I graduated from Virginia Tech with a B.S. in Physics and Mathematics. I am currently a PhD student in the department of physics and am interested in improving the accuracy and efficiency of DFT. Specifically, I am interested in strongly correlated systems, and in general, utilizing machine learning approaches to problems in DFT.
Google Scholar Publications
| [226] | The difference between molecules and materials: Reassessing the role of exact conditions in density functional theory , The Journal of Chemical Physics 159, 214113 (2023). [supplementary information] |
| [224] | Seven Useful Questions in Density Functional Theory , Letters in Mathematical Physics 113, 42 (2023). |
| [222] | Machine learning and density functional theory , Nature Reviews Physics (2022). |
| [219] | Conditional probability density functional theory , Phys. Rev. B 105, 245138 (2022). |
| [215] | How Well Does Kohn–Sham Regularizer Work for Weakly Correlated Systems? , The Journal of Physical Chemistry Letters 13, 2540-2547 (2022). |
| [206] | Kohn-Sham Equations as Regularizer: Building Prior Knowledge into Machine-Learned Physics , Phys. Rev. Lett. 126, 036401 (2021). |
| [202] | Bypassing the Energy Functional in Density Functional Theory: Direct Calculation of Electronic Energies from Conditional Probability Densities , Phys. Rev. Lett. 125, 266401 (2020). |
