Souvik Chakraborty

102 papers A* 1Journal 101

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A dual physics-informed neural network for topology optimization. J. Comput. Phys. Ajendra Singh, Souvik Chakraborty, Rajib Chowdhury
2026	J	`jnl`	Adversarial Vulnerabilities in Neural Operator Digital Twins: Gradient-Free Attacks on Nuclear Thermal-Hydraulic Surrogates. CoRR Samrendra Roy, Kazuma Kobayashi, Souvik Chakraborty, Rizwan Uddin, Syed Bahauddin Alam
2026	J	`jnl`	CoNBONet: Conformalized Neuroscience-inspired Bayesian Operator Network for Reliability Analysis. CoRR Shailesh Garg, Souvik Chakraborty
2026	J	`jnl`	CortiNet: A Physics-Perception Hybrid Cortical-Inspired Dual-Stream Network for Gallbladder Disease Diagnosis from Ultrasound. CoRR Vagish Kumar, Souvik Chakraborty
2026	J	`jnl`	From local interactions to global operators: Scalable Gaussian process operator for physical systems. J. Comput. Phys. Sawan Kumar, Tapas Tripura, Rajdip Nayek, Souvik Chakraborty
2026	J	`jnl`	Neural combinatorial wavelet neural operator for catastrophic forgetting free in-context operator learning of multiple partial differential equations. Comput. Phys. Commun. Tapas Tripura, Souvik Chakraborty
2026	A*	`conf`	PhyPlan: Learning to Plan Tasks with Generalizable and Rapid Physical Reasoning for Embodied Manipulation. AAAI Ankit Kanwar, Hartej Soin, Abhinav Barnawal, Mudit Chopra, Harshil Vagadia, Tamajit Banerjee, Shreshth Tuli, Rohan Paul, Souvik Chakraborty
2026	J	`jnl`	SPINONet: Scalable Spiking Physics-informed Neural Operator for Computational Mechanics Applications. CoRR Shailesh Garg, Luis Mandl, Somdatta Goswami, Souvik Chakraborty
2026	J	`jnl`	Scalable Random Wavelet Features: Efficient Non-Stationary Kernel Approximation with Convergence Guarantees. CoRR Sawan Kumar, Souvik Chakraborty
2026	J	`jnl`	TrustFed: Enabling Trustworthy Medical AI under Data Privacy Constraints. CoRR Vagish Kumar, Syed Bahauddin Alam, Souvik Chakraborty
2025	J	`jnl`	A Bayesian Approach for Discovering Time- Delayed Differential Equation from Data. CoRR Debangshu Chowdhury, Souvik Chakraborty
2025	J	`jnl`	A Bayesian approach for discovering time- delayed differential equation from data. J. Comput. Phys. Debangshu Chowdhury, Souvik Chakraborty
2025	J	`jnl`	Agentic Physical AI toward a Domain-Specific Foundation Model for Nuclear Reactor Control. CoRR Yoonpyo Lee, Kazuma Kobayashi, Sai Puppala, Sajedul Talukder, Seid Koric, Souvik Chakraborty, Syed Bahauddin Alam
2025	J	`jnl`	Competition is the key: A Game Theoretic Causal Discovery Approach. CoRR Amartya Roy, Souvik Chakraborty
2025	J	`jnl`	Cross-Domain Long-Term Forecasting: Radiation Dose from Sparse Neutron Sensor via Spatio-Temporal Operator Network. CoRR Jay Phil Yoo, Kazuma Kobayashi, Souvik Chakraborty, Syed Bahauddin Alam
2025	J	`jnl`	Deep Muscle EMG construction using A Physics-Integrated Deep Learning approach. CoRR Rajnish Kumar, Tapas Tripura, Souvik Chakraborty, Sitikantha Roy
2025	J	`jnl`	Deep muscle electromyogram construction using a physics-integrated deep learning approach. Eng. Appl. Artif. Intell. Rajnish Kumar, Tapas Tripura, Souvik Chakraborty, Sitikantha Roy
2025	J	`jnl`	Distribution free uncertainty quantification for neuroscience-inspired deep neural operators. J. Comput. Phys. Shailesh Garg, Souvik Chakraborty
