I am an Associate Professor in the Physics Department at the CUNY NYC College of Technology.

I am also an associate member of the recently formed Center for Computational Astrophysics at the Flatiron Institute, a visiting research scientist in the Astrophysics Department at the American Museum of Natural History, a member of the CUNY Astro group, and a Harlow Shapley Visiting Lecturer for the American Astronomical Society.

In 2017, I was a recipient of the Feliks Gross Award for outstanding research, CUNY’s highest award for assistant professors.

The picture on the left is from the one time in my life I’ve been to a telescope.

Dr. Viviana Acquaviva


My research is at the interface between Astronomy and Data Science. I am especially interested in using statistical techniques and machine learning methods to explore large galaxy catalogs and learn something about the evolution of the Universe.

Understanding the physical properties of galaxies, such as stellar mass, star formation histories, dust content, redshift, and metallicity, through Spectral Energy Distribution fitting has been a major focus of my research for several years. I wrote a Markov Chain Monte Carlo code, GalMC, for SED fitting, which you can try out here.

Don’t have data yet? If you are planning a survey and would like to know how well you can constrain the physical properties of galaxies with your observations (or want to try out a few different ones and see which one works best), you are welcome to use GalFish.

For some of my most recent work on the correlation between photometric properties and gas-phase metallicity you can check out this  paper.

I am a member of the Hobby-Eberly Telescope Dark Energy eXperiment (HETDEX) collaboration, which aims to use Lyman Alpha Emitting galaxies to study the behavior of Dark Energy at early times, when we don’t expect to see much of it (but then we weren’t expecting dark energy at all, so I am hopeful for surprises).

I enjoy working with students and have mentored several undergraduate and graduate students, inside and outside of CUNY. I have a few openings for student projects, including within the CUNY funding system (think Emerging Scholars, Research Scholars, LSAMP). If you are interested in working with me, I am happy to discuss options - please know that you need to have a strong interest in programming and in statistics and/or machine learning, and a working knowledge of Python (or the desire to learn it quickly). Knowledge of Astronomy is helpful but not required - but if you don’t enjoy coding I don’t think I’d be a great match.

You can check out my Google Scholar profile here and, if you are interested for some mysterious reason, download my CV here.

Student projects