Ankush Chakrabarty

95 papers A* 2B 3C 17Journal 48Unranked 24

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Manifold meta-learning for reduced-complexity neural system identification. CoRR Marco Forgione, Ankush Chakrabarty, Dario Piga, Matteo Rufolo, Alberto Bemporad
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	C	`conf`	Navigating the Trade-offs and Synergies of Economic and Environmental Sustainability Using Process Systems Engineering. ACC Qi Zhang, Styliani Avraamidou, Joel A. Paulson, Vyom Thakker, Zhenyu Wang, Leo Chiang, Birgit Braun, Tushar Rathi, Ankush Chakrabarty, Farshud Sorourifar, Wei-Ting Tang, Paola Munoz, Apoorva Sampat, France Guertin
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
2025	A*	`conf`	User Preference Meets Pareto-Optimality in Multi-Objective Bayesian Optimization. AAAI Joshua Hang Sai Ip, Ankush Chakrabarty, Ali Mesbah, Diego Romeres
2025	J	`jnl`	User-Preference Meets Pareto-Optimality: Multi-Objective Bayesian Optimization with Local Gradient Search. CoRR Joshua Hang Sai Ip, Ankush Chakrabarty, Ali Mesbah, Diego Romeres
2024	C	`conf`	Aircraft Approach Management Using Reachability and Dynamic Programming. ACC Abraham P. Vinod, Sachiyo Yamazaki, Ankush Chakrabarty, Nobuyuki Yoshikawa, Stefano Di Cairano
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	J	`jnl`	BEACON: A Bayesian Optimization Strategy for Novelty Search in Expensive Black-Box Systems. CoRR Wei-Ting Tang, Ankush Chakrabarty, Joel A. Paulson
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	J	`jnl`	Coactive Preference-Guided Multi-Objective Bayesian Optimization: An Application to Policy Learning in Personalized Plasma Medicine. IEEE Control. Syst. Lett. Ketong Shao, Ankush Chakrabarty, Ali Mesbah, Diego Romeres
2024	—	`conf`	MPC of Uncertain Nonlinear Systems with Meta-Learning for Fast Adaptation of Neural Predictive Models. CASE Jiaqi Yan, Ankush Chakrabarty, Alisa Rupenyan, John Lygeros
2024	J	`jnl`	MPC of Uncertain Nonlinear Systems with Meta-Learning for Fast Adaptation of Neural Predictive Models. CoRR Jiaqi Yan, Ankush Chakrabarty, Alisa Rupenyan, John Lygeros
2024	—	`conf`	Physics-Constrained Meta-Learning for Online Adaptation and Estimation in Positioning Applications. CDC Ankush Chakrabarty, Vedang M. Deshpande, Gordon Wichern, Karl Berntorp
2024	J	`jnl`	Safe Multiagent Motion Planning Under Uncertainty for Drones Using Filtered Reinforcement Learning. IEEE Trans. Robotics Sleiman Safaoui, Abraham P. Vinod, Ankush Chakrabarty, Rien Quirynen, Nobuyuki Yoshikawa, Stefano Di Cairano
2023	J	`jnl`	Extremum Seeking Control With an Adaptive Gain Based on Gradient Estimation Error. IEEE Trans. Syst. Man Cybern. Syst. Claus Danielson, Scott A. Bortoff, Ankush Chakrabarty
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	C	`conf`	Physics-Informed Machine Learning for Modeling and Control of Dynamical Systems. ACC Truong X. Nghiem, Ján Drgona, Colin N. Jones, Zoltán Nagy, Roland Schwan, Biswadip Dey, Ankush Chakrabarty, Stefano Di Cairano, Joel A. Paulson, Andrea Carron, Melanie N. Zeilinger, Wenceslao Shaw-Cortez, Draguna L. Vrabie
