Publications

39 / 3,364 publications found.


  •  Chakrabarty, A., Burns, D.J., Guay, M., Laughman, C.R., "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}
    • }
  •  Chakrabarty, A., "Optimizing Closed-Loop Performance with Data from Similar Systems: A Bayesian Meta-Learning Approach", arXiv, November 2022.
    BibTeX arXiv
    • @article{Chakrabarty2022nov,
    • author = {Chakrabarty, Ankush},
    • title = {Optimizing Closed-Loop Performance with Data from Similar Systems: A Bayesian Meta-Learning Approach},
    • journal = {arXiv},
    • year = 2022,
    • month = nov,
    • url = {https://arxiv.org/abs/2211.00077}
    • }
  •  Zhan, S., Wichern, G., Laughman, C.R., Chong, A., Chakrabarty, A., "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}
    • }
  •  Menner, M., Chakrabarty, A., Berntorp, K., Di Cairano, S., "Learning Optimization-based Control Policies Directly from Digital Twin Simulations", IEEE Conference on Control Technology and Applications (CCTA), August 2022.
    BibTeX TR2022-108 PDF
    • @inproceedings{Menner2022aug,
    • author = {Menner, Marcel and Chakrabarty, Ankush and Berntorp, Karl and Di Cairano, Stefano},
    • title = {Learning Optimization-based Control Policies Directly from Digital Twin Simulations},
    • booktitle = {IEEE Conference on Control Technology and Applications (CCTA)},
    • year = 2022,
    • month = aug,
    • url = {https://www.merl.com/publications/TR2022-108}
    • }
  •  Nasrin, S., Shylendra, A., Darabi, N., Tulabandhula, T., Gomes, W., Chakrabarty, A., Trivedi, A., "ENOS: Energy-aware Network Operator Search in Deep Neural Networks", IEEE Access, DOI: 10.1109/​ACCESS.2022.3192515, July 2022.
    BibTeX IEEE Access
    • @article{Nasrin2022jul,
    • author = {Nasrin, Shamma and Shylendra, Ahish and Darabi, Nastaran and Tulabandhula, Theja and Gomes, Wilfred and Chakrabarty, Ankush and Trivedi, Amit},
    • title = {ENOS: Energy-aware Network Operator Search in Deep Neural Networks},
    • journal = {IEEE Access},
    • year = 2022,
    • month = jul,
    • doi = {10.1109/ACCESS.2022.3192515},
    • url = {https://ieeexplore.ieee.org/document/9833492}
    • }
  •  Chakrabarty, A., Burns, D.J., Guay, M., Laughman, C.R., "Rapid Energy Optimization Of Vapor Compression Systems Using Probabilistic Machine Learning And Extremum Seeking Control", International Refrigeration and Air Conditioning Conference (IRACC), July 2022.
    BibTeX External
    • @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 (IRACC)},
    • year = 2022,
    • month = jul,
    • url = {https://docs.lib.purdue.edu/iracc/2428/}
    • }
  •  Xu, W., Jones, C., Svetozarevic, B., Laughman, C.R., Chakrabarty, A., "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}
    • }
  •  Danielson, C., Bortoff, S.A., Chakrabarty, A., "Extremum Seeking Control with an Adaptive Gain Based On Gradient Estimation Error", IEEE Transactions on Systems Man and Cybernetics: Systems, DOI: 10.1109/​TSMC.2022.3171132, May 2022.
    BibTeX
    • @article{Danielson2022may,
    • author = {Danielson, Claus and Bortoff, Scott A. and Chakrabarty, Ankush},
    • title = {Extremum Seeking Control with an Adaptive Gain Based On Gradient Estimation Error},
    • journal = {IEEE Transactions on Systems Man and Cybernetics: Systems},
    • year = 2022,
    • month = may,
    • doi = {10.1109/TSMC.2022.3171132}
    • }
  •  Vinod, A.P., Safaoui, S., Chakrabarty, A., Quirynen, R., Yoshikawa, N., Di Cairano, S., "Safe multi-agent motion planning via filtered reinforcement learning", IEEE International Conference on Robotics and Automation (ICRA), DOI: 10.1109/​ICRA46639.2022.9812259, May 2022, pp. 7270-7276.
