I am an assistant professor of astronomy & astrophysics at The Pennsylvania State University. My research interests focus on understanding the processes of galaxy formation through combining modern, deep galaxy surveys with telescopes like JWST with statistics and machine learning.

In particular, I specialize in interpreting galaxy photometry and spectra using complex models for the stars, gas and dust living within them, in building and exploring analytical and empirical models of the evolving galaxy population as a whole, and in using astrostatistics and machine learning to better understand the universe. I've harnessed millions of hours of supercomputer time running specialized code to build a more complete picture of how galaxies form and evolve. I've worked on a wide range of science ranging from understanding the stellar origins of kilonova explosions to developing new methods for wide-field infrared galaxy surveys. I am very lucky to have been afforded the privilege of asking the big questions of the Universe!

Some of my current active projects include the Prime Focus Spectrograph galaxy survey , searching for first-light galaxies in the deep JWST survey UNCOVER , analyzing high signal-to-noise spectroscopy of galaxies at 'cosmic noon' in the Blue Jay survey with JWST, and developing software to analyze galaxy spectra with JWST. I'm also an active member of the Institute for Gravitation and the Cosmos and the Institute for Computational and Data Sciences at Penn State.

Below is recent press coverage of research done in my group:

My Research Group

Current Group Members

My current (August 2023) group members are below:

Bingjie Wang, postdoctoral researcher, measuring the properties of high-redshift galaxies using JWST.

Yijia Li, 6th year graduate student, Bayesian hierarchical modeling and neural net-powered emission line modeling.

Elijah Mathews, 6th year graduate student, high-dimensional fitting and neural net emulators.

Kanishk Pandey, 1st year graduate student, exploring the galaxy-to-galaxy variation in properties of mysterious thermally-pulsating AGB stars.

Emilie Burnham Faith, 1st year graduate student, examining distant galaxy populations to understand the short-term timescales of fluctuations in their star formation rates.

Junyu Zhang, Penn State undergraduate, identifying rejuvenating galaxies using spectroscopy.

Nathan Cristello, Penn State undergraduate, building large catalogs of galaxy properties using ultra-fast simulation-based inference.

Former Group Members

Group members who have graduated and gone on to other positions.

Will Bowman (current postdoc at Yale University)


Simple Models of Galaxy Assembly

I started my Ph.D in 2010 at Yale University with Professor Pieter van Dokkum. This was an exciting time to be studying galaxy evolution. We were in the middle of the first wide, deep, and unbiased (mass-selected) surveys of galaxy evolution at "cosmic noon", spear-headed by ambitious programs with the Hubble Space Telescope such as 3D-HST and CANDELS. As a result, astronomers had now surveyed the vast majority of the galaxy population over the majority of cosmic time for the very first time. My advisor and I thought that it was now the ideal time to "put it all together" and write down how galaxies grew up in a simple analytical model. This was the beginning of my thesis.

2013: Processes affecting galaxy evolution at a constant number density

However, after constructing and testing our analytical framework, we found a serious problem with this plan. Applying our model to two independent measurements of galaxy mass growth (the current rate of star formation and the current mass locked up in stars) resulted in galaxy growth rates which were systematically offset by a factor of two. This was a big problem. To put it in persepctive, our model suggested that a typical ancestor of the Milky Way would grow by a factor of 4-16 from z~2, a confidence interval so large as to be almost useless!

2015: Even after changing the SFR(M), observed masses and SFRs disagreed

A New Method to Measure Galaxy Properties

The problem lay in the models we used to convert galaxy observations into galaxy properties. While these models had had many successes over many years, they were not quite precise enough to answer the questions we needed to answer. We identified three specific problems:

  • The models did not include enough of the relevant physics, e.g. emission from black holes or nebulae.
  • The assumptions built into them were not physically self-consistent.
  • The models needed to use more clever statistics to translate the weak observational constraints into very broad parameter estimates
Over the end of my Ph.D and during my postdoctoral research, I worked closely with stellar populations experts Professor Charlie Conroy and Dr. Ben Johnson at the Center for Astrophysics | Harvard & Smithsonian to develop a new model addressing these problems: Prospector-α, built within the Prospector Bayesian inference framework.

2017: Here Prospector fits our new galaxy SED model Prospector-α to photometry

A New Cosmic Consensus

We applied this new Prospector-α model to a mass-complete sample of 58,461 galaxies across 0.5 < z < 2.5 from the 3D-HST survey. These new inferences lowered the observed cosmic star formation rate density by ∼0.2 dex and increase the observed stellar mass growth by ∼0.1 dex, finally bringing these two measurements into agreement and implying an older, more quiescent Universe than found in previous work.

2019: A new consensus in the older, more quiescent Universe inferred by Prospector-α


In additional to my professional mentoring, I believe that knowing more about science and the scientific process improves the lives of everyone (and -- talking to folks about it is lots of fun!).

Flipped Science Fair

I host an annual reverse science fair, where professional researchers present their research to students from local elementary and middle schools. The students serve as “judges” and announce a winner at the end of the event. This encourages and develops outreach skills among researchers while simultaneously engaging the middle school students in a critical form of active learning.

Visiting URJ 6 Points Sci-Tech Academy

Giving talks to middle schoolers at science summer camp about my thesis research, and talking to them in their classrooms!


My office is Davey Laboratory 515. You can reach me electronically at (firstname).(lastname)