2023	J	`jnl`	Physics-Informed Machine Learning for Modeling and Control of Dynamical Systems. CoRR Truong X. Nghiem, Ján Drgona, Colin N. Jones, Zoltán Nagy, Roland Schwan, Biswadip Dey, Ankush Chakrabarty, Stefano Di Cairano, Joel A. Paulson, Andrea Carron, Melanie N. Zeilinger, Wenceslao Shaw-Cortez, Draguna L. Vrabie
2023	J	`jnl`	Safe multi-agent motion planning under uncertainty for drones using filtered reinforcement learning. CoRR Sleiman Safaoui, Abraham P. Vinod, Ankush Chakrabarty, Rien Quirynen, Nobuyuki Yoshikawa, Stefano Di Cairano
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	J	`jnl`	Active Learning for Estimating Reachable Sets for Systems With Unknown Dynamics. IEEE Trans. Cybern. Ankush Chakrabarty, Claus Danielson, Stefano Di Cairano, Arvind U. Raghunathan
2022	J	`jnl`	Co-design of reduced-order models and observers from thermo-fluid data. IFAC J. Syst. Control. Sanjana Vijayshankar, Ankush Chakrabarty, Piyush Grover, Saleh Nabi
2022	J	`jnl`	Data-Driven Identification of Dynamic Quality Models in Drinking Water Networks. CoRR Shen Wang, Ankush Chakrabarty, Ahmad F. Taha
2022	J	`jnl`	ENOS: Energy-Aware Network Operator Search in Deep Neural Networks. IEEE Access Shamma Nasrin, Ahish Shylendra, Nastaran Darabi, Theja Tulabandhula, Wilfred Gomes, Ankush Chakrabarty, Amit Ranjan Trivedi
2022	—	`conf`	Efficient Multi-Step Lookahead Bayesian Optimization with Local Search Constraints. CDC Joel A. Paulson, Farshud Sorourifar, Ankush Chakrabarty
2022	—	`conf`	Learning Optimization-based Control Policies Directly from Digital Twin Simulations. CCTA Marcel Menner, Ankush Chakrabarty, Karl Berntorp, Stefano Di Cairano
2022	J	`jnl`	Meta-Learning of Neural State-Space Models Using Data From Similar Systems. CoRR Ankush Chakrabarty, Gordon Wichern, Christopher R. Laughman
2022	J	`jnl`	Optimal Dynamic Transmission Scheduling for Wireless Networked Control Systems. IEEE Trans. Control. Syst. Technol. Yehan Ma, Jianlin Guo, Yebin Wang, Ankush Chakrabarty, Heejin Ahn, Philip V. Orlik, Xinping Guan, Chenyang Lu
2022	—	`conf`	Optimizing Closed-Loop Performance with Data from Similar Systems: A Bayesian Meta-Learning Approach. CDC Ankush Chakrabarty
2022	J	`jnl`	Optimizing Closed-Loop Performance with Data from Similar Systems: A Bayesian Meta-Learning Approach. CoRR Ankush Chakrabarty
2022	—	`conf`	PRISM: Recurrent Neural Networks and Presolve Methods for Fast Mixed-integer Optimal Control. L4DC Abhishek Cauligi, Ankush Chakrabarty, Stefano Di Cairano, Rien Quirynen
2022	A*	`conf`	Safe multi-agent motion planning via filtered reinforcement learning. ICRA Abraham P. Vinod, Sleiman Safaoui, Ankush Chakrabarty, Rien Quirynen, Nobuyuki Yoshikawa, Stefano Di Cairano
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	—	`conf`	Anomalous Sound Detection Using Attentive Neural Processes. WASPAA Gordon Wichern, Ankush Chakrabarty, Zhong-Qiu Wang, Jonathan Le Roux
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	J	`jnl`	Extremum Seeking Control with an Adaptive Gain Based On Gradient Estimation Error. CoRR Claus Danielson, Scott A. Bortoff, Ankush Chakrabarty
