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 Contributes to the 2022 American Modelica Conference Date: October 26, 2022 - October 28, 2022
Where: American Modelica Conference 2022
MERL Contacts: Scott A. Bortoff; Christopher R. Laughman
Research Area: Multi-Physical ModelingBrief- MERL researchers provided some key contributions to the 2022 American Modelica Conference, held October 26-28 at the University of Texas, Dallas. Chris Laughman, Senior Team Leader, Multiphysical Systems, was the Executive Coordinator of the conference, and worked to plan and stage the event. Scott A. Bortoff, Chief Scientist, gave a keynote address entitled "Sustainable HVAC: Research Opportunities for Modelicans." The talk posed the question: What are the modeling and control research challenges that, if addressed, will drive meaningful innovation in sustainable building HVAC systems in the next 20 years? In addition, the paper "Performance Enhancements for Zero-Flow Simulation of Vapor Compression Cycles," by Principal Research Scientist Hongtao Qiao and Chris Laughman, was a finalist for the conference Best Paper Award.
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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.
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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MS1958: Simulation, Control, and Optimization of Large-Scale Systems
MERL is seeking a motivated graduate student to research numerical methods pertaining to the simulation, control, and optimization of large-scale systems. Representative applications include large vapor-compression cycles and other multiphysical systems for energy conversion that couple thermodynamic, fluid, and electrical domains. The ideal candidate would have a solid background in numerical methods, control, and optimization; strong programming skills and experience with Julia/Python/Matlab are also expected. Knowledge of the fundamental physics of thermofluid flows (e.g., thermodynamics, heat transfer, and fluid mechanics), nonlinear dynamics, or equation-oriented languages (Modelica, gPROMS) is a plus. The expected duration of this internship is 3 months.
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MERL Publications
- "https://iwww.merl.com/TR/camready-4505.pdf", Modeling, Estimation and Control Conference, December 2022.BibTeX TR2022-170 PDF
- @inproceedings{Bhattacharya2022dec,
- author = {Bhattacharya, Chandrachur and Chakrabarty, Ankush and Laughman, Christopher R. and Qiao, Hongtao},
- title = {https://iwww.merl.com/TR/camready-4505.pdf},
- booktitle = {Modeling, Estimation and Control Conference},
- year = 2022,
- month = dec,
- url = {https://www.merl.com/publications/TR2022-170}
- }
, - "Simulation Failure Robust Bayesian Optimization for Data-Driven Parameter Estimation", IEEE Transactions on Systems, Man, and Cybernetics: Systems, December 2022.BibTeX TR2022-168 PDF
- @article{Chakrabarty2022dec2,
- author = {Chakrabarty, Ankush and Bortoff, Scott A. and Laughman, Christopher R.},
- title = {Simulation Failure Robust Bayesian Optimization for Data-Driven Parameter Estimation},
- journal = {IEEE Transactions on Systems, Man, and Cybernetics: Systems},
- year = 2022,
- month = dec,
- url = {https://www.merl.com/publications/TR2022-168}
- }
, - "Meta-Learning of Neural State-Space Models Using Data From Similar Systems", arXiv, November 2022. ,
- "Extremum seeking controller tuning for heat pump optimization using failure-robust Bayesian optimization", Journal of Process Control, November 2022.BibTeX TR2022-144 PDF
- @article{Chakrabarty2022nov2,
- author = {Chakrabarty, Ankush and Burns, Daniel J. and Guay, Martin and Laughman, Christopher R.},
- title = {Extremum seeking controller tuning for heat pump optimization using failure-robust Bayesian optimization},
- journal = {Journal of Process Control},
- year = 2022,
- month = nov,
- url = {https://www.merl.com/publications/TR2022-144}
- }
, - "Performance Enhancements for Zero-Flow Simulation of Vapor Compression Cycles", American Modelica Conference, October 2022.BibTeX TR2022-137 PDF
- @inproceedings{Qiao2022oct,
- author = {Qiao, Hongtao and Laughman, Christopher R.},
- title = {Performance Enhancements for Zero-Flow Simulation of Vapor Compression Cycles},
- booktitle = {American Modelica Conference},
- year = 2022,
- month = oct,
- url = {https://www.merl.com/publications/TR2022-137}
- }
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- "https://iwww.merl.com/TR/camready-4505.pdf", Modeling, Estimation and Control Conference, December 2022.
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Software Downloads
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Videos
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MERL Issued Patents
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Title: "Controlling Vapor Compression System Using Probabilistic Surrogate Model"
Inventors: Chakrabarty, Ankush; Laughman, Christopher; Bortoff, Scott A.
Patent No.: 11,573,023
Issue Date: Feb 7, 2023 -
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: "Controlling Vapor Compression System Using Probabilistic Surrogate Model"