    BibTeX TR2022-053 PDF Video
    • @inproceedings{Vinod2022may,
    • author = {Vinod, Abraham P. and Safaoui, Sleiman and Chakrabarty, Ankush and Quirynen, Rien and Yoshikawa, Nobuyuki and Di Cairano, Stefano},
    • title = {Safe multi-agent motion planning via filtered reinforcement learning},
    • booktitle = {IEEE International Conference on Robotics and Automation (ICRA)},
    • year = 2022,
    • pages = {7270--7276},
    • month = may,
    • publisher = {IEEE},
    • doi = {10.1109/ICRA46639.2022.9812259},
    • isbn = {978-1-7281-9681-7},
    • url = {https://www.merl.com/publications/TR2022-053}
    • }
  •  Ma, Y., Guo, J., Wang, Y., Chakrabarty, A., Ahn, H., Orlik, P.V., Guan, X., Lu, C., "Optimal Dynamic Transmission Scheduling for Wireless Networked Control Systems", IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, DOI: 10.1109/​TCST.2022.3141581, May 2022.
    BibTeX TR2022-043 PDF
    • @article{Ma2022may,
    • author = {Ma, Yehan and Guo, Jianlin and Wang, Yebin and Chakrabarty, Ankush and Ahn, Heejin and Orlik, Philip V. and Guan, Xinping and Lu, Chenyang},
    • title = {Optimal Dynamic Transmission Scheduling for Wireless Networked Control Systems},
    • journal = {IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY},
    • year = 2022,
    • month = may,
    • doi = {10.1109/TCST.2022.3141581},
    • url = {https://www.merl.com/publications/TR2022-043}
    • }
  •  Cauligi, A., Chakrabarty, A., Di Cairano, S., Quirynen, R., "PRISM: Recurrent Neural Networks and Presolve Methods for Fast Mixed-integer Optimal Control", Learning for Dynamics and Control Conference (L4DC), April 2022, pp. 34-46.
    BibTeX TR2022-039 PDF
    • @inproceedings{Cauligi2022apr,
    • author = {Cauligi, Abhishek and Chakrabarty, Ankush and Di Cairano, Stefano and Quirynen, Rien},
    • title = {PRISM: Recurrent Neural Networks and Presolve Methods for Fast Mixed-integer Optimal Control},
    • booktitle = {Learning for Dynamics and Control Conference (L4DC)},
    • year = 2022,
    • pages = {34--46},
    • month = apr,
    • publisher = {Proceedings of Machine Learning Research (PMLR)},
    • url = {https://www.merl.com/publications/TR2022-039}
    • }
  •  Wang, S., Taha, A., Chakrabarty, A., Sela, L., Abokifa, A., "Model Order Reduction for Water Quality Dynamics", Water Resources Research, DOI: 10.1029/​2021WR029856, April 2022.
    BibTeX
    • @article{Wang2022apr,
    • author = {Wang, Shen and Taha, Ahmad and Chakrabarty, Ankush and Sela, Lina and Abokifa, Ahmed},
    • title = {Model Order Reduction for Water Quality Dynamics},
    • journal = {Water Resources Research},
    • year = 2022,
    • month = apr,
    • doi = {10.1029/2021WR029856}
    • }
  •  Chakrabarty, A., Maddalena, E., Qiao, H., Laughman, C.R., "Scalable Bayesian Optimization for Model Calibration: Case Study on Coupled Building and HVAC Dynamics", Energy and Buildings, DOI: 10.1016/​j.enbuild.2021.111460, Vol. 253, pp. 111460, March 2022.
    BibTeX TR2022-030 PDF
    • @article{Chakrabarty2022mar,
    • author = {Chakrabarty, Ankush and Maddalena, Emilio and Qiao, Hongtao and Laughman, Christopher R.},
    • title = {Scalable Bayesian Optimization for Model Calibration: Case Study on Coupled Building and HVAC Dynamics},
    • journal = {Energy and Buildings},
    • year = 2022,
    • volume = 253,
    • pages = 111460,
    • month = mar,
    • doi = {10.1016/j.enbuild.2021.111460},
    • url = {https://www.merl.com/publications/TR2022-030}
    • }
  •  Chakrabarty, A., Danielson, C., Bortoff, S.A., Laughman, C.R., "Accelerating self-optimization control of refrigerant cycles with Bayesian optimization and adaptive moment estimation", Applied Thermal Engineering, DOI: 10.1016/​j.applthermaleng.2021.117335, Vol. 197, pp. 117335, February 2022.
    BibTeX TR2022-010 PDF
    • @article{Chakrabarty2022feb,
    • author = {Chakrabarty, Ankush and Danielson, Claus and Bortoff, Scott A. and Laughman, Christopher R.},
    • title = {Accelerating self-optimization control of refrigerant cycles with Bayesian optimization and adaptive moment estimation},
    • journal = {Applied Thermal Engineering},
    • year = 2022,
    • volume = 197,
    • pages = 117335,
    • month = feb,
    • doi = {10.1016/j.applthermaleng.2021.117335},
    • url = {https://www.merl.com/publications/TR2022-010}
    • }
  •  Vijayshankar, S., Chakrabarty, A., Grover, P., Nabi, S., "Co-Design of Reduced-Order Models and Observers from Thermo-Fluid Data", IFAC Journal of Systems and Control, DOI: 10.1016/​j.ifacsc.2021.100181, Vol. 19, pp. 100181, January 2022.
