Federica Bianco
Associate Professor University of Delaware
Media
Social
Biography
She works on data-driven solutions to problems that span from the nature of explosions in the sky to sustainability on earth. She is an expert in time-domain and multi-messenger astronomy and in the application of Machine Learning and Artificial Intelligence across domains. She is passionate about demystifying AI and empowering scientist, policy makers, and anyone who would listen to understand how AI works, how it can harm us, and how it can help us.
She served as Deputy Project Scientist for Rubin Observatory Construction, the largest ground-based optical astrophysical facility ever built, which in 2026 will begin the Legacy Survey of Space and Time: a 10-year survey of the southern sky that will deliver the largest ever dataset of astrophysical objects, from asteroids and nearby stars and planets to the farthest explosions in the Universe.
She is TED 2019 fellow.
She is a passionate communicator: contact her regarding public speaking engagements.
When not sciencing, she likes fighting.
Areas of Expertise
Media Appearances
Vera Rubin Scientists Reveal Telescope’s First Images
The New York Times online
2025-06-25
When asked about what surprises might be hiding in the data, Federica Bianco, Rubin’s deputy project scientist, said that these were unknown unknowns. “It’s really an adventurous horizon,” she said.
Two of the first images show snippets of the Virgo Cluster, a group of galaxies some 55 million light-years away.
Opening a new window into the universe
UDaily online
2025-06-18
Several University of Delaware faculty members — including astrophysicist Federica Bianco, astronomer John Gizis, data scientist David Hong and UD affiliate Beth Willman, CEO of the LSST Discovery Alliance — are in leadership and supporting roles as preparation moves steadily toward the late-2025 start of the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). LSST has been described by the National Science Foundation (NSF) as “the most comprehensive data-gathering mission in the history of astronomy.”
Astrophysicist explains how boxing makes her a better scientist
WHYY online
2019-06-06
Federica Bianco says colleagues from both careers are surprised at her alternate identity, but each role enhances the other.
Federica Bianco Is the World’s Most Badass Astrophysicist
The Daily Beast online
2017-05-21
The first time I met Federica Bianco, she was wearing a “Nasty Woman” t-shirt and punched me in the face, knocking out my right contact lens.
UFOs to UAPs
UDaily online
2023-09-15
Capture good, useful data and University of Delaware astrophysicist Federica Bianco will dig deep to help analyze it. It’s what she does with great expertise as a scientist and associate professor of physics and astronomy and it’s a big reason why she was among the 16 people selected to serve on a NASA-appointed panel studying Unidentified Anomalous Phenomena (UAP).
Articles
Every Data Point Counts: Stellar Flares as a Case Study of Atmosphere-aided Studies of Transients in the LSST Era
The Astrophysical Journal Supplement Series2024-06-10
Due to their short timescale, stellar flares are a challenging target for the most modern synoptic sky surveys. The upcoming Vera C. Rubin Legacy Survey of Space and Time (LSST), a project designed to collect more data than any precursor survey, is unlikely to detect flares with more than one data point in its main survey.
Light curve classification with DistClassiPy: A new distance-based classifier
Astronomy and Computing2024-07-01
The rise of synoptic sky surveys has ushered in an era of big data in time-domain astronomy, making data science and machine learning essential tools for studying celestial objects. While tree-based models (e.g. Random Forests) and deep learning models dominate the field, we explore the use of different distance metrics to aid in the classification of astrophysical objects.
Multifilter UV to Near-infrared Data-driven Light-curve Templates for Stripped-envelope Supernovae
The Astrophysical Journal Supplement Series2024-11-29
While the spectroscopic classification scheme for stripped-envelope supernovae (SESNe) is clear, and we know that they originate from massive stars that lost some or all of their envelopes of hydrogen and helium, the photometric evolution of classes within this family is not fully characterized.
High-cadence stellar variability studies of RR Lyrae stars with DECam: New multiband templates
Astronomy & Astrophysics2024-11-22
We present the most extensive set to date of high-quality RR Lyrae light curve templates in the ɡriz bands, based on time-series observations of the Dark Energy Camera Plane Survey (DECaPS) East field, located in the Galactic bulge at coordinates (RA, Dec)(J2000) = (18:03:34, −29:32:02), obtained with the Dark Energy Camera (DECam) on the 4-m Blanco telescope at the Cerro Tololo Inter-American Observatory (CTIO).
Autoencoder Reconstruction of Cosmological Microlensing Magnification Maps
The Astrophysical Journal2025-02-03
Enhanced modeling of microlensing variations in light curves of strongly lensed quasars improves measurements of cosmological time delays, the Hubble Constant, and quasar structure. Traditional methods for modeling extragalactic microlensing rely on computationally expensive magnification map generation.
Multi-messenger gravitational lensing
Philosophical Transactions A2025-05-01
We introduce the rapidly emerging field of multi-messenger gravitational lensing—the discovery and science of gravitationally lensed phenomena in the distant universe through the combination of multiple messengers.
MO-SAM: Testing the reliability and limits of mine feature delineation using Segment Anything Model to democratize mine observation and research
PLOS Sustainability and Transformation2025-07-15
The purpose of this paper is to leverage the growth of AI-enabled tools to support the democratization of mine observation (MO) research. Mining is essential to meet projected demand for renewable energy technologies crucial to global climate mitigation objectives, but all mining activities pose local and regional challenges to environmental sustainability.
Research Grants
The Effects of Subpopulations and Policy Change on COVID19 Hospital Demand Models
National Institutes of Health
Co-Investigator, 2020
Characterizing the Global Illicit Trade in Energy-Critical Materials using Machine Learning, Remote Sensing, and Qualitative Research
National Science Foundation Award Number: 2039857.
Co-Principal Investigator, 2021
Detecting and studying light echoes in the era of Rubin and Artificial Intelligence
National Science Foundation Award Number: 2108841.
Principal Investigator, 2021
Delaware and Mid-Atlantic Data Science Corps
National Science Foundation
Principal Investigator, 2021
Every Datapoint Counts: Atmosphere-aided Flare Studies in the Rubin era
National Science Foundation Award Number: 2308016
Principal Investigator, 2023
Accomplishments
Arts and Sciences Outstanding Advocacy Award, University of Delaware
2025
NASA Silver Group Achievement Award, Conferred “for your exceptional work as part of the NASA Unidentified Anomalous Phenomena Independent Study Team (UAPIST)”
2024
Ted Fellow
2019
Smithsonian Predoctoral Fellowship
September 2005-2009
James Arthur Postdoctoral Fellowship
September 2012-2015
Education
Alma Mater Studiorum – Università di Bologna
B.S.
Astronomy
2003
University of Pennsylvania
M.S.
Physics
2007
University of Pennsylvania
Ph.D.
Physics
2010
