Christopher R. Laughman
- Phone: 617-621-7545
- Email:
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Position:
Research / Technical Staff
Senior Principal Research Scientist, Senior Team Leader -
Education:
Ph.D., Massachusetts Institute of Technology, 2008 -
Research Areas:
- Multi-Physical Modeling
- Optimization
- Control
- Data Analytics
- Machine Learning
- Dynamical Systems
- Human-Computer Interaction
External Links:
Chris' Quick Links
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Biography
Christopher's interests lie in the intersection of the modeling of physical systems and the experimental construction and testing of these systems, including simulation, numerical methods, and fault detection. He has worked on a variety of multi-physical systems, such as thermo-fluid systems and electromechanical energy conversion systems.
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Recent News & Events
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NEWS MERL researchers win ASME Energy Systems Technical Committee Best Paper Award at 2022 American Control Conference Date: June 8, 2022
Where: 2022 American Control Conference
MERL Contacts: Ankush Chakrabarty; Christopher R. Laughman
Research Areas: Control, Machine Learning, Multi-Physical Modeling, OptimizationBrief- Researchers from EPFL (Wenjie Xu, Colin Jones) and EMPA (Bratislav Svetozarevic), in collaboration with MERL researchers Ankush Chakrabarty and Chris Laughman, recently won the ASME Energy Systems Technical Committee Best Paper Award at the 2022 American Control Conference for their work on "VABO: Violation-Aware Bayesian Optimization for Closed-Loop Performance Optimization with Unmodeled Constraints" out of 19 nominations and 3 finalists. The paper describes a data-driven framework for optimizing the performance of constrained control systems by systematically re-evaluating how cautiously/aggressively one should explore the search space to avoid sustained, large-magnitude constraint violations while tolerating small violations, and demonstrates these methods on a physics-based model of a vapor compression cycle.
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NEWS MERL researchers presented 9 papers at the American Control Conference (ACC) Date: June 8, 2022 - June 10, 2022
Where: Atlanta, GA
MERL Contacts: Karl Berntorp; Scott A. Bortoff; Ankush Chakrabarty; Stefano Di Cairano; Christopher R. Laughman; Marcel Menner; Rien Quirynen; Abraham P. Vinod; Avishai Weiss
Research Areas: Control, Machine Learning, OptimizationBrief- At the American Control Conference in Atlanta, GA, MERL presented 9 papers on subjects including autonomous-vehicle decision making and motion planning, realtime Bayesian inference and learning, reference governors for hybrid systems, Bayesian optimization, and nonlinear control.
See All News & Events for Chris -
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Internships with Chris
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MS1851: Dynamic Modeling and Control for Grid-Interactive Buildings
MERL is looking for a highly motivated and qualified candidate to work on modeling for smart sustainable buildings. The ideal candidate will have a strong understanding of modeling renewable energy sources, grid-interactive buildings, occupant behavior, and dynamical systems with expertise demonstrated via, e.g., peer-reviewed publications. Hands-on programming experience with Modelica is preferred. The minimum duration of the internship is 12 weeks; start time is flexible. This internship is preferred to be onsite at MERL, but may be done remotely where you live if the COVID pandemic makes it necessary.
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MERL Publications
- , "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}
- }
- , "Rapid Energy Optimization Of Vapor Compression Systems Using Probabilistic Machine Learning And Extremum Seeking Control", International Refrigeration and Air Conditioning Conference at Purdue, July 2022.BibTeX
- @inproceedings{Chakrabarty2022jul,
- author = {Chakrabarty, Ankush and Burns, Daniel J. and Guay, Martin and Laughman, Christopher R.},
- title = {Rapid Energy Optimization Of Vapor Compression Systems Using Probabilistic Machine Learning And Extremum Seeking Control},
- booktitle = {International Refrigeration and Air Conditioning Conference at Purdue},
- year = 2022,
- month = jul
- }
- , "VABO: Violation-Aware Bayesian Optimization for Closed-Loop Control Performance Optimization with Unmodeled Constraints", American Control Conference (ACC), June 2022, pp. 5288-5293.BibTeX TR2022-064 PDF
- @inproceedings{Xu2022jun,
- author = {Xu, Wenjie and Jones, Colin and Svetozarevic, Bratislav and Laughman, Christopher R. and Chakrabarty, Ankush},
- title = {VABO: Violation-Aware Bayesian Optimization for Closed-Loop Control Performance Optimization with Unmodeled Constraints},
- booktitle = {American Control Conference (ACC)},
- year = 2022,
- pages = {5288--5293},
- month = jun,
- isbn = {978-1-6654-5197-0},
- url = {https://www.merl.com/publications/TR2022-064}
- }
- , "Constrained Smoothers for State Estimation of Vapor Compression Cycles", American Control Conference (ACC), June 2022.BibTeX TR2022-063 PDF
- @inproceedings{Deshpande2022jun,
- author = {Deshpande, Vedang and Laughman, Christopher R. and Ma, Yingbo and Rackauckas, Chris},
- title = {Constrained Smoothers for State Estimation of Vapor Compression Cycles},
- booktitle = {American Control Conference (ACC)},
- year = 2022,
- month = jun,
- url = {https://www.merl.com/publications/TR2022-063}
- }
- , "Composable and Reusable Neural Surrogates to Predict System Response of Causal Model Components", AAAI 2022 Workshop on AI based Design and Manufacturing, March 2022.BibTeX TR2022-034 PDF
- @inproceedings{Anantharaman2022mar,
- author = {Anantharaman, Ranjan and Abdelrahim, Anas and Martinuzzi, Francesco and Yalburgi, Sharan and Saba, Elliot and Fischer, Keno and Hertz, Glen and de Vos, Pepijn and Laughman, Christopher R. and Ma, Yingbo and Shah, Viral and Edelman, Alan and Rackauckas, Chris},
- title = {Composable and Reusable Neural Surrogates to Predict System Response of Causal Model Components},
- booktitle = {AAAI 2022 Workshop on AI based Design and Manufacturing},
- year = 2022,
- month = mar,
- url = {https://www.merl.com/publications/TR2022-034}
- }
- , "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.