    BibTeX TR2022-009 PDF
    • @article{Vijayshankar2022jan,
    • author = {Vijayshankar, Sanjana and Chakrabarty, Ankush and Grover, Piyush and Nabi, Saleh},
    • title = {Co-Design of Reduced-Order Models and Observers from Thermo-Fluid Data},
    • journal = {IFAC Journal of Systems and Control},
    • year = 2022,
    • volume = 19,
    • pages = 100181,
    • month = jan,
    • doi = {10.1016/j.ifacsc.2021.100181},
    • url = {https://www.merl.com/publications/TR2022-009}
    • }
  •  Jeon, W., Chakrabarty, A., Zemouche, A., Rajamani, R., "Simultaneous State Estimation and Tire Model Learning for Autonomous Vehicle Applications", IEEE/ASME Transactions on Mechatronics, DOI: 10.1109/​TMECH.2021.3081035, Vol. 26, No. 4, pp. 1941-1950, January 2022.
    BibTeX TR2022-003 PDF
    • @article{Jeon2022jan,
    • author = {Jeon, Woongsun and Chakrabarty, Ankush and Zemouche, Ali and Rajamani, Rajesh},
    • title = {Simultaneous State Estimation and Tire Model Learning for Autonomous Vehicle Applications},
    • journal = {IEEE/ASME Transactions on Mechatronics},
    • year = 2022,
    • volume = 26,
    • number = 4,
    • pages = {1941--1950},
    • month = jan,
    • doi = {10.1109/TMECH.2021.3081035},
    • url = {https://www.merl.com/publications/TR2022-003}
    • }
  •  Zhan, S., Wichern, G., Laughman, C.R., Chakrabarty, A., "Meta-Learned Bayesian Optimization for Building Model Calibration using Attentive Neural Processes", Advances in Neural Information Processing Systems (NeurIPS), December 2021.
    BibTeX TR2021-149 PDF
    • @inproceedings{Zhan2021dec,
    • author = {Zhan, Sicheng and Wichern, Gordon and Laughman, Christopher R. and Chakrabarty, Ankush},
    • title = {Meta-Learned Bayesian Optimization for Building Model Calibration using Attentive Neural Processes},
    • booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
    • year = 2021,
    • month = dec,
    • url = {https://www.merl.com/publications/TR2021-149}
    • }
  •  Berntorp, K., Chakrabarty, A., Di Cairano, S., "Vehicle Rollover Avoidance by Parameter-Adaptive Reference Governor", IEEE Conference on Decision and Control (CDC), DOI: 10.1109/​CDC45484.2021.9683770, December 2021, pp. 635-640.
    BibTeX TR2021-151 PDF
    • @inproceedings{Berntorp2021dec,
    • author = {Berntorp, Karl and Chakrabarty, Ankush and Di Cairano, Stefano},
    • title = {Vehicle Rollover Avoidance by Parameter-Adaptive Reference Governor},
    • booktitle = {IEEE Conference on Decision and Control (CDC)},
    • year = 2021,
    • pages = {635--640},
    • month = dec,
    • doi = {10.1109/CDC45484.2021.9683770},
    • url = {https://www.merl.com/publications/TR2021-151}
    • }
  •  Srinivasan, M., Chakrabarty, A., Quirynen, R., yoshikawa, N., Mariyama, T., Di Cairano, S., "Fast Multi-Robot Motion Planning via Imitation Learning of Mixed-Integer Programs", IFAC Modeling, Estimation and Control Conference (MECC), DOI: 10.1016/​j.ifacol.2021.11.237, October 2021, pp. 598-604.
    BibTeX TR2021-134 PDF Video
    • @inproceedings{Srinivasan2021oct,
    • author = {Srinivasan, Mohit and Chakrabarty, Ankush and Quirynen, Rien and yoshikawa, nobuyuki and Mariyama, Toshisada and Di Cairano, Stefano},
    • title = {Fast Multi-Robot Motion Planning via Imitation Learning of Mixed-Integer Programs},
    • booktitle = {IFAC Modeling, Estimation and Control Conference (MECC)},
    • year = 2021,
    • pages = {598--604},
    • month = oct,
    • doi = {10.1016/j.ifacol.2021.11.237},
    • url = {https://www.merl.com/publications/TR2021-134}
    • }
  •  Chakrabarty, A., Quirynen, R., Romeres, D., Di Cairano, S., "Learning Disagreement Regions with Deep Neural Networks to Reduce Practical Complexity of Mixed-Integer MPC", IEEE International Conference on Systems, Man, and Cybernetics, DOI: 10.1109/​SMC52423.2021.9659186, October 2021, pp. 3238-3244.
