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General Pool

General pool software contributions are those where directable developer effort has been offered without an associated recipient group defined ahead of time. This pool of effort can be drawn on by any recipient group who have needs or gaps within their infrastructure or analysis software plans that are not covered by the current in-kind or other contributions. Normally recipient group(s) request general pooled software development effort for specific tasks. Note that such requests may come from either a single or multiple recipient groups who would benefit from the proposed development. Recipient groups can be either Rubin teams or LSST Science Collaborations. Further information is available on the In-kind Program Handbook

Contributions and Developers

General Pool resources have been offered by the folliowing programs and are listed with the skills of the developers available.
ProgramStartedNotes and Skills
Argentina OIAYesC/C++, Python, Fortran, SQL databases, Software debugging and testing, Docker and containerization, Data modeling, Data visualization, git, astronomy, Algorithm development, Data management, GIT, Machine Learning, Computer Vision 
Australia AALYesC/C++, Python, Java, Javascript, Node.js/React, SQL databases, noSQL databases, Software debugging and testing, Docker and containerization, Algorithm development, RESTful APIs, Data management, Project management, Virtual Observatory implementation, CI/CD, Mobile technologies, Full stack development, Project management, UI/UX, 
Canadapost 2026TBA
Hungary KonkolyYesC/C++, Python, Software debugging and testing, Algorithm development, Data modeling, Image processing, Data modeling, Data visualization, Virtual Observatory implementation, +basic machine learning, deep learning
India IIA2024TBA
Spain Barcelona/MadridYesC/C++, Python, Java, noSQL databases, Software debugging and testing, Docker and containerization,  Javascript,  RESTful APIs


Applications and Current Allocations

General pool resources can be applied for all year round. Any potential proposers should discuss their ideas with the main contact for a recipient group before applying. The link to application form can be requested by emailing jikh at lsst dot org.

A selection of allocted pool resources are listed here. 

ProjectRecipient GroupContributor
Interactive Visualizations/PlottingRubin Survey Scheduling TeamAustralia AAL
Build supportRubin Data ProcessingAustralia AAL
Targeted Identification of Low Signal-to-Noise Detections of Solar System ObjectsSolar System SCHungary KON
Community science software developerRubin Community Science TeamSpain BCM
Assistance to build a Strong Lensing Database for RubinStrong Lensing Science Collaboration & DESC SL Topical TeamAustralia AAL
Contribution to commissioning (FIG)SIT-Com teamSpain BCM


Developer Profiles

Some of the developers in the general pool have provided a short profile.

Cristobal Pio Garcia

Spain (ESP-BCM-S4)

I work as Software Engineer at IFAE being part of a multidisciplinary team that gives solutions to all the engineering challenges which IFAE leads or which participate in
I feel comfortable developing in C/C++, Python, Java, Javascript, CSS and HTML. We have a lot experience developing Control Software using any language or framework, this goes from desktop to web environment applications and from low to high level programming.
I helped developing the control software for PAU, an instrument for the WH Telescope fully developed at IFAE, also collaborating with other institutes I worked on  the camera control for the LST inside the CTA project (North Site), the instrumented baffle for VIRGO experiment and finally some control for different devices on the neutrinos experiment at T2K.

Tamás Kovács

Hungary (HUN-KON-S1)

I have been a member of the extragalactic research group for 2 years at the Eötvös University, Budapest, Hungary and am currently a senior research fellow. My primary interest is dynamical astronomy on different scales from solar system to exoplanets and galactic dynamics. I also work on the morphological characterization of well-resolved spiral galaxies. My preferred languages for work are C and python, but sometimes I also use MATLAB. I have also recently started coding in CUDA C, and I use machine learning method 'reservoir computing' for signal processing. 

Carolina Villalón

Argentina (ARG-OIA-S2)

I have been working as a scientific software developer and consultant since 2018, specifically in the area of astronomy at the Institute of Theoretical and Experimental Astronomy (IATE) in Córdoba, Argentina. In my position as support staff, I work with researchers, undergraduate and graduate students helping them with the computational aspects of astronomy, including code development, optimization and parallelization in addition to debugging, compiling and refactoring projects. Furthermore, I provide advice and technical assistance regarding the appropriate hardware for each case as well as training according to our researchers’ needs.
I have experience with Python and C and some knowledge in Fortran, OpenMP and HPC. In the past years, I have participated -and continue to do so- in projects involving the process and analysis of data from big surveys, such as the VISTA Variables in the Vía Láctea Survey (VVV) and I was also involved in the development of an image reduction pipeline. Thanks to these projects, I feel comfortable with third party libraries such as NumPy, Matplotlib, AstroPy, HealPy, CCDProc, with SQL databases and writing unit tests with pytest. Moreover, I really enjoy visualising data.

Marco Rocchietti 

Argentina (ARG-OIA-S2)

Since December 2022 I have been working at the Institute of Theoretical and Experimental Astronomy (IATE) supporting astronomers in the development of scientific software. I mostly provide assistance in the configuration, optimization and compilation of the codes that are used for their research projects. I am also an Adjunct Professor at the National University of Córdoba (Argentina) teaching in the programming laboratories of subjects such as Algorithms and Data Structures 1 and 2, Operating Systems at the Faculty of Mathematics, Physics and Computer Science.
I mainly develop software related to scientific computing using Python as the main language. My projects are related to the Computer Vision area and work with libraries such as OpenCV, Numpy, matplotlib, sklearn and a brief experience with pytorch for modelling neural networks. Also for academic purposes I have made developments in C and Haskell for the courses where I work as a teacher.
I have a degree in Computer Science and my thesis was about recognizing people through the iris. I am currently finishing my PhD in Computer Science on Face Recognition.




Financial support for Rubin Observatory comes from the National Science Foundation (NSF) through Cooperative Agreement No. 1258333, the Department of Energy (DOE) Office of Science under Contract No. DE-AC02-76SF00515, and private funding raised by the LSST Corporation. The NSF-funded Rubin Observatory Project Office for construction was established as an operating center under management of the Association of Universities for Research in Astronomy (AURA).  The DOE-funded effort to build the Rubin Observatory LSST Camera (LSSTCam) is managed by the SLAC National Accelerator Laboratory (SLAC).
The National Science Foundation (NSF) is an independent federal agency created by Congress in 1950 to promote the progress of science. NSF supports basic research and people to create knowledge that transforms the future.
NSF and DOE will continue to support Rubin Observatory in its Operations phase. They will also provide support for scientific research with LSST data.   

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