226 citations · 729 across the 62 of their papers we have counts for
10 papers · 1 filter
Interpretable deep learning for guided structure-property explorations in photovoltaics
Balaji Sesha Sarath Pokuri, Sambuddha Ghosal, Apurva Kokate +2
The performance of an organic photovoltaic device is intricately connected to its active layer morphology. This connection between the active layer and device performance is very e…
Flow Shape Design for Microfluidic Devices Using Deep Reinforcement Learning
Xian Yeow Lee, Aditya Balu, Daniel Stoecklein +2
Microfluidic devices are utilized to control and direct flow behavior in a wide variety of applications, particularly in medical diagnostics. A particularly popular form of microfl…
3D Deep Learning with voxelized atomic configurations for modeling atomistic potentials in complex solid-solution alloys
Rahul Singh, Aayush Sharma, Onur Rauf Bingol +4
The need for advanced materials has led to the development of complex, multi-component alloys or solid-solution alloys. These materials have shown exceptional properties like stren…
Physics-aware Deep Generative Models for Creating Synthetic Microstructures
Rahul Singh, Viraj Shah, Balaji Pokuri +3
A key problem in computational material science deals with understanding the effect of material distribution (i.e., microstructure) on material performance. The challenge is to syn…
Online Robust Policy Learning in the Presence of Unknown Adversaries
Aaron J. Havens, Zhanhong Jiang, Soumik Sarkar
The growing prospect of deep reinforcement learning (DRL) being used in cyber-physical systems has raised concerns around safety and robustness of autonomous agents. Recent work on…
Root-cause Analysis for Time-series Anomalies via Spatiotemporal Graphical Modeling in Distributed Complex Systems
Chao Liu, Kin Gwn Lore, Zhanhong Jiang +1
Performance monitoring, anomaly detection, and root-cause analysis in complex cyber-physical systems (CPSs) are often highly intractable due to widely diverse operational modes, di…