Professor Daniel Eisenstein studies cosmology and extragalactic astronomy with a mix of theoretical and observational methods. His dominant focus over the last decade has been on the development of the baryon acoustic oscillation method to measure the cosmic distance scale and study dark energy. Dr. Eisenstein received his Ph.D. from Harvard University in 1996 and then held postdoctoral positions at the Institute for Advanced Study and the University of Chicago. He was on the University of Arizona astronomy faculty for 9 years before moving to his current position as a professor of astronomy at Harvard University in 2010. He has been active in the Sloan Digital Sky Survey since 1998 and served as the Director of SDSS-III from 2007 to 2015. He is a member of the Dark Energy Spectroscopic Instrument collaboration, serving as co-Spokesperson from 2014 to 2020. He is a member of the JWST Near-Infrared Camera instrument team, the SDSS-IV consortium, and the Euclid consortium. He also serves on the Board of Directors of the Giant Magellan Telescope Observatory. In 2012, he served as chair of the National Science Foundation Astronomy Portfolio Review committee, and currently he is serving as chair of the Cosmology Science Panel of the Astro2020 Decadal Survey. He has been a member of numerous other scientific collaborations and national committees. In 2014, he received the Shaw Prize in Astronomy and was elected to the U.S. National Academy of Sciences. He was named as a Simons Investigator in 2016. Starting in 2020, he serves as Chair of the Harvard University Department of Astronomy.
Professor Eisenstein's work currently focuses on several themes. 1) He is active in the development and analysis of large redshift surveys. At present, this attention is largely on DESI, an ambitious new instrument that will begin its survey in 2020. His students are working on DESI target selection, survey design, and mock catalogs. He also is a member of the SDSS-IV and Euclid consortia.
2) He pursues the development of new statistical methods for the interpretation of large-scale structure. Recent examples are development of practical methods for the three-point correlation function, development of fast estimation of covariance matrices for two-point clustering, application of neural nets to inference from large-scale structure, and studies of halo occupations and their impact on large-scale clustering.
3) He is actively developing the novel Abacus code for high-performance cosmological N-body simulations. His group is using Abacus at the Oak Ridge Leadership Computing Facility GPU-based supercomputer Summit to generate the AbacusSummit suite of high-accuracy large-volume cosmological simulations, designed to support the testing of cosmological statistical inferences in DESI and other surveys.
4) As part of the JWST Near-Infrared Camera team, he is preparing for the observation, reduction, and analysis of the JADES program, a very deep imaging and spectroscopic view of high-redshift galaxy evolution in the GOODS-S and GOODS-N fields.
5) He participates in the planning for next-generation telescopes and facilities, notably the Giant Magellan Telescope.