Rishikesh Ranade

29 papers A* 1A 1Journal 25Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	A Benchmarking Framework for AI models in Automotive Aerodynamics. CoRR Kaustubh Tangsali, Rishikesh Ranade, Mohammad Amin Nabian, Alexey Kamenev, Peter Sharpe, Neil Ashton, Ram Cherukuri, Sanjay Choudhry
2025	J	`jnl`	Accelerating Transient CFD through Machine Learning-Based Flow Initialization. CoRR Peter Sharpe, Rishikesh Ranade, Sanjay Choudhry
2025	J	`jnl`	Automotive Crash Dynamics Modeling Accelerated with Machine Learning. CoRR Mohammad Amin Nabian, Sudeep Chavare, Deepak Akhare, Rishikesh Ranade, Ram Cherukuri, Srinivas Tadepalli
2025	J	`jnl`	DoMINO: A Decomposable Multi-scale Iterative Neural Operator for Modeling Large Scale Engineering Simulations. CoRR Rishikesh Ranade, Mohammad Amin Nabian, Kaustubh Tangsali, Alexey Kamenev, Oliver Hennigh, Ram Cherukuri, Sanjay Choudhry
2025	J	`jnl`	GeoTransolver: Learning Physics on Irregular Domains Using Multi-scale Geometry Aware Physics Attention Transformer. CoRR Corey Adams, Rishikesh Ranade, Ram Cherukuri, Sanjay Choudhry
2024	J	`jnl`	A domain decomposition-based autoregressive deep learning model for unsteady and nonlinear partial differential equations. CoRR Sheel Nidhan, Haoliang Jiang, Lalit Ghule, Clancy Umphrey, Rishikesh Ranade, Jay Pathak
2024	J	`jnl`	Blending neural operators and relaxation methods in PDE numerical solvers. Nat. Mac. Intell. Enrui Zhang, Adar Kahana, Alena Kopanicáková, Eli Turkel, Rishikesh Ranade, Jay Pathak, George Em Karniadakis
2024	J	`jnl`	Large scale scattering using fast solvers based on neural operators. CoRR Zongren Zou, Adar Kahana, Enrui Zhang, Eli Turkel, Rishikesh Ranade, Jay Pathak, George Em Karniadakis
2024	—	`conf`	Parallel Per-tile Activation with Linear Superposition of Thermal Response for Solving Arbitrary Power Pattern in 3DIC Thermal Simulation. MLCAD Haiyang He, Norman Chang, Akhilesh Kumar, Jie Yang, Wenbo Xia, Lang Lin, Jessica Yen, Haoliang Jiang, Rishikesh Ranade
2024	J	`jnl`	Sampling-based Distributed Training with Message Passing Neural Network. CoRR Priyesh Kakka, Sheel Nidhan, Rishikesh Ranade, Jonathan F. MacArt
2023	J	`jnl`	Diffusion model based data generation for partial differential equations. CoRR Rucha Apte, Sheel Nidhan, Rishikesh Ranade, Jay Pathak
2023	A	`conf`	Invited Paper: Solving Fine-Grained Static 3DIC Thermal with ML Thermal Solver Enhanced with Decay Curve Characterization. ICCAD Haiyang He, Norman Chang, Jie Yang, Akhilesh Kumar, Wenbo Xia, Lang Lin, Rishikesh Ranade
2022	J	`jnl`	A Hybrid Iterative Numerical Transferable Solver (HINTS) for PDEs Based on Deep Operator Network and Relaxation Methods. CoRR Enrui Zhang, Adar Kahana, Eli Turkel, Rishikesh Ranade, Jay Pathak, George Em Karniadakis
2022	—	`conf`	A Thermal Machine Learning Solver For Chip Simulation. MLCAD Rishikesh Ranade, Haiyang He, Jay Pathak, Norman Chang, Akhilesh Kumar, Jimin Wen
2022	J	`jnl`	A Thermal Machine Learning Solver For Chip Simulation. CoRR Rishikesh Ranade, Haiyang He, Jay Pathak, Norman Chang, Akhilesh Kumar, Jimin Wen
2022	A*	`conf`	A composable machine-learning approach for steady-state simulations on high-resolution grids. NeurIPS Rishikesh Ranade, Chris Hill, Lalit Ghule, Jay Pathak
2022	J	`jnl`	A composable machine-learning approach for steady-state simulations on high-resolution grids. CoRR Rishikesh Ranade, Chris Hill, Lalit Ghule, Jay Pathak
2022	J	`jnl`	NLP Inspired Training Mechanics For Modeling Transient Dynamics. CoRR Lalit Ghule, Rishikesh Ranade, Jay Pathak
2022	J	`jnl`	On the Geometry Transferability of the Hybrid Iterative Numerical Solver for Differential Equations. CoRR Adar Kahana, Enrui Zhang, Somdatta Goswami, George Em Karniadakis, Rishikesh Ranade, Jay Pathak
2021	J	`jnl`	A Latent space solver for PDE generalization. CoRR Rishikesh Ranade, Chris Hill, Haiyang He, Amir Maleki, Jay Pathak
2021	J	`jnl`	A composable autoencoder-based iterative algorithm for accelerating numerical simulations. CoRR Rishikesh Ranade, Chris Hill, Haiyang He, Amir Maleki, Norman Chang, Jay Pathak
2021	J	`jnl`	ActivationNet: Representation learning to predict contact quality of interacting 3-D surfaces in engineering designs. CoRR Rishikesh Ranade, Jay Pathak
2021	J	`jnl`	Algorithmically-consistent deep learning frameworks for structural topology optimization. Eng. Appl. Artif. Intell. Jaydeep Rade, Aditya Balu, Ethan Herron, Jay Pathak, Rishikesh Ranade, Soumik Sarkar, Adarsh Krishnamurthy
2021	J	`jnl`	Generalized Joint Probability Density Function Formulation inTurbulent Combustion using DeepONet. CoRR Rishikesh Ranade, Kevin Gitushi, Tarek Echekki
2021	J	`jnl`	Geometry encoding for numerical simulations. CoRR Amir Maleki, Jan Heyse, Rishikesh Ranade, Haiyang He, Priya Kasimbeg, Jay Pathak
2021	J	`jnl`	One-shot learning for solution operators of partial differential equations. CoRR Lu Lu, Haiyang He, Priya Kasimbeg, Rishikesh Ranade, Jay Pathak
2020	J	`jnl`	An Efficient Machine-Learning Approach for PDF Tabulation in Turbulent Combustion Closure. CoRR Rishikesh Ranade, Genong Li, Shaoping Li, Tarek Echekki
2020	J	`jnl`	DiscretizationNet: A Machine-Learning based solver for Navier-Stokes Equations using Finite Volume Discretization. CoRR Rishikesh Ranade, Chris Hill, Jay Pathak
2020	J	`jnl`	Physics-consistent deep learning for structural topology optimization. CoRR Jaydeep Rade, Aditya Balu, Ethan Herron, Jay Pathak, Rishikesh Ranade, Soumik Sarkar, Adarsh Krishnamurthy