General Lab Information

Matthew Carbone

Research Staff 3 Computational, Comput. Sci. Mach. Learning, Computational Science Initiative

Matthew Carbone

Brookhaven National Laboratory

Computational Science Initiative
Bldg. 725
P.O. Box 5000
Upton, NY 11973-5000

(631) 344-4827
mcarbone@bnl.gov

Pronouns: he, him, his

Expertise | Research | Education | Appointments | Publications | Awards | Certifications


Expertise

  • Theoretical condensed matter & spectroscopy
  • Machine learning & data analysis
  • High-performance computing
  • Software development (primarily Python & C++)

Research Activities

Matt works closely with researchers at BNL's light source and nanocenter, as well as other DOE national labs, and the Air Force Research Lab. His primary research interests are, in no particular order (with some highlighted works hyperlinked):

You can also find me on Google Scholar or my personal website. Select high-impact publications can be found below.

Education

  • Ph. D. in chemical physics; Columbia University, New York, NY (2021)
  • M. A. in chemical physics; Columbia University, New York, NY (2017)
  • B. S. magna cum laude in chemistry, with highest distinction; University of Rochester, Rochester, NY (2016)
  • B. A. magna cum laude in physics, with highest distinction; University of Rochester, Rochester, NY (2016)

Professional Appointments

  • Assistant Computational Scientist (RS3); Brookhaven National Laboratory (2021-present)

Selected Publications

  • Carbone MR, Kim HJ, Fernando C, et al (2024) Flexible formulation of value for experiment interpretation and design. Matter 7:685–696. https://doi.org/10.1016/j.matt.2023.11.012
  • Carbone MR (2022) When not to use machine learning: A perspective on potential and limitations. MRS Bulletin 47:968–974. https://doi.org/10.1557/s43577-022-00417-z
  • Torrisi SB, Carbone MR, Rohr BA, et al (2020) Random forest machine learning models for interpretable X-ray absorption near-edge structure spectrum-property relationships. npj Computational Materials 6:. https://doi.org/10.1038/s41524-020-00376-6
  • Carbone MR, Topsakal M, Lu D, Yoo S (2020) Machine-Learning X-Ray Absorption Spectra to Quantitative Accuracy. Physical Review Letters 124:. https://doi.org/10.1103/physrevlett.124.156401

Awards & Recognition

Certifications

Matthew Carbone

Brookhaven National Laboratory

Computational Science Initiative
Bldg. 725
P.O. Box 5000
Upton, NY 11973-5000

(631) 344-4827
mcarbone@bnl.gov

Matthew's Links