2021	B	`conf`	Learning Disagreement Regions with Deep Neural Networks to Reduce Practical Complexity of Mixed-Integer MPC. SMC Ankush Chakrabarty, Rien Quirynen, Diego Romeres, Stefano Di Cairano
2021	J	`jnl`	Model Order Reduction for Water Quality Dynamics. CoRR Shen Wang, Ahmad F. Taha, Ankush Chakrabarty, Lina Sela, Ahmed A. Abokifa
2021	J	`jnl`	Safe Approximate Dynamic Programming via Kernelized Lipschitz Estimation. IEEE Trans. Neural Networks Learn. Syst. Ankush Chakrabarty, Devesh K. Jha, Gregery T. Buzzard, Yebin Wang, Kyriakos G. Vamvoudakis
2021	J	`jnl`	Safe learning-based observers for unknown nonlinear systems using Bayesian optimization. Autom. Ankush Chakrabarty, Mouhacine Benosman
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
2021	C	`conf`	Vehicle Center-of-Gravity Height and Dynamics Estimation with Uncertainty Quantification by Marginalized Particle Filter. ACC Karl Berntorp, Ankush Chakrabarty, Stefano Di Cairano
2021	—	`conf`	Vehicle Rollover Avoidance by Parameter-Adaptive Reference Governor. CDC Karl Berntorp, Ankush Chakrabarty, Stefano Di Cairano
2020	—	`conf`	Data-Driven Optimal Tracking with Constrained Approximate Dynamic Programming for Servomotor Systems. CCTA Ankush Chakrabarty, Claus Danielson, Yebin Wang
2020	C	`conf`	Dynamic Mode Decomposition and Robust Estimation: Case Study of a 2D Turbulent Boussinesq Flow. ACC Sanjana Vijayshankar, Saleh Nabi, Ankush Chakrabarty, Piyush Grover, Mouhacine Benosman
2020	J	`jnl`	Embedded Model Predictive Control for a Wearable Artificial Pancreas. IEEE Trans. Control. Syst. Technol. Ankush Chakrabarty, Elizabeth Healey, Dawei Shi, Stamatina Zavitsanou, Francis J. Doyle, Eyal Dassau
2020	J	`jnl`	Embedding Approximate Nonlinear Model Predictive Control at Ultrahigh Speed and Extremely Low Power. IEEE Trans. Control. Syst. Technol. Arnab Raha, Ankush Chakrabarty, Vijay Raghunathan, Gregery T. Buzzard
2020	C	`conf`	Learning-based Parameter-Adaptive Reference Governors. ACC Ankush Chakrabarty, Karl Berntorp, Stefano Di Cairano
2020	J	`jnl`	Safe Learning-based Observers for Unknown Nonlinear Systems using Bayesian Optimization. CoRR Ankush Chakrabarty, Mouhacine Benosman
2019	—	`conf`	Approximate Dynamic Programming For Linear Systems with State and Input Constraints. ECC Ankush Chakrabarty, Rien Quirynen, Claus Danielson, Weinan Gao
2019	J	`jnl`	Approximate Dynamic Programming For Linear Systems with State and Input Constraints. CoRR Ankush Chakrabarty, Rien Quirynen, Claus Danielson, Weinan Gao
2019	C	`conf`	Data-Driven Control Policies for Partially Known Systems via Kernelized Lipschitz Learning. ACC Ankush Chakrabarty, Devesh K. Jha, Yebin Wang
2019	J	`jnl`	Highly Accurate and Efficient Data-Driven Methods for Genotype Imputation. IEEE ACM Trans. Comput. Biol. Bioinform. Olivia Choudhury, Ankush Chakrabarty, Scott J. Emrich
2019	J	`jnl`	L2 Observers for a Class of Nonlinear Systems with Unknown Inputs. CoRR Martin J. Corless, Ankush Chakrabarty
2019	—	`conf`	L2Observers for a Class of Nonlinear Systems with Unknown Inputs. ECC Martin Corless, Ankush Chakrabarty
