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}
      • }