36. F. J. Solis and V. Jadhao, “Conduction in heterogeneous systems in the low-frequency regime: variational principles and boundary integral equations”, Eur. Phys. J. E 47, 60 (2024)
35. W. Li and V. Jadhao, “Comparing phenomenological models of shear thinning of alkanes at low and high Newtonian viscosities”, Tribology Letters, 72, 112, pages 1--9 (2024)
34. L. B. Nilsson, F. Sun, JCS Kadupitiya, and V. Jadhao, “Molecular dynamics simulations of deformable virus capsomers”, Viruses, 15, 1672 (2023) [Part of the "Physical Virology - Viruses at Multiple Levels of Complexity" special issue]
33. F. J. Solis and V. Jadhao, “Electrical properties of tissues from a microscopic model of confined electrolytes”, Physics in Medicine and Biology, 68, 105017 (2023)
32. W. Li, JCS Kadupitiya and V. Jadhao, “Rheological properties of small-molecular liquids at high shear strain rates”, Polymers, 15, 2166 (2023) [Part of the "Research on Polymer Simulation, Modeling and Computation" special issue]
31. F. Sun, JCS Kadupitiya, and V. Jadhao, “Probing accuracy-speedup tradeoff in machine learning surrogates for molecular dynamics simulations”, Journal of Chemical Theory and Computation (JCTC), 19, 4606-4618 (2023) [Part of the "Machine Learning for Molecular Simulation" special issue]
30. F. Sun, N. Brunk, and V. Jadhao, “Shape control of deformable charge-patterned nanoparticles”, Physical Review E (PRE), 107, 014502 (2023)
29. M. Uchida, N. Brunk, N. Hewagama, B. Lee, P. Prevelige Jr., V. Jadhao, and T. Douglas, “Multilayered ordered protein arrays self-assembled from a mixed population of virus-like particles”, ACS Nano, 16, 7662-7673 (2022)
28. JCS Kadupitiya, G. C. Fox, and V. Jadhao, “Solving Newton's equations of motion with large timesteps using recurrent neural networks based operators”, Machine Learning: Science and Technology (MLST), 3, 025002 (2022)
27. JCS Kadupitiya, V. Jadhao, and P. Sharma, “SciSpot: Scientific computing on temporally constrained cloud preemptible VMs”, IEEE Transactions on Parallel and Distributed Systems (TPDS), 33, 3575-3588 (2022)
26. [Position Paper] P. Sharma and V. Jadhao, “Molecular dynamics simulations on cloud computing and machine learning platforms”, Proceedings of the 2021 IEEE 14th International Conference on Cloud Computing (CLOUD), Volume: 1, pages 751-753, doi:10.1109/CLOUD53861.2021.00101 (2021)
25. JCS Kadupitiya and V. Jadhao, “Probing the rheological properties of liquids under conditions of elastohydrodynamic lubrication using simulations and machine learning”, Tribology Letters 69, 82 (2021) [Editors’ Selections]
24. N. E. Brunk, JCS Kadupitiya, and V. Jadhao, “Designing surface charge patterns for shape control of deformable nanoparticles”, Physical Review Letters (PRL) 125, 248001 (2020)
23. N. Anousheh, F. J. Solis, and V. Jadhao, “Ionic structure and decay length in highly concentrated confined electrolytes”, AIP Advances 10, 125312 (2020) [Featured Article], [Selected as Scilight]
22. V. Jadhao and JCS Kadupitiya, “Integrating machine learning with HPC-driven simulations for enhanced student learning”, Proceedings of the 2020 IEEE/ACM Workshop on Education for High-Performance Computing (EduHPC'20) in conjunction with the International Conference for High Performance Computing, Networking, Storage and Analysis (SC'20), DOI:10.1109/EduHPC51895.2020.00009
21. JCS Kadupitiya, V. Jadhao, and P. Sharma, “Modeling the temporally constrained preemptions of transient cloud VMs”, Proceedings of the 29th International Symposium on High-Performance Parallel and Distributed Computing (HPDC), 41-52 (2020)
20. JCS Kadupitiya, F. Sun, G. C. Fox, and V. Jadhao, “Machine learning surrogates for molecular dynamics simulations of soft materials”, Journal of Computational Science 42, 101107 (2020) [Virtual Special Issue of the Best Papers of the 2019 International Conference on Computational Science]