2025	J	`jnl`	Distribution-Free Uncertainty-Aware Virtual Sensing via Conformalized Neural Operators. CoRR Kazuma Kobayashi, Shailesh Garg, Farid Ahmed, Souvik Chakraborty, Syed Bahauddin Alam
2025	J	`jnl`	Energy network for state estimation with random sensors and sparse labels. Comput. Phys. Commun. Yash Kumar, Tushar, Souvik Chakraborty
2025	J	`jnl`	Event-driven physics-informed operator learning for reliability analysis. CoRR Shailesh Garg, Souvik Chakraborty
2025	J	`jnl`	From Local Interactions to Global Operators: Scalable Gaussian Process Operator for Physical Systems. CoRR Sawan Kumar, Tapas Tripura, Rajdip Nayek, Souvik Chakraborty
2025	J	`jnl`	Generative flow induced neural architecture search: Towards discovering optimal architecture in wavelet neural operator. Comput. Phys. Commun. Hartej Soin, Tapas Tripura, Souvik Chakraborty
2025	J	`jnl`	Geometry adaptive waveformer for cardio-vascular modeling. Comput. Biol. Medicine Navaneeth N., Souvik Chakraborty
2025	J	`jnl`	Geometry adaptive waveformer for cardio-vascular modeling. CoRR Navaneeth N., Souvik Chakraborty
2025	J	`jnl`	Physics- and geometry-aware spatio-spectral graph neural operator for time-independent and time-dependent PDEs. CoRR Subhankar Sarkar, Souvik Chakraborty
2025	J	`jnl`	Scalable h-adaptive probabilistic solver for time-independent and time-dependent systems. CoRR Akshay Thakur, Sawan Kumar, Matthew J. Zahr, Souvik Chakraborty
2024	J	`jnl`	Continuous control of structural vibrations using hybrid deep reinforcement learning policy. Expert Syst. Appl. Jagajyoti Panda, Mudit Chopra, Vasant Matsagar, Souvik Chakraborty
2024	J	`jnl`	Deep learning accelerated efficient framework for topology optimization. Eng. Appl. Artif. Intell. Arya Prakash Padhi, Souvik Chakraborty, Anupam Chakrabarti, Rajib Chowdhury
2024	J	`jnl`	Discovering governing equation in structural dynamics from acceleration-only measurements. CoRR Calvin Alvares, Souvik Chakraborty
2024	J	`jnl`	Discovering interpretable Lagrangian of dynamical systems from data. Comput. Phys. Commun. Tapas Tripura, Souvik Chakraborty
2024	J	`jnl`	Distribution free uncertainty quantification in neuroscience-inspired deep operators. CoRR Shailesh Garg, Souvik Chakraborty
2024	J	`jnl`	FUsion-based ConstitutivE model (FuCe): Towards model-data augmentation in constitutive modelling. CoRR Tushar, Sawan Kumar, Souvik Chakraborty
2024	J	`jnl`	G CoRR Riya Arora, Niveditha Narendranath, Aman Tambi, Sandeep S. Zachariah, Souvik Chakraborty, Rohan Paul
2024	J	`jnl`	Generative adversarial wavelet neural operator: Application to fault detection and isolation of multivariate time series data. CoRR Jyoti Rani, Tapas Tripura, Hariprasad Kodamana, Souvik Chakraborty
2024	J	`jnl`	Generative flow induced neural architecture search: Towards discovering optimal architecture in wavelet neural operator. CoRR Hartej Soin, Tapas Tripura, Souvik Chakraborty
2024	J	`jnl`	Harnessing physics-informed operators for high-dimensional reliability analysis problems. CoRR Navaneeth N., Tushar, Souvik Chakraborty
2024	J	`jnl`	Hybrid variable spiking graph neural networks for energy-efficient scientific machine learning. CoRR Isha Jain, Shailesh Garg, Shaurya Shriyam, Souvik Chakraborty
2024	J	`jnl`	MD-NOMAD: Mixture density nonlinear manifold decoder for emulating stochastic differential equations and uncertainty propagation. CoRR Akshay Thakur, Souvik Chakraborty
