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Within the Aerospace Mechanics Research Center in the at the ¾«Æ·SMÔÚÏßӰƬ, the UQ and Data-driven lab is led by Professor Alireza Doostan. The group actively develops novel uncertainty quantification and data-driven methods and applies these techniques to both academic and large-scale problems, ranging from solid and fluid mechanics.

Our group has been actively pursuing inter-disciplinary research across several areas, including:

  • Uncertainty quantification and reliability analysis of complex systems using multi-fidelity and reduced-order modeling strategies
  • Data-driven model discovery and system identificationÌý
  • Streaming scientific data reduction Ìý
  • Design/optimization under uncertaintyÌý
  • Scientific machine learning (SciML)

Over the past several years, our team has tackled several applications across solid and fluid mechanics, as well as astrodynamics.Ìý

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Available Positions: We are currently hiring two Ph.D. students (starting Summer or Fall 2025) and one postdoctoral fellow for research projects related to uncertainty quantification, scientific machine learning, and data compression. Please reach out to Prof. Doostan for more details.Ìý

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We acknowledge generous funding from various agencies supporting our research!

A collection of logos of various funding institutions

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Attention: This page is under construction!