A list of selected publications and papers.
Publications
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William S. Moses, Sri Hari Krishna Narayanan, Ludger Paehler, Valentin Churavy, Michel Schanen, Jan Hückelheim, Johannes Doerfert, and Paul Hovland. 2022. Scalable automatic differentiation of multiple parallel paradigms through compiler augmentation. In Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis (SC ’22). IEEE Press, Article 60, 1–18.
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Tao B. Schardl, I-Ting Angelina Lee. 2023. OpenCilk: A Modular and Extensible Software Infrastructure for Fast Task-Parallel Code. In Proceedings of the 28th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming (PPoPP ’23). 189–203.
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Sakurada, T., Cho, Y., Paritmongkol, W., Wan, R., Su, A., Lee, W. S., Shcherbakov-Wu, W., Müller, P., Kulik, H. J., & Tisdale, W. A. (2023). 1D hybrid semiconductor silver 2,6-difluorophenylselenolate. Journal of the American Chemical Society, 145, 5183-5190.
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Lee, W.-S., Cho, Y., Powers, E. R., Paritmongkol, W., Sakurada, T., Kulik, H. J., & Tisdale, W. A. (2022). Light Emission in 2D Silver Phenylchalcogenolates. ACS Nano, 16, 20318-20328.
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Duan, C., Nandy, A., Meyer, R., Arunachalam, N., & Kulik, H. J. (2023). A Transferable Recommender Approach for Selecting the Best Density Functional Approximations in Chemical Discovery. Nature Computational Science, 3, 38-47.
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Duan, C., Nandy, A., Adamji, H., Roman-Leshkov, Y., & Kulik, H. J. (2022). Machine learning models predict calculation outcomes with the transferability necessary for computational catalysis. Journal of Chemical Theory and Computation, 18, 4282-4292.
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Cytter, Y., Nandy, A., Bajaj, A., & Kulik, H. J. (2022). Ligand Additivity and Divergent Trends in Two Types of Delocalization Errors from Approximate Density Functional Theory. The Journal of Physical Chemistry Letters, 13, 4549-4555.
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Cho, Y., Nandy, A., Duan, C., & Kulik, H. J. (2023). DFT-based Multireference Diagnostics in the Solid State: Application to Metal–organic Frameworks. Journal of Chemical Theory and Computation, 19, 190-197.
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Bajaj, A., & Kulik, H. J. (2022). Eliminating Delocalization Error to Improve Heterogeneous Catalysis Predictions with Molecular DFT+U. Journal of Chemical Theory and Computation, 18, 1142-1155.
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Ariyarathna, I. R., Duan, C., & Kulik, H. J. (2022). Understanding the chemical bonding of ground and excited states of HfO and HfB with correlated wavefunction theory and density functional approximations. Journal of Chemical Physics, 156, 184113.
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Ariyarathna, I. R., Cho, Y., Duan, C., & Kulik, H. J. (2023). Gas-Phase and Solid-State Electronic Structure Analysis and DFT Benchmarking of HfCO. Physical Chemistry Chemical Physics, 25, 26632–26639.
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Terrana, S., Nguyen, N. C., & Peraire, J. (2020). GPU-accelerated Large Eddy Simulation of Hypersonic Flows. AIAA Scitech 2020 Forum, AIAA-2020-1062.
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Nguyen, N. C., Terrana, S., & Peraire, J. (2022). Large-Eddy Simulation of Transonic Buffet Using Matrix-Free Discontinuous Galerkin Method. AIAA Journal, 60(5), 3060–3077.
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Van Heyningen, R. L., Nguyen, C., & Peraire, J. (2023). Shock capturing for discontinuous Galerkin approximations of hypersonic non-equilibrium flow. AIAA SCITECH 2023 Forum, AIAA-2023-0853.
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Nguyen, C., Terrana, S., & Peraire, J. (2023). Implicit Large eddy simulation of hypersonic boundary-layer transition for a flared cone. AIAA SCITECH 2023 Forum, AIAA 2023-0659.
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Nguyen, N. C., & Peraire, J. (2023). Efficient and accurate nonlinear model reduction via first-order empirical interpolation. Journal of Computational Physics, 112512.
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Nguyen, N. C., Vila-Pérez, J., & Peraire, J. (2023). An adaptive viscosity regularization approach for the numerical solution of conservation laws: Application to finite element methods. Journal of Computational Physics, 112507.
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Nguyen, N. C., & Rohskopf, A. (2023). Proper orthogonal descriptors for efficient and accurate interatomic potentials. Journal of Computational Physics, 480, 112030.
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Nguyen, N. C. (2023). Fast proper orthogonal descriptors for many-body interatomic potentials. Physical Review B, 107(14), 144103.
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Rohskopf, A., Goff, J., Sema, D., Gordiz, K., Nguyen, N. C., Henry, A., Thompson, A. P., & Wood, M. A. (2023). Exploring model complexity in machine learned potentials for simulated properties. Journal of Materials Research.
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Vila-Pérez, J., Van Heyningen, R. L., Nguyen, N.-C., & Peraire, J. (2022). Exasim: Generating discontinuous Galerkin codes for numerical solutions of partial differential equations on graphics processors. SoftwareX, 20, 101212.
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Nicolas G. Hadjiconstantinou and Mathew M. Swisher, “On the equivalence of nonequilibrium and equilibrium measurements of slip in molecular dynamics simulations,” Physical Review Fluids, 7, 114203, 2022
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Nandy, A., Duan, C., Taylor, M.G., Liu, F., Steeves, A.H., & Kulik, H.J. (2021). Computational Discovery of Transition-metal Complexes: From High-throughput Screening to Machine Learning. Chemical Reviews, 121, 9927–10000.
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William Moses, Valentin Churavy. “Instead of Rewriting Foreign Code for Machine Learning, Automatically Synthesize Fast Gradients.” In Advances in Neural Information Processing Systems 33 (NeurIPS 2020).