2019	—	`conf`	Learning autonomous vehicle passengers' preferred driving styles using g-g plots and haptic feedback. ITSC Uros Kalabic, Ankush Chakrabarty, Rien Quirynen, Stefano Di Cairano
2019	B	`conf`	Near-Optimal Control of Motor Drives via Approximate Dynamic Programming. SMC Yebin Wang, Ankush Chakrabarty, MengChu Zhou, Jinyun Zhang
2019	—	`conf`	Optimal dynamic scheduling of wireless networked control systems. ICCPS Yehan Ma, Jianlin Guo, Yebin Wang, Ankush Chakrabarty, Heejin Ahn, Philip V. Orlik, Chenyang Lu
2019	J	`jnl`	Pharmaceutical-based entrainment of circadian phase via nonlinear model predictive control. Autom. John H. Abel, Ankush Chakrabarty, Elizabeth B. Klerman, Francis J. Doyle III
2019	—	`conf`	Robust Data-Driven Neuro-Adaptive Observers With Lipschitz Activation Functions. CDC Ankush Chakrabarty, Ali Zemouche, Rajesh Rajamani, Mouhacine Benosman
2019	J	`jnl`	Safe Approximate Dynamic Programming Via Kernelized Lipschitz Estimation. CoRR Ankush Chakrabarty, Devesh K. Jha, Gregery T. Buzzard, Yebin Wang, Kyriakos G. Vamvoudakis
2018	—	`conf`	Data-Driven Estimation of Backward Reachable and Invariant Sets for Unmodeled Systems via Active Learning. CDC Ankush Chakrabarty, Arvind U. Raghunathan, Stefano Di Cairano, Claus Danielson
2018	C	`conf`	Deep Learning Assisted Macronutrient Estimation For Feedforward-Feedback Control In Artificial Pancreas Systems. ACC Ankush Chakrabarty, Francis J. Doyle, Eyal Dassau
2018	J	`jnl`	Event-Triggered Model Predictive Control for Embedded Artificial Pancreas Systems. IEEE Trans. Biomed. Eng. Ankush Chakrabarty, Stamatina Zavitsanou, Francis J. Doyle, Eyal Dassau
2018	J	`jnl`	State and unknown input observers for nonlinear systems with delayed measurements. Autom. Ankush Chakrabarty, Emilia Fridman, Stanislaw H. Zak, Gregery T. Buzzard
2018	J	`jnl`	Unknown Input Estimation for Nonlinear Systems Using Sliding Mode Observers and Smooth Window Functions. SIAM J. Control. Optim. Ankush Chakrabarty, Ann E. Rundell, Stanislaw H. Zak, Fanglai Zhu, Gregery T. Buzzard
2017	J	`jnl`	Delayed unknown input observers for discrete-time linear systems with guaranteed performance. Syst. Control. Lett. Ankush Chakrabarty, Raid Ayoub, Stanislaw H. Zak, Shreyas Sundaram
2017	—	`conf`	Model predictive control with event-triggered communication for an embedded artificial pancreas. CCTA Ankush Chakrabarty, Stamatina Zavitsanou, Francis J. Doyle, Eyal Dassau
2017	J	`jnl`	Output-Tracking Quantized Explicit Nonlinear Model Predictive Control Using Multiclass Support Vector Machines. IEEE Trans. Ind. Electron. Ankush Chakrabarty, Gregery T. Buzzard, Stanislaw H. Zak
2017	C	`conf`	Reducing controller updates via event-triggered model predictive control in an embedded artificial pancreas. ACC Ankush Chakrabarty, Stamatina Zavitsanou, Francis J. Doyle, Eyal Dassau
2017	C	`conf`	Robust state and unknown input estimation for nonlinear systems characterized by incremental multiplier matrices. ACC Stanislaw H. Zak, Ankush Chakrabarty, Gregery T. Buzzard
2017	J	`jnl`	State and Unknown Input Observers for Nonlinear Systems With Bounded Exogenous Inputs. IEEE Trans. Autom. Control. Ankush Chakrabarty, Martin J. Corless, Gregery T. Buzzard, Stanislaw H. Zak, Ann E. Rundell
