Catalyst Postdoc Alliance Leadership Mini-Grant Projects

Margherita Grespan

From Active Learning to Active Collaboration and Dissemination 

I am a postdoctoral researcher at the University of Oxford, working with Dr. Aprajita Verma and supported by the Bekker NAWA fellowship. My research focuses on the discovery of rare astrophysical objects, particularly strong gravitational lenses, using AI techniques. A central component of my work is the application of active learning to static anomaly detection, enabling the discovery of a broader class of scientifically valuable systems, including strong gravitational lenses, galaxy mergers, and objects with unusual morphologies. I also serve as co-lead of the Static Strong Lens Challenge Task Force within the Strong Lensing Science Collaboration, leading a community-wide machine-learning benchmarking effort on LSST-like data. 

This grant will support essential travel for international collaboration and dissemination. The funds will enable my participation in the July 2026 Rubin Community Workshop, followed by targeted collaboration visits in the United States. These visits will allow me to work directly with experts at the intersection of AI and astrophysics, including fellow Catalyst Postdoc Alliance Dr. Jimena González and other members of the Rubin community.

Gabriele Riccio

Extragalactic Distances with the Surface Brightness Fluctuation Method 

I am a postdoctoral researcher at the INAF – Osservatorio Astronomico d’Abruzzo. My scientific interests lie primarily in the field of extragalactic astronomy, with a focus on galaxy evolution and star formation, the study of stellar populations, and the measurement of extragalactic distances using the Surface Brightness Fluctuation (SBF) method. Together with my team in Teramo, I am currently working on developing efficient strategies to fully exploit the next generation of large astronomical surveys, such as LSST and Euclid, to obtain accurate and precise distance measurements across the Universe. To this end, my team and I have developed FAST-SBF, a new fast, robust, and automated pipeline for SBF analysis. The pipeline is specifically designed to operate on deep, wide-field imaging data and to efficiently process the massive datasets anticipated from facilities such as LSST.

This mini-grant project is part of the INAF-LSST in-kind contributions (ITA-INA-S6). The main goal of this project is to prepare the community of researchers working with LSST data to use the SBF method as a tool for distance measurements in their scientific applications. To achieve this goal, I plan to organize dedicated training sessions and to visit institutions of researchers interested in learning and applying the method. The training activities will primarily consist of hands-on hack sessions, during which participants will be guided through the steps required for SBF analysis, as well as the efficient use of the FAST-SBF pipeline. In addition, together with my team, we will organize a small workshop at the INAF – Osservatorio Astronomico d’Abruzzo in Teramo aimed at researchers interested in applying the SBF technique. Participants will be hosted for a few days and will work directly on SBF analysis using LSST data. For any further information, please do not hesitate to contact me.

Jake Miller

Young Astronomers Learning LSST (YALL)  

The University of Texas A&M will host the first in a small series of hands-on bootcamps educating interested students and faculty in the central Texas area on how to utilize the Rubin Science Platform (RSP). Graduate students, postdocs, and faculty from Texas A&M (TAMU) and the University of Texas Rio Grande Valley (UTRGV) can attend both workshops for free, encouraging both academic development and the fostering of new working relationships. Funding from this proposal will be utilized to prepare for the workshop and provide travel stipends to graduate students traveling from UTRGV.

The first day of this 2.5-day workshop will provide an overview of Legacy Survey of Space and Time (LSST) terminology, recent updates to the Rubin Observatory and the LSST, and familiarization with the basics of the RSP. The second day will consist of more focused activities, specifically crafted to cater to the science interests of the participating institutions. In particular, hands-on tutorials involving active galactic nuclei, supernovae, cataclysmic variables, and transients will be covered. The last half-day will cover more information regarding the usage and future of the RSP, such as the expected cadence of data releases, the timeline for future LSST-related events, and more. Finally, any materials created as part of this workshop will be made freely available to both the attendees and to the broader LSST community.

Colin Burke and
Antonio J. Porras-Valverde

Tracing the Seeds of Supermassive Black Holes with the Rubin Undergraduate Network

Colin Burke and Antonio J. Porras-Valverde are National Science Foundation Astronomy & Astrophysics Postdoctoral Fellows at Yale University working on black hole physics and scaling relations. Our project combines both of our areas of expertise: AGN variability modeling, Bayesian inference, and semi-analytic modeling to make quantitative predictions for the supermassive black hole population that LSST will observe. Together with two Yale undergraduates, we will incorporate light- and heavy-seed black hole formation pathways into the semi-analytic model Dark Sage and generate mock LSST-like AGN samples for direct comparison with observations. One undergraduate will produce synthetic AGN light curves using observed correlations between luminosity, black hole mass, and variability properties, while the other will implement new seeding prescriptions in Dark Sage and explore simulation-based inference techniques to link model predictions with LSST detections.

Yu-Ching (Tony) Chen

Building LSST Expertise: Rubin Science Platform Bootcamp Series for Institutional Readiness at JHU/STScI

My name is Yu-Ching (Tony) Chen, and I am a postdoctoral fellow at Johns Hopkins University (JHU) specializing in quasar research. As a member of the inaugural LSST-DA Catalyst Postdoc Alliance cohort, I will use the Leadership Mini-Grant to conduct the initiative, “Building LSST Expertise: RSP Bootcamp Series for Institutional Readiness at JHU/STScI.” This project is designed to substantially enhance the technical preparedness of our local research community by providing comprehensive, hands-on training for the Rubin Science Platform (RSP). Through the development and execution of a focused one-day workshop at JHU in early 2026, I will equip faculty, postdoctoral researchers, and graduate students with the specialized expertise required to access and analyze LSST data efficiently. This upskilling effort is strategically timed to ensure that local researchers are prepared to utilize upcoming Rubin data and establish critical professional connections during the LSST-DA regional meeting, which JHU/STScI will host in Summer 2026.

The requested funding will be primarily allocated to two months of dedicated Principal Investigator salary support, allowing me to disengage from existing grant obligations to master the latest RSP functionalities and curate the curriculum. The remaining funds will cover essential administrative and logistical expenses, thereby ensuring a professional and accessible training environment at JHU. Beyond its local impact, this project will establish a successful training model and resources for sharing throughout the Catalyst Postdoc Alliance, maximizing the grant’s influence across the broader LSST community.

Jesse Han 

Proposing for the Roman Ultrawide Survey in the era of LSST

Jesse Han is a Stanford Science Fellow, and will be using the funds to host a workshop focused on proposing for an ultrawide H-band survey with the Roman space telescope. The workshop will specifically highlight the synergies between LSST and a wide-field H-band survey.

Viraj Karambelkar

Marrying the deep with the red : An open-source tool for crossmatching Rubin and NEOWISE transient alerts

The Rubin Observatory presents an unprecedented opportunity for transient studies. This potential can be further enhanced by cross-matching Rubin alerts with existing infrared time-domain surveys, extending Rubin’s wavelength coverage and enabling the discovery of the reddest, dustiest transients that have so far been overlooked. Of particular interest is the NEOWISE mid-infrared survey, which provides a decade-long baseline preceding Rubin observations and coverage at mid-infrared wavelength. This project will aim to develop an open-source tool for crossmatching Rubin alerts to NEOWISE transients, thereby enabling joint searches for dusty, red transients in the Milky Way and beyond. This project will be led by an undergraduate student supervised by Dr. Viraj Karambelkar (NASA Hubble Fellow) and Prof. Kishalay De at Columbia University. The funds will be used to support the undergraduate student in the Summer of 2026.