A power quality prediction system. - Steven R. Shaw; Christopher R. Laughman; Steven B. Leeb; Robert F. Lepard (IEEE Trans. Ind. Electron., 2000)

A Method for Nonlinear Least Squares With Structured Residuals. - Steven R. Shaw; Christopher R. Laughman (IEEE Trans. Autom. Control., 2006)

A Kalman-Filter Spectral Envelope Preprocessor. - Steven R. Shaw; Christopher R. Laughman (IEEE Trans. Instrum. Meas., 2007)

Optimization of circuitry arrangements for heat exchangers using derivative-free optimization. - Nikolaos Ploskas; Christopher R. Laughman; Arvind U. Raghunathan; Nikolaos V. Sahinidis (CoRR, 2017)

Power Optimizing Control of Multi-Zone Heat Pumps. - Scott A. Bortoff; Daniel J. Burns; Christopher R. Laughman; Hongtao Qiao; Claus Danielson; Abraham Goldsmith; Stefano Di Cairano (CCTA, 2018)

Heat Exchanger Circuitry Design by Decision Diagrams. - Nikolaos Ploskas; Christopher R. Laughman; Arvind U. Raghunathan; Nikolaos V. Sahinidis (CPAIOR, 2019)

Modelica Implementation of Centralized MPC Controller for a Multi-Zone Heat Pump. - Pablo Krupa; Claus Danielson; Christopher R. Laughman; Scott A. Bortoff; Daniel J. Burns; Stefano Di Cairano; Daniel Limón (ECC, 2019)

An Extended Luenberger Observer for HVAC Application using FMI. - Scott A. Bortoff; Christopher R. Laughman (Modelica, 2019)

Thermodynamic Property and Fluid Modeling with Modern Programming Language Construct. - Martin Otter; Hilding Elmqvist; Dirk Zimmer; Christopher R. Laughman (Modelica, 2019)

Coupled Simulation of a Room Air-conditioner with CFD Models for Indoor Environment. - Hongtao Qiao; Xu Han; Saleh Nabi; Christopher R. Laughman (Modelica, 2019)

Proportional-Integral Extremum Seeking for Vapor Compression Systems. - Daniel J. Burns; Christopher R. Laughman; Martin Guay (IEEE Trans. Control. Syst. Technol., 2020)

Accelerating Simulation of Stiff Nonlinear Systems using Continuous-Time Echo State Networks. - Ranjan Anantharaman; Yingbo Ma; Shashi Gowda; Chris Laughman; Viral B. Shah; Alan Edelman; Christopher Rackauckas (AAAI Spring Symposium: MLPS, 2021)

Simulation Failure Robust Bayesian Optimization for Estimating Black-Box Model Parameters. - Ankush Chakrabarty; Scott A. Bortoff; Christopher R. Laughman (SMC, 2021)

ModelingToolkit: A Composable Graph Transformation System For Equation-Based Modeling. - Yingbo Ma; Shashi Gowda; Ranjan Anantharaman; Chris Laughman; Viral B. Shah; Christopher Rackauckas (CoRR, 2021)

Attentive Neural Processes and Batch Bayesian Optimization for Scalable Calibration of Physics-Informed Digital Twins. - Ankush Chakrabarty; Gordon Wichern; Christopher R. Laughman (CoRR, 2021)

Constrained Smoothers for State Estimation of Vapor Compression Cycles. - Vedang M. Deshpande; Christopher R. Laughman; Yingbo Ma; Chris Rackauckas (ACC, 2022)

VABO: Violation-Aware Bayesian Optimization for Closed-Loop Control Performance Optimization with Unmodeled Constraints. - Wenjie Xu; Colin N. Jones; Bratislav Svetozarevic; Christopher R. Laughman; Ankush Chakrabarty (ACC, 2022)

Composing Modeling And Simulation With Machine Learning In Julia. - Chris Rackauckas; Maja Gwózdz; Anand Jain; Yingbo Ma; Francesco Martinuzzi; Utkarsh Rajput; Elliot Saba; Viral B. Shah; Ranjan Anantharaman; Alan Edelman; Shashi Gowda; Avik Pal; et al. (ANNSIM, 2022)

Meta-Learning of Neural State-Space Models Using Data From Similar Systems. - Ankush Chakrabarty; Gordon Wichern; Christopher R. Laughman (CoRR, 2022)

Learning Residual Dynamics via Physics-Augmented Neural Networks: Application to Vapor Compression Cycles. - Raphael Chinchilla; Vedang M. Deshpande; Ankush Chakrabarty; Christopher R. Laughman (ACC, 2023)

LSR-BO: Local Search Region Constrained Bayesian Optimization for Performance Optimization of Vapor Compression Systems. - Joel A. Paulson; Farshud Sorourifar; Christopher R. Laughman; Ankush Chakrabarty (ACC, 2023)

Synthesizing Building Operation Data with Generative Models: VAEs, GANs, or Something In Between? - Alessandro Salatiello; Ye Wang 001; Gordon Wichern; Toshiaki Koike-Akino; Yoshihiro Ohta; Yosuke Kaneko; Christopher R. Laughman; Ankush Chakrabarty (e-Energy (Companion), 2023)

Violation-Aware Contextual Bayesian Optimization for Controller Performance Optimization with Unmodeled Constraints. - Wenjie Xu; Colin N. Jones; Bratislav Svetozarevic; Christopher R. Laughman; Ankush Chakrabarty (CoRR, 2023)

Physics-Constrained Deep Autoencoded Kalman Filters for Estimating Vapor Compression System States. - Vedang M. Deshpande; Ankush Chakrabarty; Abraham P. Vinod; Christopher R. Laughman (IEEE Control. Syst. Lett., 2023)

Simulation Failure-Robust Bayesian Optimization for Data-Driven Parameter Estimation. - Ankush Chakrabarty; Scott A. Bortoff; Christopher R. Laughman (IEEE Trans. Syst. Man Cybern. Syst., 2023)

Modeling and Control of a Multi-Mode Heat Pump. - Scott A. Bortoff; Hongtao Qiao; Christopher R. Laughman (CCTA, 2024)

Assessing Building Control Performance Using Physics-Based Simulation Models and Deep Generative Networks. - Ankush Chakrabarty; Luigi Vanfretti; Wei-Ting Tang; Joel A. Paulson; Sicheng Zhan; Scott A. Bortoff; Vedang M. Deshpande; Ye Wang 001; Christopher R. Laughman (CCTA, 2024)

Bayesian Forecasting with Deep Generative Disturbance Models in Stochastic MPC for Building Energy Systems. - Farshud Sorourifar; Joel A. Paulson; Ye Wang 001; Rien Quirynen; Christopher R. Laughman; Ankush Chakrabarty (CCTA, 2024)

Power System Modeling for Identification and Control Applications using Modelica and OpenIPSL. - Luigi Vanfretti; Christopher R. Laughman (CCTA, 2024)

Meta-Learning for Physically-Constrained Neural System Identification. - Ankush Chakrabarty; Gordon Wichern; Vedang M. Deshpande; Abraham P. Vinod; Karl Berntorp; Christopher R. Laughman (CoRR, 2025)

Probabilistic Forecasting for Building Energy Systems using Time-Series Foundation Models. - Young Jin Park; François G. Germain; Jing Liu 009; Ye Wang 001; Toshiaki Koike-Akino; Gordon Wichern; Navid Azizan; Christopher R. Laughman; Ankush Chakrabarty (CoRR, 2025)