danaci; Sanjaya Lohani; Brian T. Kirby; Ryan T. Glasser (Mach. Learn. Sci. Technol., 2021)

Telecom-band Hyperentangled Photon Pairs from a Fiber-based Source. - Changjia Chen; Calvin Xu; Arash Riazi; Eric Y. Zhu; Alexander Greenwood; Alexey V. Gladyshev; Peter G. Kazansky; Brian T. Kirby; Li Qian (OFC, 2022)

Demonstration of machine-learning-enhanced Bayesian quantum state estimation. - Sanjaya Lohani; Joseph M. Lukens; Atiyya A. Davis; Amirali Khannejad; Sangita Regmi; Daniel E. Jones; Ryan T. Glasser; Thomas A. Searles; Brian T. Kirby (CoRR, 2022)

Data-centric machine learning in quantum information science. - Sanjaya Lohani; Joseph M. Lukens; Ryan T. Glasser; Thomas A. Searles; Brian T. Kirby (Mach. Learn. Sci. Technol., 2022)

Computational Simulation Framework for Tactical Quantum Network Applications. - Dashiell L. P. Vitullo; Trevor Cook; Daniel E. Jones; Lisa M. Scott; Brian T. Kirby (MILCOM, 2023)

Dimension-adaptive machine learning-based quantum state reconstruction. - Sanjaya Lohani; Sangita Regmi; Joseph M. Lukens; Ryan T. Glasser; Thomas A. Searles; Brian T. Kirby (Quantum Mach. Intell., 2023)

Deep learning for enhanced free-space optical communications. - Manon P. Bart; Nicholas J. Savino; Paras Regmi; Lior Cohen; Haleh Safavi; Harry C. Shaw; Sanjaya Lohani; Thomas A. Searles; Brian T. Kirby; Hwang Lee; Ryan T. Glasser (Mach. Learn. Sci. Technol., 2023)

SMC Is All You Need: Parallel Strong Scaling. - Xinzhu Liang; Sanjaya Lohani; Joseph M. Lukens; Brian T. Kirby; Thomas A. Searles; Kody J. H. Law (CoRR, 2024)

An exponential reduction in training data sizes for machine learning derived entanglement witnesses. - Aiden R. Rosebush; Alexander Greenwood; Brian T. Kirby; Li Qian (Mach. Learn. Sci. Technol., 2024)

On the connection between least squares, regularization, and classical shadows. - Zhihui Zhu; Joseph M. Lukens; Brian T. Kirby (Quantum, 2024)

Scalable Bayesian Monte Carlo: fast uncertainty estimation beyond deep ensembles. - Xinzhu Liang; Joseph M. Lukens; Sanjaya Lohani; Brian T. Kirby; Thomas A. Searles; Xin Qiu; Kody J. H. Law (CoRR, 2025)