NEWS    Ankush Chakrabarty co-organized three sessions at the ACC2023, and was nominated for Best Energy Systems Paper.

Date released: June 6, 2023

  •  NEWS    Ankush Chakrabarty co-organized three sessions at the ACC2023, and was nominated for Best Energy Systems Paper.
  • Date:

    June 30, 2023 - June 2, 2023

  • Where:

    San Diego, CA

  • Description:

    Ankush Chakrabarty (researcher, Multiphysical Systems Team) co-organized and spoke at 3 sessions at the 2023 American Control Conference in San Diego, CA. These include: (1) A tutorial session (w/ Stefano Di Cairano) on "Physics Informed Machine Learning for Modeling and Control": an effort with contributions from multiple academic institutes and US research labs; (2) An invited session on "Energy Efficiency in Smart Buildings and Cities" in which his paper (w/ Chris Laughman) on "Local Search Region Constrained Bayesian Optimization for Performance Optimization of Vapor Compression Systems" was nominated for Best Energy Systems Paper Award; and, (3) A special session on Diversity, Equity, and Inclusion to improve recruitment and retention of underrepresented groups in STEM research.

  • MERL Contact:
  • Research Areas:

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

    •  Paulson, J.A., Sorouifar, F., Laughman, C.R., Chakrabarty, A., "LSR-BO: Local Search Region Constrained Bayesian Optimization for Performance Optimization of Vapor Compression Systems", American Control Conference (ACC), DOI: 10.23919/​ACC55779.2023.10155821, May 2023.
      BibTeX TR2023-057 PDF
      • @inproceedings{Paulson2023may,
      • author = {Paulson, Joel A. and Sorouifar, Farshud and Laughman, Christopher R. and Chakrabarty, Ankush},
      • title = {LSR-BO: Local Search Region Constrained Bayesian Optimization for Performance Optimization of Vapor Compression Systems},
      • booktitle = {American Control Conference (ACC)},
      • year = 2023,
      • month = may,
      • doi = {10.23919/ACC55779.2023.10155821},
      • url = {https://www.merl.com/publications/TR2023-057}
      • }
    •  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}
      • }
    •  Chinchilla, R., Deshpande, V.M., Chakrabarty, A., Laughman, C.R., "Learning Residual Dynamics via Physics-Augmented Neural Networks: Application to Vapor Compression Cycles", American Control Conference (ACC), DOI: 10.23919/​ACC55779.2023.10155954, May 2023, pp. 4069-4076.
      BibTeX TR2023-051 PDF
      • @inproceedings{Chinchilla2023may,
      • author = {Chinchilla, Raphael and Deshpande, Vedang M. and Chakrabarty, Ankush and Laughman, Christopher R.},
      • title = {Learning Residual Dynamics via Physics-Augmented Neural Networks: Application to Vapor Compression Cycles},
      • booktitle = {American Control Conference (ACC)},
      • year = 2023,
      • pages = {4069--4076},
      • month = may,
      • publisher = {IEEE},
      • doi = {10.23919/ACC55779.2023.10155954},
      • issn = {2378-5861},
      • isbn = {978-1-6654-6952-4},
      • url = {https://www.merl.com/publications/TR2023-051}
      • }