77 citations · 174 across the 23 of their papers we have counts for
23 papers
Federated Causal Representation Learning in State-Space Systems for Decentralized Counterfactual Reasoning
Nazal Mohamed, Ayush Mohanty, Nagi Gebraeel
Networks of interdependent industrial assets (clients) are tightly coupled through physical processes and control inputs, raising a key question: how would the output of one client…
Learning Unknown Interdependencies for Decentralized Root Cause Analysis in Nonlinear Dynamical Systems
Ayush Mohanty, Paritosh Ramanan, Nagi Gebraeel
Root cause analysis (RCA) in networked industrial systems, such as supply chains and power networks, is notoriously difficult due to unknown and dynamically evolving interdependenc…
Federated Learning of Nonlinear Temporal Dynamics with Graph Attention-based Cross-Client Interpretability
Ayse Tursucular, Ayush Mohanty, Nazal Mohamed +1
Networks of modern industrial systems are increasingly monitored by distributed sensors, where each system comprises multiple subsystems that generate high-dimensional time-series.…
Uncertainty Quantification in Federated Granger Causality Learning
Ayush Mohanty, Nazal Mohamed, Nagi Gebraeel
Granger causality identifies predictive dependencies in multivariate time series. In distributed settings where parties cannot share data, federated causal learning enables joint a…
A Federated Generalized Expectation-Maximization Algorithm for Mixture Models with an Unknown Number of Components
Michael Ibrahim, Nagi Gebraeel, Weijun Xie
We study the problem of federated clustering when the total number of clusters across clients is unknown, and the clients have heterogeneous but potentially overlapping cluster…
Data-driven joint optimization of maintenance and spare parts provisioning: A distributionally robust approach
Heraldo Rozas, Weijun Xie, Nagi Gebraeel +1
This paper investigates the joint optimization of condition-based maintenance and spare provisioning, incorporating insights obtained from sensor data. Prognostic models estimate c…