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ORCIDMuralikrishnan Gopalakrishnan Meena
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2020 – today
- 2026
[j4]Amir Shehata
, Peter Groszkowski, Thomas J. Naughton, Muralikrishnan Gopalakrishnan Meena, Elaine Wong, Daniel Claudino, Rafael Ferreira da Silva, Thomas Beck:
Bridging paradigms: Designing for HPC-Quantum convergence. Future Gener. Comput. Syst. 174: 107980 (2026)- [j3]Chao Lu, Muralikrishnan Gopalakrishnan Meena, Kalyana C. Gottiparthi:
LuGo: An enhanced quantum phase estimation implementation. Future Gener. Comput. Syst. 178: 108270 (2026) - 2025
- [c4]Srikar Chundury, Amir Shehata, Seongmin Kim, Muralikrishnan Gopalakrishnan Meena, Chao Lu, Kalyana C. Gottiparthi, Eduardo Antonio Coello Pérez, Frank Mueller, In-Saeng Suh:
Scaling Hybrid Quantum-HPC Applications with the Quantum Framework. SC Workshops 2025: 1888-1897 - [i10]Yanfan Zhu, Isaac Lyngaas, Muralikrishnan Gopalakrishnan Meena, Mary Ellen Koran, Bradley A. Malin, Daniel Moyer, Shunxing Bao, Anuj J. Kapadia, Xiao Wang, Bennett A. Landman, Yuankai Huo:
Scale-up Unlearnable Examples Learning with High-Performance Computing. CoRR abs/2501.06080 (2025) - [i9]Amir Shehata, Peter Groszkowski, Thomas J. Naughton, Muralikrishnan Gopalakrishnan Meena, Elaine Wong, Daniel Claudino, Rafael Ferreira da Silva, Thomas Beck:
Building a Software Stack for Quantum-HPC Integration. CoRR abs/2503.01787 (2025) - [i8]Chao Lu, Muralikrishnan Gopalakrishnan Meena, Kalyana Chakravarthi Gottiparthi:
LuGo: an Enhanced Quantum Phase Estimation Implementation. CoRR abs/2503.15439 (2025) - [i7]Junqi Yin, Mijanur Palash, M. Paul Laiu, Muralikrishnan Gopalakrishnan Meena, John Gounley, Stephen M. de Bruyn Kops, Feiyi Wang, Ramanan Sankaran, Pei Zhang:
Pixel-Resolved Long-Context Learning for Turbulence at Exascale: Resolving Small-scale Eddies Toward the Viscous Limit. CoRR abs/2507.16697 (2025) - [i6]Wesley Brewer, Muralikrishnan Gopalakrishnan Meena, Matthias Maiterth, Aditya Kashi, Jong Youl Choi, Pei Zhang, Stephen Nichols, Riccardo Balin, Miles Couchman, Stephen M. de Bruyn Kops, P. K. Yeung, Daniel Dotson, Rohini Uma-Vaideswaran, Sarp Oral, Feiyi Wang:
Intelligent Sampling of Extreme-Scale Turbulence Datasets for Accurate and Efficient Spatiotemporal Model Training. CoRR abs/2508.03872 (2025) - [i5]Srikar Chundury, Amir Shehata, Seongmin Kim, Muralikrishnan Gopalakrishnan Meena, Chao Lu, Kalyana C. Gottiparthi, Eduardo Antonio Coello Pérez, Frank Mueller, In-Saeng Suh:
Scaling Hybrid Quantum-HPC Applications with the Quantum Framework. CoRR abs/2509.14470 (2025) - 2024
- [j2]Thomas Beck, Alessandro Baroni, Ryan S. Bennink, Gilles Buchs, Eduardo Antonio Coello Pérez, Markus Eisenbach, Rafael Ferreira da Silva, Muralikrishnan Gopalakrishnan Meena, Kalyana C. Gottiparthi, Peter Groszkowski, Travis S. Humble, Ryan Landfield, Ketan Maheshwari, Sarp Oral, Michael A. Sandoval, Amir Shehata, In-Saeng Suh, Christopher Zimmer:
Integrating quantum computing resources into scientific HPC ecosystems. Future Gener. Comput. Syst. 161: 11-25 (2024) - [j1]Muralikrishnan Gopalakrishnan Meena, Demetri Liousas, Andrew D. Simin, Aditya Kashi, Wesley H. Brewer, James J. Riley, Stephen M. de Bruyn Kops:
Machine-learned closure of URANS for stably stratified turbulence: connecting physical timescales & data hyperparameters of deep time-series models. Mach. Learn. Sci. Technol. 5(3): 45063 (2024) - [c3]Muralikrishnan Gopalakrishnan Meena, Yu Zhang, Weiwen Jiang, Youzuo Lin, Stefanie Günther, Xinfeng Gao:
Towards a Quantum Algorithm for the Incompressible Nonlinear Navier-Stokes Equations. QCE 2024: 662-668 - [i4]Muralikrishnan Gopalakrishnan Meena, Demetri Liousas, Andrew D. Simin, Aditya Kashi, Wesley Brewer, James J. Riley, Stephen M. de Bruyn Kops:
Machine-Learned Closure of URANS for Stably Stratified Turbulence: Connecting Physical Timescales & Data Hyperparameters of Deep Time-Series Models. CoRR abs/2404.16141 (2024) - [i3]Aditya Kashi, Arka Daw, Muralikrishnan Gopalakrishnan Meena, Hao Lu:
Learning the boundary-to-domain mapping using Lifting Product Fourier Neural Operators for partial differential equations. CoRR abs/2406.16740 (2024) - [i2]Thomas Beck, Alessandro Baroni, Ryan S. Bennink, Gilles Buchs, Eduardo Antonio Coello Pérez, Markus Eisenbach, Rafael Ferreira da Silva, Muralikrishnan Gopalakrishnan Meena, Kalyana C. Gottiparthi, Peter Groszkowski, Travis S. Humble, Ryan Landfield, Ketan Maheshwari, Sarp Oral, Michael A. Sandoval, Amir Shehata, In-Saeng Suh, Christopher Zimmer:
Integrating Quantum Computing Resources into Scientific HPC Ecosystems. CoRR abs/2408.16159 (2024) - 2023
- [c2]Muralikrishnan Gopalakrishnan Meena, Amirkoushyar Ziabari, Singanallur V. Venkatakrishnan, Isaac Lyngaas, Matthew R. Norman, Bálint Joó, Thomas L. Beck, Charles A. Bouman, Anuj J. Kapadia, Xiao Wang:
Physics guided machine learning for multi-material decomposition of tissues from dual-energy CT scans of simulated breast models with calcifications. High Performance Computing for Imaging 2023: 1-7 - [c1]Wesley Brewer, Daniel Martínez, Muralikrishnan Gopalakrishnan Meena, Aditya Kashi, Katarzyna Borowiec, Siyan Liu, Christopher Pilmaier, Greg W. Burgreen, Shanti Bhushan:
Entropy-driven Optimal Sub-sampling of Fluid Dynamics for Developing Machine-learned Surrogates. SC Workshops 2023: 73-80 - 2020
- [b1]Muralikrishnan Gopalakrishnan Meena:
Network community-based analysis of complex vortical flows: Laminar and turbulent flows. University of California, Los Angeles, USA, 2020
2010 – 2019
- 2019
- [i1]Zhe Bai, N. Benjamin Erichson, Muralikrishnan Gopalakrishnan Meena, Kunihiko Taira, Steven L. Brunton:
Randomized methods to characterize large-scale vortical flow network. CoRR abs/1909.00535 (2019)
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last updated on 2026-02-05 01:25 CET by the dblp team
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