NEWS    Ankush Chakrabarty gave a lecture at UT-Austin's Seminar Series on Occupant-Centric Grid-Interactive Buildings

Date released: March 20, 2024

  •  NEWS    Ankush Chakrabarty gave a lecture at UT-Austin's Seminar Series on Occupant-Centric Grid-Interactive Buildings
  • Date:

    March 20, 2024

  • Where:

    Austin, TX

  • Description:

    Ankush Chakrabarty, Principal Research Scientist in the Multiphysical Systems Team, was invited to speak as a guest lecturer in the seminar series on "Occupant-Centric Grid Interactive Buildings" in the Department of Civil, Architectural and Environmental Engineering (CAEE) at the University of Texas at Austin.

    The talk, entitled "Deep Generative Networks and Fine-Tuning for Net-Zero Energy Buildings" described lessons learned from MERL's recent research on generative models for building simulation and control, along with meta-learning for on-the-fly fine-tuning to adapt and optimize energy expenditure.

  • External Link:

    https://github.com/intelligent-environments-lab/occupant_centric_grid_interactive_buildings_course?tab=readme-ov-file

  • MERL Contact:
  • Research Areas:

    Artificial Intelligence, Control, Data Analytics, Dynamical Systems, Machine Learning, Multi-Physical Modeling, Optimization

    •  Deshpande, V.M., Chakrabarty, A., Vinod, A.P., Laughman, C.R., "Physics-Constrained Deep Autoencoded Kalman Filters for Estimating Vapor Compression System States", IEEE Control Systems Letters, DOI: 10.1109/​LCSYS.2023.3334959, November 2023.
      BibTeX TR2023-138 PDF
      • @article{Deshpande2023nov,
      • author = {{Deshpande, Vedang M. and Chakrabarty, Ankush and Vinod, Abraham P. and Laughman, Christopher R.}},
      • title = {Physics-Constrained Deep Autoencoded Kalman Filters for Estimating Vapor Compression System States},
      • journal = {IEEE Control Systems Letters},
      • year = 2023,
      • month = nov,
      • doi = {10.1109/LCSYS.2023.3334959},
      • url = {https://www.merl.com/publications/TR2023-138}
      • }
    •  Chakrabarty, A., Wichern, G., Laughman, C.R., "Meta-Learning of Neural State-Space Models Using Data From Similar Systems", World Congress of the International Federation of Automatic Control (IFAC), DOI: 10.1016/​j.ifacol.2023.10.1843, July 2023.
      BibTeX TR2023-087 PDF Software
      • @inproceedings{Chakrabarty2023jul,
      • author = {Chakrabarty, Ankush and Wichern, Gordon and Laughman, Christopher R.},
      • title = {Meta-Learning of Neural State-Space Models Using Data From Similar Systems},
      • booktitle = {World Congress of the International Federation of Automatic Control (IFAC)},
      • year = 2023,
      • month = jul,
      • doi = {10.1016/j.ifacol.2023.10.1843},
      • url = {https://www.merl.com/publications/TR2023-087}
      • }
    •  Salatiello, A., Wang, Y., Wichern, G., Koike-Akino, T., Yoshihiro, O., Kaneko, Y., Laughman, C.R., Chakrabarty, A., "Synthesizing Building Operation Data with Generative Models: VAEs, GANs, or Something In Between?", ACM e-Energy Conference, DOI: 10.1145/​3599733.3600260, June 2023.
      BibTeX TR2023-072 PDF
      • @inproceedings{Salatiello2023jun,
      • author = {Salatiello, Alessandro and Wang, Ye and Wichern, Gordon and Koike-Akino, Toshiaki and Yoshihiro, Ohta and Kaneko, Yosuke and Laughman, Christopher R. and Chakrabarty, Ankush},
      • title = {Synthesizing Building Operation Data with Generative Models: VAEs, GANs, or Something In Between?},
      • booktitle = {ACM e-Energy Conference},
      • year = 2023,
      • month = jun,
      • doi = {10.1145/3599733.3600260},
      • url = {https://www.merl.com/publications/TR2023-072}
      • }
    •  Ngheim, T.X., Drgona, J., Jones, C., Nagy, Z., Schwan, R., Dey, B., Chakrabarty, A., Di Cairano, S., Paulson, J.A., Carron, A., Zeilinger, M., Cortez, W.S., Vrabie, D.L., "Physics-Informed Machine Learning for Modeling and Control of Dynamical Systems", American Control Conference (ACC), DOI: 10.23919/​ACC55779.2023.10155901, May 2023.
      BibTeX TR2023-052 PDF
      • @inproceedings{Ngheim2023may,
      • author = {Ngheim, Truong X. and Drgona, Jan and Jones, Colin and Nagy, Zoltan and Schwan, Roland and Dey, Biswadip and Chakrabarty, Ankush and Di Cairano, Stefano and Paulson, Joel A. and Carron, Andrea and Zeilinger, Melanie and Cortez, Wenceslaw S. and Vrabie, Draguna L.},
      • title = {Physics-Informed Machine Learning for Modeling and Control of Dynamical Systems},
      • booktitle = {American Control Conference (ACC)},
      • year = 2023,
      • month = may,
      • doi = {10.23919/ACC55779.2023.10155901},
      • url = {https://www.merl.com/publications/TR2023-052}
      • }
    •  Zhan, S., Wichern, G., Laughman, C.R., Chong, A., Chakrabarty, A., "Calibrating building simulation models using multi-source datasets and meta-learned Bayesian optimization", Energy and Buildings, DOI: 10.1016/​j.enbuild.2022.112278, Vol. 270, pp. 112278, September 2022.
      BibTeX TR2022-072 PDF
      • @article{Zhan2023jan,
      • author = {Zhan, Sicheng and Wichern, Gordon and Laughman, Christopher R. and Chong, Adrian and Chakrabarty, Ankush},
      • title = {Calibrating building simulation models using multi-source datasets and meta-learned Bayesian optimization},
      • journal = {Energy and Buildings},
      • year = 2022,
      • volume = 270,
      • pages = 112278,
      • month = sep,
      • doi = {10.1016/j.enbuild.2022.112278},
      • url = {https://www.merl.com/publications/TR2022-072}
      • }