2024	J	`jnl`	Neural Operator induced Gaussian Process framework for probabilistic solution of parametric partial differential equations. CoRR Sawan Kumar, Rajdip Nayek, Souvik Chakraborty
2024	J	`jnl`	Neuroscience inspired neural operator for partial differential equations. J. Comput. Phys. Shailesh Garg, Souvik Chakraborty
2024	J	`jnl`	PhyPlan: Compositional and Adaptive Physical Task Reasoning with Physics-Informed Skill Networks for Robot Manipulators. CoRR Harshil Vagadia, Mudit Chopra, Abhinav Barnawal, Tamajit Banerjee, Shreshth Tuli, Souvik Chakraborty, Rohan Paul
2024	J	`jnl`	PhyPlan: Generalizable and Rapid Physical Task Planning with Physics Informed Skill Networks for Robot Manipulators. CoRR Mudit Chopra, Abhinav Barnawal, Harshil Vagadia, Tamajit Banerjee, Shreshth Tuli, Souvik Chakraborty, Rohan Paul
2024	J	`jnl`	Spatio-spectral graph neural operator for solving computational mechanics problems on irregular domain and unstructured grid. CoRR Subhankar Sarkar, Souvik Chakraborty
2024	J	`jnl`	Towards Gaussian Process for operator learning: an uncertainty aware resolution independent operator learning algorithm for computational mechanics. CoRR Sawan Kumar, Rajdip Nayek, Souvik Chakraborty
2023	J	`jnl`	A Bayesian Framework for learning governing Partial Differential Equation from Data. CoRR Kalpesh Sanjay More, Tapas Tripura, Rajdip Nayek, Souvik Chakraborty
2023	J	`jnl`	A Bayesian framework for discovering interpretable Lagrangian of dynamical systems from data. CoRR Tapas Tripura, Souvik Chakraborty
2023	J	`jnl`	A foundational neural operator that continuously learns without forgetting. CoRR Tapas Tripura, Souvik Chakraborty
2023	J	`jnl`	A wavelet neural operator based elastography for localization and quantification of tumors. Comput. Methods Programs Biomed. Tapas Tripura, Abhilash Awasthi, Sitikantha Roy, Souvik Chakraborty
2023	J	`jnl`	DPA-WNO: A gray box model for a class of stochastic mechanics problem. CoRR Tushar, Souvik Chakraborty
2023	J	`jnl`	Deep Physics Corrector: A physics enhanced deep learning architecture for solving stochastic differential equations. J. Comput. Phys. Tushar, Souvik Chakraborty
2023	J	`jnl`	Discovering interpretable Lagrangian of dynamical systems from data. CoRR Tapas Tripura, Souvik Chakraborty
2023	J	`jnl`	Discovering stochastic partial differential equations from limited data using variational Bayes inference. CoRR Yogesh Chandrakant Mathpati, Tapas Tripura, Rajdip Nayek, Souvik Chakraborty
2023	J	`jnl`	Efficient hybrid topology optimization using GPU and homogenization-based multigrid approach. Eng. Comput. Arya Prakash Padhi, Souvik Chakraborty, Anupam Chakrabarti, Rajib Chowdhury
2023	J	`jnl`	Enhanced multi-fidelity modelling for digital twin and uncertainty quantification. CoRR Aarya Sheetal Desai, Navaneeth N., Sondipon Adhikari, Souvik Chakraborty
2023	J	`jnl`	Explainable, Interpretable & Trustworthy AI for Intelligent Digital Twin: Case Study on Remaining Useful Life. CoRR Kazuma Kobayashi, Bader Almutairi, Md. Nazmus Sakib, Souvik Chakraborty, Syed B. Alam
2023	J	`jnl`	MAntRA: A framework for model agnostic reliability analysis. Reliab. Eng. Syst. Saf. Yogesh Chandrakant Mathpati, Kalpesh Sanjay More, Tapas Tripura, Rajdip Nayek, Souvik Chakraborty
2023	J	`jnl`	Neuroscience inspired scientific machine learning (Part-1): Variable spiking neuron for regression. CoRR Shailesh Garg, Souvik Chakraborty
