Chesapeake Machine Learning and Astronomy
An astrophysics and ML research group based out of Baltimore, Maryland.
The Chesapeake ML-Astro group is a research collaboration at Space Telescope Science Institute (STScI) and Johns Hopkins University (JHU). Our group maintains diverse scientific interests spanning galaxy clusters, large scale structures, and galaxy systems. We also focus on developing and applying novel machine learning methods to both simulated and observed data sets; check out our research page. Our weekly group meetings are on Fridays.
Current Group Members
- PI Michelle Ntampaka
- Associate Astronomer, STScI
- Associate Research Scientist, JHU
- PI John F Wu
- Assistant Astronomer, STScI
- Associate Research Scientist, JHU
- Ana Maria Delgado
- Postdoctoral Fellow, JHU
- John Soltis
- 6th year PhD candidate, JHU
- Mikaeel Yunus
- 3rd year PhD candidate, JHU
- Nikhil Garuda
- Final year undergraduate student, UArizona
Announcements
| 2024-12-06 | The paper "A Multi-Wavelength Technique for Estimating Galaxy Cluster Mass Accretion Rates" led by John Soltis (including M. Ntampaka and Ana Maria Delgado) is now posted to arXiv. |
| 2024-12-03 | Congratulations to Mikaeel Yunus for passing his Graduate Board Oral (PhD qualifying) exam! |
| 2024-11-19 | The paper "Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks" led by Nikhil Garuda (including John Wu) has been accepted to the NeurIPS ML4PS workshop and posted to arXiv. |
| 2024-10-09 | The paper "Conditional Diffusion Models for Generating Images of SDSS-Like Galaxies" led by Mikaeel Yunus (including John Wu) has been accepted to the NeurIPS ML4PS workshop. |
| 2024-05-08 | The paper "Self-Similar Mass Accretion History in Scale-Free Simulations" led by John Soltis is now posted to arXiv. |
| 2024-04-15 | Congratulations to John Wu for being named the 2024 Maryland Outstanding Young Scientist! |
| 2024-02-12 | The paper "How the Galaxy-Halo Connection Depends on Large-Scale Environment" led by John Wu is now posted to arXiv. |
| 2023-10-19 | The paper "Constructing Impactful Machine Learning Research for Astronomy: Best Practices for Researchers and Reviewers" co-led by Michelle Ntampaka can now be read on arXiv. |
| 2023-08-30 | Looking for a JHU research rotation project? Please reach out to the PIs of the group! |
| 2023-08-17 | Hello world! |