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Deep Representation Learning on Labeled Graphs
(Virginia Tech, 2020-01-27)
We introduce recurrent collective classification (RCC), a variant of ICA analogous to recurrent neural network prediction. RCC accommodates any differentiable local classifier and relational feature functions. We provide ...
Predictive Turbulence Modeling with Bayesian Inference and Physics-Informed Machine Learning
(Virginia Tech, 2018-09-25)
Reynolds-Averaged Navier-Stokes (RANS) simulations are widely used for engineering design and analysis involving turbulent flows. In RANS simulations, the Reynolds stress needs closure models and the existing models have ...
Physics-Informed, Data-Driven Framework for Model-Form Uncertainty Estimation and Reduction in RANS Simulations
(Virginia Tech, 2017-04-05)
Computational fluid dynamics (CFD) has been widely used to simulate turbulent flows. Although an increased availability of computational resources has enabled high-fidelity simulations (e.g. large eddy simulation and direct ...
Management of Complex Sociotechnical Systems
(Virginia Tech, 2020-04-20)
Sociotechnical systems (STSs) rely on the collaboration between humans and autonomous decision-making units to fulfill their objectives. Highly intertwined social and technical contextual factors influence the collaboration ...
Integrated Process Modeling and Data Analytics for Optimizing Polyolefin Manufacturing
(Virginia Tech, 2021-11-19)
Polyolefins are one of the most widely used commodity polymers with applications in films, packaging and automotive industry. The modeling of polymerization processes producing polyolefins, including high-density polyethylene ...
Spatiotemporal Event Forecasting and Analysis with Ubiquitous Urban Sensors
(Virginia Tech, 2021-07-13)
The study of information extraction and knowledge exploration in the urban environment is gaining popularity. Ubiquitous sensors and a plethora of statistical reports provide an immense amount of heterogeneous urban data, ...
Machine Learning-Based Parameter Validation
(Virginia Tech, 2014-04-24)
As power system grids continue to grow in order to support an increasing energy demand, the system's behavior accordingly evolves, continuing to challenge designs for maintaining security. It has become apparent in the ...
Machine Learning and Multivariate Statistics for Optimizing Bioprocessing and Polyolefin Manufacturing
(Virginia Tech, 2022-01-07)
Chemical engineers have routinely used computational tools for modeling, optimizing, and debottlenecking chemical processes. Because of the advances in computational science over the past decade, multivariate statistics ...
Developing machine learning tools to understand transcriptional regulation in plants
(Virginia Tech, 2019-09-09)
Abiotic stresses constitute a major category of stresses that negatively impact plant growth and development. It is important to understand how plants cope with environmental stresses and reprogram gene responses which in ...
Statistical Machine Learning for Multi-platform Biomedical Data Analysis
(Virginia Tech, 2011-08-24)
Recent advances in biotechnologies have enabled multiplatform and large-scale quantitative measurements of biomedical events. The need to analyze the produced vast amount of imaging and genomic data stimulates various novel ...