    BibTeX TR2021-126 PDF Video
    • @inproceedings{Chakrabarty2021oct,
    • author = {Chakrabarty, Ankush and Quirynen, Rien and Romeres, Diego and Di Cairano, Stefano},
    • title = {Learning Disagreement Regions with Deep Neural Networks to Reduce Practical Complexity of Mixed-Integer MPC},
    • booktitle = {IEEE International Conference on Systems, Man, and Cybernetics},
    • year = 2021,
    • pages = {3238--3244},
    • month = oct,
    • doi = {10.1109/SMC52423.2021.9659186},
    • url = {https://www.merl.com/publications/TR2021-126}
    • }
  •  Chakrabarty, A., Bortoff, S.A., Laughman, C.R., "Simulation Failure Robust Bayesian Optimization for Estimating Black-Box Model Parameters", IEEE International Conference on Systems, Man, and Cybernetics (SMC), DOI: 10.1109/​SMC52423.2021.9658893, October 2021.
    BibTeX TR2021-128 PDF Video
    • @inproceedings{Chakrabarty2021oct2,
    • author = {Chakrabarty, Ankush and Bortoff, Scott A. and Laughman, Christopher R.},
    • title = {Simulation Failure Robust Bayesian Optimization for Estimating Black-Box Model Parameters},
    • booktitle = {IEEE International Conference on Systems, Man, and Cybernetics (SMC)},
    • year = 2021,
    • month = oct,
    • doi = {10.1109/SMC52423.2021.9658893},
    • url = {https://www.merl.com/publications/TR2021-128}
    • }
  •  Wichern, G., Chakrabarty, A., Wang, Z.-Q., Le Roux, J., "Anomalous sound detection using attentive neural processes", IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), DOI: 10.1109/​WASPAA52581.2021.9632762, October 2021, pp. 186-190.
    BibTeX TR2021-129 PDF
    • @inproceedings{Wichern2021oct,
    • author = {Wichern, Gordon and Chakrabarty, Ankush and Wang, Zhong-Qiu and Le Roux, Jonathan},
    • title = {Anomalous sound detection using attentive neural processes},
    • booktitle = {IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA)},
    • year = 2021,
    • pages = {186--190},
    • month = oct,
    • publisher = {IEEE},
    • doi = {10.1109/WASPAA52581.2021.9632762},
    • url = {https://www.merl.com/publications/TR2021-129}
    • }
  •  Chakrabarty, A., Maddalena, E., Qiao, H., Laughman, C.R., "Data-driven calibration of physics-informed models of joint building/equipment dynamics using Bayesian optimization", 2021 Building Simulation Conference, September 2021.
    BibTeX TR2021-105 PDF Video
    • @inproceedings{Chakrabarty2021sep,
    • author = {Chakrabarty, Ankush and Maddalena, Emilio and Qiao, Hongtao and Laughman, Christopher R.},
    • title = {Data-driven calibration of physics-informed models of joint building/equipment dynamics using Bayesian optimization},
    • booktitle = {2021 Building Simulation Conference},
    • year = 2021,
    • month = sep,
    • url = {https://www.merl.com/publications/TR2021-105}
    • }
  •  Chakrabarty, A., Benosman, M., "Safe Learning-based Observers for Unknown Nonlinear Systems using Bayesian Optimization", Automatica, DOI: 10.1016/​j.automatica.2021.109860, August 2021.
    BibTeX TR2021-101 PDF
    • @article{Chakrabarty2021aug,
    • author = {Chakrabarty, Ankush and Benosman, Mouhacine},
    • title = {Safe Learning-based Observers for Unknown Nonlinear Systems using Bayesian Optimization},
    • journal = {Automatica},
    • year = 2021,
    • month = aug,
    • doi = {10.1016/j.automatica.2021.109860},
    • url = {https://www.merl.com/publications/TR2021-101}
    • }
  •  Chakrabarty, A., Wichern, G., Laughman, C.R., "ANP-BBO: Attentive Neural Processes and Batch Bayesian Optimization for Scalable Calibration of Physics-Informed Digital Twins", International Conference on Machine Learning (ICML), July 2021.
    BibTeX TR2021-086 PDF
    • @inproceedings{Chakrabarty2021jul,
    • author = {Chakrabarty, Ankush and Wichern, Gordon and Laughman, Christopher R.},
    • title = {ANP-BBO: Attentive Neural Processes and Batch Bayesian Optimization for Scalable Calibration of Physics-Informed Digital Twins},
    • booktitle = {International Conference on Machine Learning (ICML)},
    • year = 2021,
    • month = jul,
    • url = {https://www.merl.com/publications/TR2021-086}
    • }