2023	J	`jnl`	Neuroscience inspired scientific machine learning (Part-2): Variable spiking wavelet neural operator. CoRR Shailesh Garg, Souvik Chakraborty
2023	J	`jnl`	Physics informed WNO. CoRR Navaneeth N., Tapas Tripura, Souvik Chakraborty
2023	J	`jnl`	Randomized prior wavelet neural operator for uncertainty quantification. CoRR Shailesh Garg, Souvik Chakraborty
2023	J	`jnl`	VB-DeepONet: A Bayesian operator learning framework for uncertainty quantification. Eng. Appl. Artif. Intell. Shailesh Garg, Souvik Chakraborty
2023	J	`jnl`	Waveformer for modelling dynamical systems. CoRR Navaneeth N., Souvik Chakraborty
2022	J	`jnl`	Assessment of DeepONet for reliability analysis of stochastic nonlinear dynamical systems. CoRR Shailesh Garg, Harshit Gupta, Souvik Chakraborty
2022	J	`jnl`	Deep Capsule Encoder-Decoder Network for Surrogate Modeling and Uncertainty Quantification. CoRR Akshay Thakur, Souvik Chakraborty
2022	J	`jnl`	Deep Physics Corrector: A physics enhanced deep learning architecture for solving stochastic differential equations. CoRR Tushar, Souvik Chakraborty
2022	J	`jnl`	Efficient hybrid topology optimization using GPU and homogenization based multigrid approach. CoRR Arya Prakash Padhi, Souvik Chakraborty, Anupam Chakrabarti, Rajib Chowdhury
2022	J	`jnl`	Energy networks for state estimation with random sensors using sparse labels. CoRR Yash Kumar, Souvik Chakraborty
2022	J	`jnl`	Koopman operator for time-dependent reliability analysis. CoRR Navaneeth N., Souvik Chakraborty
2022	J	`jnl`	MAntRA: A framework for model agnostic reliability analysis. CoRR Yogesh Chandrakant Mathpati, Kalpesh Sanjay More, Tapas Tripura, Rajdip Nayek, Souvik Chakraborty
2022	J	`jnl`	Model-agnostic stochastic model predictive control. CoRR Tapas Tripura, Souvik Chakraborty
2022	J	`jnl`	Multi-fidelity wavelet neural operator with application to uncertainty quantification. CoRR Akshay Thakur, Tapas Tripura, Souvik Chakraborty
2022	J	`jnl`	Physics-Informed Multi-Stage Deep Learning Framework Development for Digital Twin-Centred State-Based Reactor Power Prediction. CoRR James Daniell, Kazuma Kobayashi, Susmita Naskar, Dinesh Kumar, Souvik Chakraborty, Ayodeji Alajo, Ethan Taber, Joseph Graham, Syed B. Alam
2022	J	`jnl`	Probabilistic machine learning based predictive and interpretable digital twin for dynamical systems. CoRR Tapas Tripura, Aarya Sheetal Desai, Sondipon Adhikari, Souvik Chakraborty
2022	J	`jnl`	State estimation with limited sensors - A deep learning based approach. J. Comput. Phys. Yash Kumar, Pranav Bahl, Souvik Chakraborty
2022	J	`jnl`	Stochastic projection based approach for gradient free physics informed learning. CoRR Navaneeth N., Souvik Chakraborty
2022	J	`jnl`	Variational Bayes Deep Operator Network: A data-driven Bayesian solver for parametric differential equations. CoRR Shailesh Garg, Souvik Chakraborty
2022	J	`jnl`	Wavelet neural operator: a neural operator for parametric partial differential equations. CoRR Tapas Tripura, Souvik Chakraborty
2021	J	`jnl`	A change of measure enhanced near exact Euler Maruyama scheme for the solution to nonlinear stochastic dynamical systems. CoRR Tapas Tripura, Mohammad Imran, Budhaditya Hazra, Souvik Chakraborty
2021	J	`jnl`	A deep learning based surrogate model for stochastic simulators. CoRR Akshay Thakur, Souvik Chakraborty
