Dr. Melton specializes in transiting exoplanets both in identifying new candidates from large space-based surveys such as the Transiting Exoplanet Satellite Survey (TESS) and Kepler as well as ground-based follow-up utilizing both the Oakley Observatory located on ÃÛÌÒÓ°Ïñ’s campus and the remote Oakley Southern Sky Observatory located in New South Wales, Australia. She enjoys working with independent student researchers and the ÃÛÌÒÓ°Ïñ Astronomical Society to fully utilize the telescopes and resources on campus for both astronomical research, outreach and enjoyment.
Academic Degrees
- PhD, Pennsylvania State University, Astronomy and Astrophysics, 2022
- MS, Pennsylvania State University, Astronomy and Astrophysics, 2020
- BS, ÃÛÌÒÓ°Ïñ, Physics with minor in Astronomy, 2015
- BS, ÃÛÌÒÓ°Ïñ, Mathematics, 2015
Publications & Presentations
- Melton, E., Pellegrino, A., Feigelson E., "DIAmante TESS AutoRegressive Planet Search (DTARPS) Results from the DTARPS-S Catalog", TESS Science Conference III, Cambridge, Massachusetts, 2024
- Melton, E., Pellegrino, A., Feigelson E., "The AutoRegressive Planet Search Method Applied to TESS Year 1 and 2", Exoplanets V, Leiden, The Netherlands, 2024
- Melton, E., Feigelson, E., Montalto, M. et al. 2024, AJ, DIAmante Tess AutoRegressive Planet Search (DTARPS) I. Analysis of 0.9 Million Light Curves, 167, 5, 202, doi:10.3847/1538-3881/ad29f0
- Melton, E., Feigelson, E., Montalto, M. et al. 2024, AJ, DIAmante Tess AutoRegressive Planet Search (DTARPS) II. Hundreds of New TESS Candidate Exoplanets, 167, 5, 203, doi:10.3847/1538-3881/ad29f1
- Melton, E., Feigelson, E., Montalto, M. et al. 2024, AJ, DIAmante Tess AutoRegressive Planet Search (DTARPS) III. Understanding the DTARPS-S Candidate Transiting Planet Catalogs, 168, 6, 271, doi:10.3847/1538-3881/ad8355
- Melton, E, "New Exoplanet Candidates from DIAmante TESS FFIs", TESS Science Team Meeting, 2022
- Melton, E. "Applying ARIMA to Irregular Time Series", Statistical Challenges in Modern Astronomy VII, 2021
- Melton, E 2020, AJ, A Random Forest Approach to Identifying Young Stellar Object Candidates in the Lupus Star-forming Region, 159, 5, 200, doi: 10.3847/1538-3881/ab72ac
Research Experiences
- Ground Based-Exoplanet Follow-up
- Machine Learning Classification
- Astrostatistics
Teaching Interests
- Astronomy and Astrophysics
- Introductory Physics
- Machine Learning
- Applied Data Science