Ilias Bilionis
Associate Professor of Mechanical Engineering
Purdue University
ibilion@purdue.edu
We are a research laboratory at the School of Mechanical Engineering of Purdue University, founded in 2014 by Dr. Ilias Bilionis.
Our mission is to develop scientific machine learning technologies to accelerate engineering innovation.
We operate at the intersection of mathematics, statistics, and engineering, facilitating communication between these disciplines by employing Bayesian probability and an additional layer of causality expressed through differential equations.
Our funding comes from NSF, NASA, DARPA, AFRL, Eli Lilly, Cummins, and Ford.
Bilionis loves teaching scientific machine learning, probabilistic thinking, and uncertainty quantification to engineers. Some examples are these:
Associate Professor of Mechanical Engineering
Purdue University
ibilion@purdue.edu
Postdoctoral Researcher
Bayesian inverse problems, Physics informed neural networks, Digital twins for advanced manufacturing
Postdoctoral Researcher
Bayesian inverse problems, Physics informed neural networks, Sequential design of experiments
Ph.D. Student
Purdue University
beltranp@purdue.edu
Electric machine design optimization using physics informed neural networks
Ph.D. Student
Physics-informed, information field theory
Ph.D. Student
mrajase@purdue.edu
Ph.D. Student
Physics-informed, information field theory for dynamical systems
Ph.D. Student
Particle image velocimetry using information field theory
hans1@purdue.edu
Ph.D. Student
Bayesian calibration of hyperelasticity models
Ph.D. Student
Information field theory for fluid flow reconstruction from non-intrusive flow measurements
Ph.D. Student
Digital twins for smart buildings
Ph.D. Student
Information field theory
Ph.D. Student
Emissions modeling
szinage@purdue.edu
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