Christopher R. Laughman

31 papers B 2C 5Journal 14Unranked 10
YearRankTypeTitle / Venue / Authors
2025 J jnl
Meta-Learning for Physically-Constrained Neural System Identification.
CoRR
Ankush Chakrabarty, Gordon Wichern, Vedang M. Deshpande, Abraham P. Vinod, Karl Berntorp, Christopher R. Laughman
2025 J jnl
Meta-learning for physically-constrained neural system identification.
Neurocomputing
Ankush Chakrabarty, Gordon Wichern, Vedang M. Deshpande, Abraham P. Vinod, Karl Berntorp, Christopher R. Laughman
2025 J jnl
Probabilistic Forecasting for Building Energy Systems using Time-Series Foundation Models.
CoRR
Young Jin Park, François G. Germain, Jing Liu, Ye Wang, Toshiaki Koike-Akino, Gordon Wichern, Navid Azizan, Christopher R. Laughman, Ankush Chakrabarty
2024 — conf
Assessing Building Control Performance Using Physics-Based Simulation Models and Deep Generative Networks.
CCTA
Ankush Chakrabarty, Luigi Vanfretti, Wei-Ting Tang, Joel A. Paulson, Sicheng Zhan, Scott A. Bortoff, Vedang M. Deshpande, Ye Wang, Christopher R. Laughman
2024 — conf
Bayesian Forecasting with Deep Generative Disturbance Models in Stochastic MPC for Building Energy Systems.
CCTA
Farshud Sorourifar, Joel A. Paulson, Ye Wang, Rien Quirynen, Christopher R. Laughman, Ankush Chakrabarty
2024 — conf
Modeling and Control of a Multi-Mode Heat Pump.
CCTA
Scott A. Bortoff, Hongtao Qiao, Christopher R. Laughman
2024 — conf
Power System Modeling for Identification and Control Applications using Modelica and OpenIPSL.
CCTA
Luigi Vanfretti, Christopher R. Laughman
2023 C conf
LSR-BO: Local Search Region Constrained Bayesian Optimization for Performance Optimization of Vapor Compression Systems.
ACC
Joel A. Paulson, Farshud Sorourifar, Christopher R. Laughman, Ankush Chakrabarty
2023 C conf
Learning Residual Dynamics via Physics-Augmented Neural Networks: Application to Vapor Compression Cycles.
ACC
Raphael Chinchilla, Vedang M. Deshpande, Ankush Chakrabarty, Christopher R. Laughman
2023 J jnl
Physics-Constrained Deep Autoencoded Kalman Filters for Estimating Vapor Compression System States.
IEEE Control. Syst. Lett.
Vedang M. Deshpande, Ankush Chakrabarty, Abraham P. Vinod, Christopher R. Laughman
2023 J jnl
Simulation Failure-Robust Bayesian Optimization for Data-Driven Parameter Estimation.
IEEE Trans. Syst. Man Cybern. Syst.
Ankush Chakrabarty, Scott A. Bortoff, Christopher R. Laughman
2023 — conf
Synthesizing Building Operation Data with Generative Models: VAEs, GANs, or Something In Between?
e-Energy (Companion)
Alessandro Salatiello, Ye Wang, Gordon Wichern, Toshiaki Koike-Akino, Yoshihiro Ohta, Yosuke Kaneko, Christopher R. Laughman, Ankush Chakrabarty
2023 J jnl
Violation-Aware Contextual Bayesian Optimization for Controller Performance Optimization with Unmodeled Constraints.
CoRR
Wenjie Xu, Colin N. Jones, Bratislav Svetozarevic, Christopher R. Laughman, Ankush Chakrabarty
2022 C conf
Constrained Smoothers for State Estimation of Vapor Compression Cycles.
ACC
Vedang M. Deshpande, Christopher R. Laughman, Yingbo Ma, Chris Rackauckas
2022 J jnl
Meta-Learning of Neural State-Space Models Using Data From Similar Systems.
CoRR
Ankush Chakrabarty, Gordon Wichern, Christopher R. Laughman
2022 C conf
VABO: Violation-Aware Bayesian Optimization for Closed-Loop Control Performance Optimization with Unmodeled Constraints.
ACC
Wenjie Xu, Colin N. Jones, Bratislav Svetozarevic, Christopher R. Laughman, Ankush Chakrabarty
2021 J jnl
Attentive Neural Processes and Batch Bayesian Optimization for Scalable Calibration of Physics-Informed Digital Twins.
CoRR
Ankush Chakrabarty, Gordon Wichern, Christopher R. Laughman
2021 B conf
Simulation Failure Robust Bayesian Optimization for Estimating Black-Box Model Parameters.
SMC
Ankush Chakrabarty, Scott A. Bortoff, Christopher R. Laughman
2021 J jnl
VABO: Violation-Aware Bayesian Optimization for Closed-Loop Control Performance Optimization with Unmodeled Constraints.
CoRR
Wenjie Xu, Colin N. Jones, Bratislav Svetozarevic, Christopher R. Laughman, Ankush Chakrabarty
2020 J jnl
Proportional-Integral Extremum Seeking for Vapor Compression Systems.
IEEE Trans. Control. Syst. Technol.
Daniel J. Burns, Christopher R. Laughman, Martin Guay
2019 — conf
An Extended Luenberger Observer for HVAC Application using FMI.
Modelica
Scott A. Bortoff, Christopher R. Laughman
2019 — conf
Coupled Simulation of a Room Air-conditioner with CFD Models for Indoor Environment.
Modelica
Hongtao Qiao, Xu Han, Saleh Nabi, Christopher R. Laughman
2019 B conf
Heat Exchanger Circuitry Design by Decision Diagrams.
CPAIOR
Nikolaos Ploskas, Christopher R. Laughman, Arvind U. Raghunathan, Nikolaos V. Sahinidis
2019 — conf
Modelica Implementation of Centralized MPC Controller for a Multi-Zone Heat Pump.
ECC
Pablo Krupa, Claus Danielson, Christopher R. Laughman, Scott A. Bortoff, Daniel J. Burns, Stefano Di Cairano, Daniel Limón
2019 — conf
Thermodynamic Property and Fluid Modeling with Modern Programming Language Construct.
Modelica
Martin Otter, Hilding Elmqvist, Dirk Zimmer, Christopher R. Laughman
2018 — conf
Power Optimizing Control of Multi-Zone Heat Pumps.
CCTA
Scott A. Bortoff, Daniel J. Burns, Christopher R. Laughman, Hongtao Qiao, Claus Danielson, Abraham Goldsmith, Stefano Di Cairano
2017 J jnl
Optimization of circuitry arrangements for heat exchangers using derivative-free optimization.
CoRR
Nikolaos Ploskas, Christopher R. Laughman, Arvind U. Raghunathan, Nikolaos V. Sahinidis
2016 C conf
Proportional-integral extremum seeking for vapor compression systems.
ACC
Daniel J. Burns, Christopher R. Laughman, Martin Guay
2007 J jnl
A Kalman-Filter Spectral Envelope Preprocessor.
IEEE Trans. Instrum. Meas.
Steven R. Shaw, Christopher R. Laughman
2006 J jnl
A Method for Nonlinear Least Squares With Structured Residuals.
IEEE Trans. Autom. Control.
Steven R. Shaw, Christopher R. Laughman
2000 J jnl
A power quality prediction system.
IEEE Trans. Ind. Electron.
Steven R. Shaw, Christopher R. Laughman, Steven B. Leeb, Robert F. Lepard