[HTML][HTML] A physics informed bayesian optimization approach for material design: application to NiTi shape memory alloys

D Khatamsaz, R Neuberger, AM Roy… - npj Computational …, 2023 - nature.com
The design of materials and identification of optimal processing parameters constitute a
complex and challenging task, necessitating efficient utilization of available data. Bayesian …

Bayesian optimization objective-based experimental design

M Imani, SF Ghoreishi - 2020 American control conference …, 2020 - ieeexplore.ieee.org
Design has become a salient part of most of the scientific and engineering tasks, embracing
a wide range of domains including real experimental settings (eg, material discovery or drug …

Multi-information source constrained Bayesian optimization

SF Ghoreishi, D Allaire - Structural and Multidisciplinary Optimization, 2019 - Springer
Abstract Design decisions for complex systems often can be made or informed by a variety
of information sources. When optimizing such a system, the evaluation of a quantity of …

Control of gene regulatory networks using Bayesian inverse reinforcement learning

M Imani, UM Braga-Neto - IEEE/ACM transactions on …, 2018 - ieeexplore.ieee.org
Control of gene regulatory networks (GRNs) to shift gene expression from undesirable states
to desirable ones has received much attention in recent years. Most of the existing methods …

Boolean Kalman filter and smoother under model uncertainty

M Imani, ER Dougherty, U Braga-Neto - Automatica, 2020 - Elsevier
Partially-observed Boolean dynamical systems (POBDS) are a general class of nonlinear
state-space models that provide a rich framework for modeling many complex dynamical …

A general frame for uncertainty propagation under multimodally distributed random variables

X Meng, J Liu, L Cao, Z Yu, D Yang - Computer Methods in Applied …, 2020 - Elsevier
Uncertainty propagation under multimodally distributed random variables, called multimodal
distribution propagation for short, is a challenging problem due to the complicate probability …

Bayesian uncertainty quantification and information fusion in CALPHAD-based thermodynamic modeling

P Honarmandi, TC Duong, SF Ghoreishi, D Allaire… - Acta Materialia, 2019 - Elsevier
Calculation of phase diagrams is one of the fundamental tools in alloy design—more
specifically under the framework of Integrated Computational Materials Engineering …

Design of collision detection system for smart car using Li-Fi and ultrasonic sensor

P Krishnan - IEEE Transactions on Vehicular Technology, 2018 - ieeexplore.ieee.org
The 21st century is defined as the era of technological development. With drastic increase in
population, automation is becoming the need of the hour in order to make life more …

Control of gene regulatory networks with noisy measurements and uncertain inputs

M Imani, UM Braga-Neto - IEEE Transactions on Control of …, 2017 - ieeexplore.ieee.org
This paper is concerned with the problem of stochastic control of gene regulatory networks
(GRNs) observed indirectly through noisy measurements and with uncertainty in the …

Uncertainty propagation in a multiscale CALPHAD-reinforced elastochemical phase-field model

V Attari, P Honarmandi, T Duong, DJ Sauceda… - Acta Materialia, 2020 - Elsevier
ICME approaches provide decision support for materials design by establishing quantitative
process-structure-property relations. Confidence in the decision support, however, must be …