Research output per year
Research output per year
Personal profile
Research interests
My research interests span condensed matter physics, algorithm design, high-performance computing, and machine learning. My expertise is in the state-of-the-art classical and parallel Monte Carlo algorithms in statistical mechanics for the study of thermodynamics and phase transitions, first principles methods for the study of materials properties, as well as the applications of machine learning techniques to computer simulations and data analytics. I am an enthusiastic scientific software developer proficient in software engineering, performance analysis and optimization, with an emphasis on programming for heterogeneous system architectures consisting of CPUs and GPU accelerators.
Education/Academic qualification
Physics and philosophy, PHD, University of Georgia
Award Date: Jul 1 2012
Physics and philosophy, MS, Chinese University of Hong Kong
Award Date: Jul 1 2007
Physics and Mathematics, BS, Chinese University of Hong Kong
Award Date: May 1 2005
Fingerprint
Dive into the research topics where Ying Wai Li, is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
- 1 Similar Profiles
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Machine Learning Potentials with the Iterative Boltzmann Inversion: Training to Experiment
Matin, S., Allen, A. E. A., Smith, J., Lubbers, N., Jadrich, R. B., Messerly, R., Nebgen, B., Li, Y. W., Tretiak, S. & Barros, K., Feb 13 2024, In: Journal of Chemical Theory and Computation. 20, 3, p. 1274-1281 8 p.Research output: Contribution to journal › Article › peer-review
1 Scopus citations -
Gradient-based Wang-Landau Algorithm: A Novel Sampler for Output Distribution of Neural Networks over the Input Space
Liu, W., You, Y. Z., Li, Y. W. & Shang, J., 2023, In: Proceedings of Machine Learning Research. 202, p. 21825-21838 14 p.Research output: Contribution to journal › Conference article › peer-review
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HPC Application Performance Prediction with Machine Learning on New Architectures
Yokelson, D., Charest, M. R. J. & Li, Y. W., Jul 28 2023, PERMAVOST 2023 - Proceedings of the 2023 on Performance Engineering, Modelling, Analysis, and Visualization Strategy. Unknown Publisher, p. 1-8 8 p. (PERMAVOST 2023 - Proceedings of the 2023 on Performance Engineering, Modelling, Analysis, and Visualization Strategy).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
Open Access -
Synergy of semiempirical models and machine learning in computational chemistry
Fedik, N., Nebgen, B., Lubbers, N., Barros, K., Kulichenko, M., Li, Y. W., Zubatyuk, R., Messerly, R., Isayev, O. & Tretiak, S., Sep 21 2023, In: Journal of Chemical Physics. 159, 11, 110901.Research output: Contribution to journal › Article › peer-review
Open Access2 Scopus citations -
Uncertainty-driven dynamics for active learning of interatomic potentials
Kulichenko, M., Barros, K., Lubbers, N., Li, Y. W., Messerly, R., Tretiak, S., Smith, J. S. & Nebgen, B., Mar 2023, In: Nature Computational Science. 3, 3, p. 230-239 10 p.Research output: Contribution to journal › Article › peer-review
Open Access18 Scopus citations
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Accelerated Dynamics Across Computational and Physical Scales
Li, Y. W., Lin, Y. T., Perez, D., DeGennaro, A., Lin, K., Po, G., Trinkle, D., Urban, N., Bagchi, S., Julian, N. H., Mathew, N., Myhill, L. A., Pandey, A., Pilania, G., Talapatra, A. A., Tian, Y., Wilson, M. S. & Uberuaga, B. P.
10/1/21 → 09/30/24
Project: Other
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Accelerated Monte Carlo Algorithms without Detailed Balance
Li, Y. W., Acharya, S. R., Casiano-Diaz, E., Cooper, V. R., Eisenbach, M., Farris, A. C. K., Ferreira, T., Liu, W., Maestro, A. D., Parker, D. S., Pitike, K. C., Sattar, N. S., Sefat, A. S., Shang, J., Vogel, T., Xu, L., Yuk, S. F., Casiano-Diaz, E. & Wilson, M. S.
04/5/21 → 09/30/23
Project: Other
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Data Driven Modeling of Non-Equilibrium Dynamics in Chemical and Materials Systems
Habib, A., Nebgen, B. T., Loomis, E. N., Boldyrev, A., Das, P., Isayev, O., Lee, H. J., Peralta, P., Barros, K. M., Kozlowski, P. M., Li, W., Lubbers, N. E., Messerly, R. A., Montgomery, D., Murphy, T. J., Smith, J. S., Zhou, G., Bhattarai, M., Fedik, N., Malone, W. F., Kim, K., Li, Y. W., Tretiak, S., Lee, B., Schuman, A., Zuo, X., Williams, D. J. & LaNasa, J. A.
10/1/20 → 09/30/23
Project: Other
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Enabling Predictive Scale-Bridging Simulations through Active Learning
Viswanathan, H. S., Bennett, K., Junghans, C., Kang, Q., Mehana, M. Z. S., Germann, T. C., Ba?ant, Z. P., Murillo, M., Nasrabadi, H., Wagner, A., Agarwal, A., Barros, K. M., Diaw, A., Haack, J. R., Karra, S., Lubbers, N. E., McKerns, M., Pavel, R. S., Rosenberger, D. G., Sagert, I., Sauppe, J. P., Wang, K., Chen, Y., Karim, M. R., Son, S., Livescu, D. & Li, Y. W.
10/1/18 → 09/30/21
Project: Other