Aaron Gilad Kusne

According to our database, Aaron Gilad Kusne authored at least 15 papers between 2017 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

PRESTO: Privacy REcommendation and SecuriTy Optimization.

Olivera Kotevska, Aaron Gilad Kusne, Prasanna Balaprakash, Robert M. Patton

Dataset, July, 2025

2024

Real-time experiment-theory closed-loop interaction for autonomous materials science.

Haotong Liang, Chuangye Wang, Heshan Yu, Dylan Kirsch, Rohit Pant, Austin McDannald, Aaron Gilad Kusne, Ji-Cheng Zhao, Ichiro Takeuchi

CoRR, 2024

2023

Learning material synthesis-process-structure-property relationship by data fusion: Bayesian Coregionalization N-Dimensional Piecewise Function Learning.

Aaron Gilad Kusne, Austin McDannald, Brian DeCost

CoRR, 2023

Human-In-the-Loop for Bayesian Autonomous Materials Phase Mapping.

Felix Adams, Austin McDannald, Ichiro Takeuchi, Aaron Gilad Kusne

CoRR, 2023

2022

Scalable Multi-Agent Framework for Optimizing the Lab and Warehouse.

Aaron Gilad Kusne, Austin McDannald

CoRR, 2022

Benchmarking Active Learning Strategies for Materials Optimization and Discovery.

Alex Wang, Haotong Liang, Austin McDannald, Ichiro Takeuchi, Aaron Gilad Kusne

CoRR, 2022

A Low-Cost Robot Science Kit for Education with Symbolic Regression for Hypothesis Discovery and Validation.

Logan Saar, Haotong Liang, Alex Wang, Austin McDannald, Efrain Rodriguez, Ichiro Takeuchi, Aaron Gilad Kusne

CoRR, 2022

Analyzing Data Privacy for Edge Systems.

Olivera Kotevska, Jordan Johnson, Aaron Gilad Kusne

Proceedings of the 2022 IEEE International Conference on Smart Computing, 2022

Privacy policy robustness to reverse engineering.

Aaron Gilad Kusne, Olivera Kotevska

Proceedings of the CIKM 2022 Workshops co-located with 31st ACM International Conference on Information and Knowledge Management (CIKM 2022), 2022

2021

Physics in the Machine: Integrating Physical Knowledge in Autonomous Phase-Mapping.

Aaron Gilad Kusne, Austin McDannald, Brian L. DeCost, Corey Oses, Cormac Toher, Stefano Curtarolo, Apurva Mehta, Ichiro Takeuchi

CoRR, 2021

2020

Scientific AI in materials science: a path to a sustainable and scalable paradigm.

Brian DeCost, Jason Hattrick-Simpers, Zachary Trautt, Aaron Gilad Kusne, Eva Campo, Martin Green

Mach. Learn. Sci. Technol., 2020

2019

Designing over uncertain outcomes with stochastic sampling Bayesian optimization.

Peter D. Tonner, Daniel V. Samarov, Aaron Gilad Kusne

CoRR, 2019

Peak Area Detection Network for Directly Learning Phase Regions from Raw X-ray Diffraction Patterns.

Dipendra Jha, Aaron Gilad Kusne, Reda Al-Bahrani, Nam Nguyen, Wei-keng Liao, Alok N. Choudhary, Ankit Agrawal

Proceedings of the International Joint Conference on Neural Networks, 2019

2018

Fast classification of small X-ray diffraction datasets using data augmentation and deep neural networks.

Felipe Oviedo, Zekun Ren, Shijing Sun, Charlie Settens, Zhe Liu, Noor Titan Putri Hartono, Ramasamy Savitha, Brian L. DeCost, Siyu I. P. Tian, Giuseppe Romano, Aaron Gilad Kusne, Tonio Buonassisi

CoRR, 2018

2017

Dynamic Network Model for Smart City Data-Loss Resilience Case Study: City-to-City Network for Crime Analytics.

Olivera Kotevska, Aaron Gilad Kusne, Daniel V. Samarov, Ahmed Lbath, Abdella Battou

IEEE Access, 2017