2021	J	`jnl`	Gated Linear Model induced U-net for surrogate modeling and uncertainty quantification. CoRR Sai Krishna Mendu, Souvik Chakraborty
2021	J	`jnl`	Generalized weakly corrected Milstein solutions to stochastic differential equations. CoRR Tapas Tripura, Budhaditya Hazra, Souvik Chakraborty
2021	J	`jnl`	GrADE: A graph based data-driven solver for time-dependent nonlinear partial differential equations. CoRR Yash Kumar, Souvik Chakraborty
2021	J	`jnl`	Machine learning based digital twin for stochastic nonlinear multi-degree of freedom dynamical system. CoRR Shailesh Garg, Ankush Gogoi, Souvik Chakraborty, Budhaditya Hazra
2021	J	`jnl`	Physics-integrated hybrid framework for model form error identification in nonlinear dynamical systems. CoRR Shailesh Garg, Souvik Chakraborty, Budhaditya Hazra
2021	J	`jnl`	State estimation with limited sensors - A deep learning based approach. CoRR Yash Kumar, Pranav Bahl, Souvik Chakraborty
2021	J	`jnl`	Surrogate assisted active subspace and active subspace assisted surrogate - A new paradigm for high dimensional structural reliability analysis. CoRR Navaneeth N., Souvik Chakraborty
2021	J	`jnl`	Transfer learning based multi-fidelity physics informed deep neural network. J. Comput. Phys. Souvik Chakraborty
2020	J	`jnl`	Machine learning based digital twin for dynamical systems with multiple time-scales. CoRR Souvik Chakraborty, Sondipon Adhikari
2020	J	`jnl`	The role of surrogate models in the development of digital twins of dynamic systems. CoRR Souvik Chakraborty, Sondipon Adhikari, Ranjan Ganguli
2020	J	`jnl`	Transfer learning based multi-fidelity physics informed deep neural network. CoRR Souvik Chakraborty
2019	J	`jnl`	A Gaussian process latent force model for joint input-state estimation in linear structural systems. CoRR Rajdip Nayek, Souvik Chakraborty, Sriram Narasimhan
2019	J	`jnl`	Threshold shift method for reliability-based design optimization. CoRR Somdatta Goswami, Souvik Chakraborty, Rajib Chowdhury, Timon Rabczuk
2019	J	`jnl`	Transfer learning enhanced physics informed neural network for phase-field modeling of fracture. CoRR Somdatta Goswami, Cosmin Anitescu, Souvik Chakraborty, Timon Rabczuk
2018	J	`jnl`	Dynamical accelerated performance measure approach for efficient reliability-based design optimization with highly nonlinear probabilistic constraints. Reliab. Eng. Syst. Saf. Behrooz Keshtegar, Souvik Chakraborty
2018	J	`jnl`	Efficient data-driven reduced-order models for high-dimensional multiscale dynamical systems. Comput. Phys. Commun. Souvik Chakraborty, Nicholas Zabaras
2018	J	`jnl`	Hybrid Reliability Analysis Framework for Reliability Analysis of Tunnels. J. Comput. Civ. Eng. Souvik Chakraborty, Dipaloke Majumder
2017	J	`jnl`	A hybrid approach for global sensitivity analysis. Reliab. Eng. Syst. Saf. Souvik Chakraborty, Rajib Chowdhury
2017	J	`jnl`	An efficient algorithm for building locally refined hp - adaptive H-PCFE: Application to uncertainty quantification. J. Comput. Phys. Souvik Chakraborty, Rajib Chowdhury
2017	J	`jnl`	Moment Independent Sensitivity Analysis: H-PCFE-Based Approach. J. Comput. Civ. Eng. Souvik Chakraborty, Rajib Chowdhury
2016	J	`jnl`	Modelling uncertainty in incompressible flow simulation using Galerkin based generalized ANOVA. Comput. Phys. Commun. Souvik Chakraborty, Rajib Chowdhury
2016	J	`jnl`	Sequential experimental design based generalised ANOVA. J. Comput. Phys. Souvik Chakraborty, Rajib Chowdhury