# Members

If you are interested in joining the LSST ISSC, please see the Apply page.

## Regular Members

Member |
Institution |
Research Areas |

Tatiana Acero-Cuellar | University of Delaware | machine learning, computer vision, transient and variable phenomena |

Patrick Aleo | UIUC | Anomaly Detection, Supernova Classification, Similarity Search |

Ethan Anderes | UC Davis | Theoretical and applied methods for spatial statistics |

James Annis | Fermilab | Bayesian inference, deep learning |

Alejandra Munozar Arancibia | IFA-UV | |

Eric Aubourg | CNRS/IN2P3/APC Paris | Deep learning, Bayesian methods, Image processing |

Luis Ricardo Arantes Filho | Lab for Computing and Applied Math - INPE | Deep learning, supernovae |

G. Jogesh Babu | Penn State University | Statistical methods and theory |

Arash Bahramian | Curtin Institute of Radio Astronomy | Bayesian inference, Time series analysis |

Anastasia Baluta | Lomonosov Moscow State University | supernovae, anomaly detection |

Luan Orion Baraúna | Lab for Computing and Applied Math - INPE | Deep Learning, Time Series prediction and classification, Computer Vision, Radio Transients |

Jacek Becla | SLAC | Systems for managing extreme-scale data sets |

Wilson Beebe | University of Washington / LINCC Frameworks | Software engineering |

Saptashwa Bhattacharyya | University of Nova Gorica | Deep Learning, Computer Vision |

Federica Bianco | University of Delaware | Transients and variable stars |

Bryce Bolin | Goddard Space Flight Center | Deep learning |

Adam Bolton | NSF’s NOIRLab | Strong lensing, spectroscopic surveys, end-to-end data systems |

Kirk Borne | Booz Allen | Large databases, data mining, knowledge discovery |

Alexandre Boucaud | IN2P3/APC | Image processing, deep learning, mlops |

Doug Branton | University of Washington | Software Engineering, Data Science |

Robert Brunner | University of Illinois | Observational cosmology, transient and variable phenomena |

James Buchanan | Lawrence Livermore National Laboratory | Bayesian inference, weak lensing, galaxy detection and deblending |

Tamas Budavari | Johns Hopkins University | Computational statistics, low-dimensional embeddings, scientific databases |

Douglas Burke | Harvard CFA | Galaxy clusters, galaxy evolution, virtual observatory, semantic astronomy |

Nathaniel Butler | Arizona State University | Astrophysical transients |

Juan Cabral | CIFASIS, IATE, CONICET | Classification Methods, machine learning, software engeenering |

Guillermo Cabrera | Millenium Institute of Astrophysics | Machine learning, computer vision, data-science, astroinformatics |

Jean-Eric Campagne | CNRS/IN2P3/IJCLab | Deep Learning, auto-diff with JAX |

Sandro Campos | Carnegie Mellon University | Software engineering, machine learning |

Siddharth Chaini | University of Delaware | Deep Learning, Distance Metrics |

Yen-Chi Chen | University of Washington | Nonparametric statistics, cluster analysis, statistical learning theory, large scale structure |

David Chernoff | Cornell University | Cosmology, statistics and numerical methods for physics |

Aleksandra Ciprijanovic | Fermilab | Deep learning, domain adaptation, algorithm robustness and uncertainties |

Jessica Cisewski Kehe | University of Wisconsin - Madison | Statistical methods, topological data, approximate Bayesian computation |

James Cordes | Cornell University | Radio astronomy, neutron stars, pulsars, signal processing techniques |

John Franklin Crenshaw | University of Washington | Deep learning, photometric redshifts |

Mi Dai | University of Pittsburgh | |

Shar Daniels | University of Delaware | deep learning, anomaly detection |

Melissa DeLucchi | Carnegie Mellon University | High performance data analysis |

Boris Demkov | SNAD project member | classification methods, anomaly detection, clustering |

Biprateep Dey | University of Pittsburgh | Uncertainty Quantification, Deep Learning |

Mariano Dominguez | IATE | Galactic and extragalactic astronomy |

Cyrille Doux | CNRS/IN2P3 | Cosmology, Bayesian Inference, Deep Learning |

Jordan Dowdy | Bellarmine University | Algorithm development, Phosim |

George Djorgovski | Caltech | Computational, data-intensive science, development of cyberinfrastructure |

