4 citations · 11 across the 8 of their papers we have counts for
15 papers
Bayesian Model Averaging for Data Driven Decision Making when Causality is Partially Known
Marios Papamichalis, Abhishek Ray, Ilias Bilionis +2
Probabilistic machine learning models are often insufficient to help with decisions on interventions because those models find correlations - not causal relationships. If observati…
Exploratory Data Analysis for Airline Disruption Management
Kolawole Ogunsina, Ilias Bilionis, Daniel DeLaurentis
Reliable platforms for data collation during airline schedule operations have significantly increased the quality and quantity of available information for effectively managing air…
Improving Reconstructive Surgery Design using Gaussian Process Surrogates to Capture Material Behavior Uncertainty
Casey Stowers, Taeksang Lee, Ilias Bilionis +2
Excessive loads near wounds produce pathological scarring and other complications. Presently, stress cannot easily be measured by surgeons in the operating room. Instead, surgeons…
Learning Arbitrary Quantities of Interest from Expensive Black-Box Functions through Bayesian Sequential Optimal Design
Piyush Pandita, Nimish Awalgaonkar, Ilias Bilionis +1
Estimating arbitrary quantities of interest (QoIs) that are non-linear operators of complex, expensive-to-evaluate, black-box functions is a challenging problem due to missing doma…
A Resilience-based Method for Prioritizing Post-event Building Inspections
Ali Lenjani, Ilias Bilionis, Shirley Dyke +2
Despite the wide range of possible scenarios in the aftermath of a disruptive event, each community can make choices to improve its resilience, or its ability to bounce back. A res…
Towards fully automated post-event data collection and analysis: pre-event and post-event information fusion
Ali Lenjani, Shirley J. Dyke, Ilias Bilionis +5
In post-event reconnaissance missions, engineers and researchers collect perishable information about damaged buildings in the affected geographical region to learn from the conseq…