2017	J	`jnl`	Support Vector Machine Informed Explicit Nonlinear Model Predictive Control Using Low-Discrepancy Sequences. IEEE Trans. Autom. Control. Ankush Chakrabarty, Vu C. Dinh, Martin J. Corless, Ann E. Rundell, Stanislaw H. Zak, Gregery T. Buzzard
2017	C	`conf`	Ultrafast embedded explicit model predictive control for nonlinear systems. ACC Arnab Raha, Ankush Chakrabarty, Vijay Raghunathan, Gregery T. Buzzard
2016	C	`conf`	Distributed unknown input observers for interconnected nonlinear systems. ACC Ankush Chakrabarty, Shreyas Sundaram, Martin J. Corless, Gregery T. Buzzard, Stanislaw H. Zak, Ann E. Rundell
2016	—	`conf`	HAPI-Gen: Highly Accurate Phasing and Imputation of Genotype Data. BCB Olivia Choudhury, Ankush Chakrabarty, Scott J. Emrich
2016	J	`jnl`	Nonfragile Fault-Tolerant Fuzzy Observer-Based Controller Design for Nonlinear Systems. IEEE Trans. Fuzzy Syst. Xiaohang Li, Fanglai Zhu, Ankush Chakrabarty, Stanislaw H. Zak
2016	—	`conf`	Sampling-based explicit nonlinear model predictive control for output tracking. CDC Haotian Zhang, Ankush Chakrabarty, Raid Ayoub, Gregery T. Buzzard, Shreyas Sundaram
2016	—	`conf`	State and unknown input observers for discrete-time nonlinear systems. CDC Ankush Chakrabarty, Stanislaw H. Zak, Shreyas Sundaram
2016	—	`—`	Supervised learning-based explicit nonlinear model predictive control and unknown input estimation in biomedical systems Ankush Chakrabarty
2016	—	`conf`	Unknown input estimation via observers for nonlinear systems with measurement delays. CDC Ankush Chakrabarty, Gregery T. Buzzard, Emilia Fridman, Stanislaw H. Zak
2015	J	`jnl`	Simultaneous Unknown Input And Sensor Noise Reconstruction For Nonlinear Systems With Boundary Layer Sliding Mode Observers. CoRR Ankush Chakrabarty, Gregery T. Buzzard, Stanislaw H. Zak, Fanglai Zhu, Ann E. Rundell
2014	—	`conf`	Correcting hypothalamic-pituitary-adrenal axis dysfunction using observer-based explicit nonlinear model predictive control. EMBC Ankush Chakrabarty, Gregery T. Buzzard, Martin J. Corless, Stanislaw H. Zak, Ann E. Rundell
2014	C	`conf`	Robust explicit nonlinear model predictive control with integral sliding mode. ACC Ankush Chakrabarty, Vu C. Dinh, Gregery T. Buzzard, Stanislaw H. Zak, Ann E. Rundell
2013	C	`conf`	Treating acute myeloid leukemia via HSC transplantation: A preliminary study of multi-objective personalization strategies. ACC Ankush Chakrabarty, Serena M. Pearce, Robert P. Nelson, Ann E. Rundell
2013	J	`jnl`	Volterra kernel based face recognition using artificial bee colonyoptimization. Eng. Appl. Artif. Intell. Ankush Chakrabarty, Harsh Jain, Amitava Chatterjee
2012	J	`jnl`	Hyperspectral image classification incorporating bacterial foraging-optimized spectral weighting. Artif. Intell. Res. Ankush Chakrabarty, Olivia Choudhury, Pallab Sarkar, Avishek Paul, Debarghya Sarkar
2011	J	`jnl`	Feedback linearizing indirect adaptive fuzzy control with foraging based on-line plant model estimation. Appl. Soft Comput. Suvadeep Banerjee, Ankush Chakrabarty, Sayan Maity, Amitava Chatterjee