Greis Julieth Kim Reyes

Dr. Greis Julieth Kim Reyes serves as Assistant Professor of Physics in the Department of Physics and Astronomy at SUNY New Paltz, where she conducts computational research on semiconductor materials and defects. Her work bridges theoretical physics and practical materials design for energy applications.

Her educational journey includes a Ph.D. in Physics from University at Buffalo (2024), Master's in Physics from Universidad Nacional de Colombia (2014), and Bachelor's in Physics-Education from Universidad Distrital Francisco José de Caldas (2010). This international background informs her interdisciplinary approach to materials science.

Dr. Reyes specializes in computational exploration of intermediate band semiconductors, defect engineering, and magnetic materials using density functional theory (DFT) and machine learning. Her research reveals how atomic-scale defects create novel electronic properties, particularly in 2D materials like C₃N/C₃B bilayers and perovskite oxides. She employs iterative Kohn-Sham methods to simulate electronic behavior and optical responses, with recent work focusing on excitonic effects for solar energy applications.

Analysis of her 15 most recent publications shows consistent emphasis on computational discovery of materials with tailored optical and electronic properties. Key trends include defect-enabled photocatalysis, interlayer exciton engineering in van der Waals heterostructures, and Jahn-Teller effects in doped semiconductors - all targeting next-generation energy technologies.

Her scholarly recognition includes:

• Bahethi Scholarship (SUNY Buffalo, 2022)
• Silvestro Scholarship (SUNY Buffalo, 2022)
• Marshall Plan Foundation grant (Johannes Keppler Universität, 2018)

As an educator, Dr. Reyes develops interactive quantum mechanics curricula using Mathematica simulations, as evidenced by her GitHub repository. She teaches General Physics and Quantum Physics courses while integrating computational tools to build student intuition for quantum materials. Though specific research students aren't listed, her teaching philosophy emphasizes critical thinking through problem-solving sessions and real-world applications.

Her computational laboratory work focuses on first-principles simulations of materials, with active development of educational resources for quantum mechanics instruction. Current projects explore machine learning pipelines for materials discovery and defect-property relationships in emerging semiconductor systems.