19. JCS Kadupitiya, G. C. Fox, and V. Jadhao, “Machine learning for parameter auto-tuning in molecular dynamics simulations: Efficient dynamics of ions near polarizable nanoparticles”, International
Journal of High Performance Computing Applications (IJHPCA) 34, 3, 357-374 (2020);
arxiv:1910.14620
18. N. E. Brunk and V. Jadhao, “Computational studies of shape control of charged deformable nanocontainers”, Journal of Materials Chemistry B 7, 6370 (2019) [Part of the 2019 Emerging Investigators themed issue] [Featured on the Issue's Back Cover]
17. V. Jadhao and M. O. Robbins, “Rheological properties of liquids under conditions of elastohydrodynamic lubrication”, Tribology Letters 67, 66 (2019) [2019 Editor's Choice]
16. N. E. Brunk, M. Uchida, B. Lee, M. Fukuto, L. Yang, T. Douglas, and V. Jadhao, “Linker-mediated assembly of virus-like particles into ordered arrays via electrostatic control”, ACS Applied Bio Materials 2, (5), 2192-2201 (2019)
15. G. Fox, J. A. Glazier, JCS Kadupitiya, V. Jadhao, M. Kim, J. Qiu, J. P. Sluka, E. Somogyi, M. Marathe, A. Adiga, J. Chen, O. Beckstein, and S. Jha,
"Learning everywhere: pervasive machine learning for effective high-performance computation",
IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), 422-429, Rio de Janeiro, Brazil (2019)
14. JCS Kadupitiya, G. C. Fox, and V. Jadhao, “Machine learning for performance enhancement of molecular dynamics simulations”, In: Rodrigues J. et al. (eds) Computational Science ICCS 2019. ICCS 2019. Lecture Notes in Computer Science, vol 11537, pp 116-130, Springer, Cham (2019) [Selected among the Best Papers of ICCS 2019] [Invited to the Virtual Special Issue of the Journal of Computational Science]
13. S. Marru and V. Jadhao, “Development of the nanoconfinement science gateway”, Gateways 2017, Ann Arbor, Michigan (2017)
12. V. Jadhao and M. O. Robbins, “Reply to Bair: Crossover to Arrhenius behavior at high viscosities in squalane”, Proceedings of the National Academy of Sciences (PNAS) 114, E8807 (2017)
11. V. Jadhao and M. O. Robbins, “Probing large viscosities in glass formers with nonequilibrium simulations”, Proceedings of the National Academy of Sciences (PNAS) 114, 7952 (2017)
10. Y. Jing, V. Jadhao, J.
Zwanikken, and M. Olvera de la Cruz, "Ionic structure in fluids confined by
planar dielectric interfaces”, Journal of Chemical Physics (JCP) 143, 194508 (2015)
9. V. Jadhao, Z. Yao, C. K. Thomas, and
M. Olvera de la Cruz, “Coulomb energy of
uniformly-charged spheroidal shell
systems”, Physical Review E (PRE) 91, 032305
(2015)8. V. Jadhao, C. K. Thomas, and M. Olvera de la Cruz, “Electrostatics-driven shape transitions in soft shells”, Proceedings of the National Academy of Sciences (PNAS) 111, 12673 (2014)
7. F. J. Solis, V. Jadhao, and M. Olvera de la Cruz, “Generating true minima in constrained variational formulations via modified Lagrange multipliers”, Physical Review E (PRE) 88, 053306 (2013)
6. V. Jadhao, F. J. Solis, and M. Olvera de la Cruz, “Free-energy functionals of the electrostatic potential for Poisson-Boltzmann theory”, Physical Review E (PRE) 88, 022305 (2013)
5. V. Jadhao, F. J. Solis, and M. Olvera de la Cruz, “A variational formulation of electrostatics in a medium with spatially varying dielectric permittivity”, Journal of Chemical Physics (JCP) 138, 054119 (2013)
4. V. Jadhao, F. J. Solis, and M. Olvera de la Cruz, “Simulation of charged systems in heterogeneous dielectric media via a true energy functional”, Physical Review Letters (PRL) 109, 223905 (2012)
3. V. Jadhao and N. Makri, “Iterative Monte Carlo path integral with optimal grids from whole-necklace sampling”, Journal of Chemical Physics (JCP) 133, 114105 (2010)
2. V. Jadhao and N. Makri, “Iterative Monte Carlo with bead-adapted sampling for complex-time correlation functions”, Journal of Chemical Physics (JCP) 132, 104110 (2010)
1. V. Jadhao and N. Makri, “Iterative Monte Carlo for quantum dynamics”, Journal of Chemical Physics (JCP) 129, 161102 (2008)
