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Welcome to the Uncertainty Quantification & Scientific Machine Learning Group!

Our research focuses on developing computational methods of uncertainty quantification and machine learning for complex systems in science, engineering, and medicine. We seek to derive these methods under a rigorous framework of mathematics and statistics together with computational feasibility and scalability. Our projects entail answering questions such as:

  • How much uncertainty accompanies the model prediction, and how can we reduce it from new data/evidence?
  • What data should we acquire next, and how many?
  • How can machine learning be used together with physical modeling?
See our review paper on optimal experimental design!
Check out our real-time prediction of global geomagnetic perturbations! [paper]

News

  • Upcoming/Interesting Events:
  • (2025/06) Yossi Cohen is giving a presentation “Data-Driven Prediction and Uncertainty Quantification on Chemical Concentration in Electroless Plating Process” and another presentation “An Industrial Framework for Explainable Anomaly Detection: A Case Study for Pick-and-Place Machines” at MSEC.
  • (2025/07) USNCCM
    • Yossi Cohen is giving a presentation “Explainable AI for enhanced and trustworthy industrial anomaly detection”.
    • Thomas Coons is giving a presentation “Efficient budget allocation strategies for multi-fidelity optimization under uncertainty”.
    • Chengyang Huang is giving a presentation “Bayesian system identification via the weak form of the partial differential equations”.
    • Siddhartha Srivastava is giving a presentation “Inverse characterization and coarse-grained modeling of agent-based epidemiological dynamics via delay differential equations”.
  • (2025/07) Xun Huan is giving a presentation “Optimal Pilot Sampling for Multi-fidelity Monte Carlo Methods” and co-organizing a session “Next-generation optimal experimental design: theory, scalability, and real world impact” at MCM.
  • (2025/09) Workshop on Scientific Machine Learning for Differential Equations
  • (2025/10) Xun Huan is co-organizing the IMSI Workshop on Optimal Control and Decision Making Under Uncertainty for Digital Twins.
  • (2026/03) SIAM UQ

We are grateful to all our current and past sponsors.