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Software Downloads
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Videos
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MERL Issued Patents
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Title: "Extremum Seeking Control with Stochastic Gradient Estimation"
Inventors: Chakrabarty, Ankush; Danielson, Claus; Bortoff, Scott A.; Laughman, Christopher
Patent No.: 11,467,544
Issue Date: Oct 11, 2022 -
Title: "System and Method for Power Optimizing Control of Multi-Zone Heat Pumps"
Inventors: Bortoff, Scott A.; Burns, Dan J; Laughman, Christopher; Qiao, Hongtao
Patent No.: 10,895,412
Issue Date: Jan 19, 2021 -
Title: "System and Method for Controlling Refrigerant in Vapor Compression System"
Inventors: Laughman, Christopher; Qiao, Hongtao; Burns, Dan J; Bortoff, Scott A.
Patent No.: 10,830,515
Issue Date: Nov 10, 2020 -
Title: "System and Method for Thermal Comfort Control"
Inventors: Laughman, Christopher; Bortoff, Scott A.
Patent No.: 10,767,887
Issue Date: Sep 8, 2020 -
Title: "System and Method for Controlling Vapor Compression Systems"
Inventors: Burns, Dan J; Laughman, Christopher; Bortoff, Scott A.
Patent No.: 10,495,364
Issue Date: Dec 3, 2019 -
Title: "Coordinated Operation of Multiple Space-Conditioning Systems"
Inventors: Laughman, Christopher; Qiao, Hongtao; Burns, Dan J; Bortoff, Scott A.
Patent No.: 10,234,158
Issue Date: Mar 19, 2019 -
Title: "System and Method for Controlling Multi-Zone Vapor Compression Systems"
Inventors: Burns, Dan J; Di Cairano, Stefano; Bortoff, Scott A.; Laughman, Christopher
Patent No.: 10,174,957
Issue Date: Jan 8, 2019 -
Title: "System and Method for Controlling of Vapor Compression System"
Inventors: Burns, Dan J; Jain, Neera; Laughman, Christopher; Di Cairano, Stefano; Bortoff, Scott A.
Patent No.: 9,625,196
Issue Date: Apr 18, 2017 -
Title: "Method For Reconstructing 3D Scenes From 2D Images"
Inventors: Ramalingam, Srikumar; Taguchi, Yuichi; Pillai, Jaishanker K; Burns, Dan J; Laughman, Christopher
Patent No.: 9,595,134
Issue Date: Mar 14, 2017 -
Title: "System and Method for Controlling Vapor Compression Systems"
Inventors: Burns, Dan J; Laughman, Christopher; Bortoff, Scott A.
Patent No.: 9,534,820
Issue Date: Jan 3, 2017 -
Title: "System and Method for Controlling Temperature and Humidity in Multiple Spaces using Liquid Desiccant"
Inventors: Laughman, Christopher; Burns, Dan J; Bortoff, Scott A.; Waters, Richard C.
Patent No.: 9,518,765
Issue Date: Dec 13, 2016 -
Title: "Adaptive Control of Vapor Compression System"
Inventors: Burns, Dan J; Laughman, Christopher
Patent No.: 9,182,154
Issue Date: Nov 10, 2015 -
Title: "Controlling Operation of Vapor Compression System"
Inventors: Nikovski, Daniel N.; Laughman, Christopher; Burns, Dan J
Patent No.: 8,793,003
Issue Date: Jul 29, 2014 -
Title: "System and Method for Controlling Operations of Vapor Compression"
Inventors: Bortoff, Scott A.; Burns, Dan J; Laughman, Christopher
Patent No.: 8,694,131
Issue Date: Apr 8, 2014
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Title: "Extremum Seeking Control with Stochastic Gradient Estimation"
