NEWS    Ankush Chakrabarty gave an invited talk at CRAN: Centre de Recherche en Automatique de Nancy, France

Date released: October 22, 2021

  •  NEWS    Ankush Chakrabarty gave an invited talk at CRAN: Centre de Recherche en Automatique de Nancy, France
  • Date:

    October 21, 2021

  • Where:

    Université de Lorraine, France

  • Description:

    Ankush Chakrabarty (RS, Multiphysical Systems Team) gave an invited talk on `Bayesian-Optimized Estimation and Control for Buildings and HVAC' at the Research Center for Automatic Control (CRAN) in the University of Lorraine in France. The talk presented recent MERL research on probabilistic machine learning for set-point optimization and calibration of digital twins for building energy systems.

  • MERL Contact:
  • Research Areas:

    Artificial Intelligence, Control, Machine Learning, Multi-Physical Modeling, Optimization

    •  Chakrabarty, A., Maddalena, E., Qiao, H., Laughman, C.R., "Data-driven calibration of physics-informed models of joint building/equipment dynamics using Bayesian optimization", Building Simulation Conference 2021, September 2021.
      BibTeX TR2021-105 PDF Video
      • @inproceedings{Chakrabarty2021sep,
      • author = {Chakrabarty, Ankush and Maddalena, Emilio and Qiao, Hongtao and Laughman, Christopher R.},
      • title = {Data-driven calibration of physics-informed models of joint building/equipment dynamics using Bayesian optimization},
      • booktitle = {Building Simulation Conference 2021},
      • year = 2021,
      • month = sep,
      • url = {https://www.merl.com/publications/TR2021-105}
      • }
    •  Chakrabarty, A., Benosman, M., "Safe Learning-based Observers for Unknown Nonlinear Systems using Bayesian Optimization", Automatica, DOI: 10.1016/​j.automatica.2021.109860, August 2021.
      BibTeX TR2021-101 PDF
      • @article{Chakrabarty2021aug,
      • author = {Chakrabarty, Ankush and Benosman, Mouhacine},
      • title = {Safe Learning-based Observers for Unknown Nonlinear Systems using Bayesian Optimization},
      • journal = {Automatica},
      • year = 2021,
      • month = aug,
      • doi = {10.1016/j.automatica.2021.109860},
      • url = {https://www.merl.com/publications/TR2021-101}
      • }
    •  Chakrabarty, A., Wichern, G., Laughman, C.R., "ANP-BBO: Attentive Neural Processes and Batch Bayesian Optimization for Scalable Calibration of Physics-Informed Digital Twins", International Conference on Machine Learning (ICML), July 2021.
      BibTeX TR2021-086 PDF
      • @inproceedings{Chakrabarty2021jul,
      • author = {Chakrabarty, Ankush and Wichern, Gordon and Laughman, Christopher R.},
      • title = {ANP-BBO: Attentive Neural Processes and Batch Bayesian Optimization for Scalable Calibration of Physics-Informed Digital Twins},
      • booktitle = {International Conference on Machine Learning (ICML)},
      • year = 2021,
      • month = jul,
      • url = {https://www.merl.com/publications/TR2021-086}
      • }