Marina Dunn | University of California, Riverside / Lawrence Livermore National Laboratory | Machine Learning/Deep Learning, Bayesian methods, galaxy morphology |

Pedro Antonio Escarate Monetta | Universidad Técnica Federico Santa María | Electro-optics systems, spectroscopy, astronomical instrumentation |

Susana Eyheramendy | Pontifica Universidad Catolica de Chile | Methods for Big Data |

Maria Luiza Falci | Universidade Federal Fluminense | |

Eric Feigelson | Penn State University | X-ray studies of star formation, cross-disciplinary astrostatistics |

Agnès Ferté | SLAC/KIPAC | Bayesian inference, dimensionality reduction |

Karin S. F. Fornazier Guimaraes | Instituto de Física da Universidade de São Paulo | Bayesian inference, machine learning |

Francisco Forster | Center for Mathematical Modelling / Millennium Institute for Astrophysics, Chile | Time series classification |

Willow Fortino | University of Delaware | transformers, generative AI, classification methods |

Peter Freeman | Carnegie Mellon University | Implementation of statistical methods in astronomy |

Shih Ching Fu | Curtin University | Bayesian inference, Gaussian Processes, Time series |

Alex Gagliano | University of Illinois, Urbana-Champaign | Classification, generative models, simulation-based inference |

Christopher Genovese | Carnegie Mellon University | Statistical methods and theory, nonparametric methods |

Aritra Ghosh | Yale University | Deep learning, uncertainty quantification |

Karl Glazebrook | Swinburne University of Technology | Observational cosmology, the formation and evolutionary history of galaxies |

Matthew Graham | Caltech | Data representation, visualization, storage, interpretation |

Alexander Gray | IBM | Scalable machine learning |

Carlo Graziani | University of Chicago | |

Julia Gschwend | LIneA | photometric redshifts, object classification, machine learning |

Leanne Guy | AURA/LSST | Mining alert stream and catalogues |

Jon Hakkila | College of Charleston | Gamma ray bursts |

Alan Heavens | Imperial College London | Bayesian inference, simulation-based inference |

Nina Hernitschek | Vanderbilt University | Large time-domain data sets, classifcation of variable sources |

Daniel Hestroffer | Paris Observatory / PSL | Bayesian inference; regression; parameter estimation |

Timothy Holt | Southwest Research Institute | Solar system body analysis |

Jianhua Huang | Texas A&M | Gaussian process, functional data analysis, spatial temporal statistics, Bayesian statistics |

Amr Ibrahim | Laboratorio Interinstitucional de e-Astronomia (LIneA) | Data science, informatics, programming |

Emille Ishida | CNRS/LPC-Clermont | Anomaly detection, active learning |

Zeljko Ivezic | University of Washington | Large survey astronomy |

Rafael Izbicki | Federal University of Sao Carlos | Nonparametric methods, high-dimensional inference |

Allan Jackson | Rubin DP0.2 delegate | LLM, deep learning, K-means |

Andrew Jaffe | Imperial College | Statistical cosmology, testing cosmological theories, Bayesian methods |

Daniel Leonardo Jasbick | Laboratório Interinstitucional de e-Astronomia (LineA) / Universidade Federal Fluminense | Data provenance, scientific workflows |

Elise Jennings | Argonne National Laboratory | Computational cosmology, large scale structure |

Andres Jordan | Pontifica Universidad Catolica de Chile | Exoplanets, early-type galaxies |

Bryce Kalmbach | University of Washington | Machine learning, photometric redshifts |

Vinay Kashyap | Harvard CFA | |

Somayeh Khakpash | Rutgers University | Microlensing , Time Series Classification, Machine Learning |

Kevin Knuth | University at Albany | Information physics, Bayesian data analysis, source separation |

Sthabile Kolwa | University of Johannesburg | Unsupervised learning for anomaly detection; Bayesian inference; source classification |

Simon Krughoff | LSST/AURA | Astronomical survey planning, data reduction, simulation |

Jeremy Kubica | Carnegie Mellon University | Software engineering, machine learning, algorithms |

Hermine Landt | Durham University | Time series, Gaussian processes |

Francois Lanusse | CNRS/INSU | Weak gravitational lensing, deep learning, generative modeling |

Marcelo Lares | IATE | Astrostatistics, data pipelines, visualization |

Anastasia Lavrukhina | Lomonosov Moscow State University | Classification methods, anomaly detection, deep learning |

Ilin Lazar | University of Hertfordshire | Galaxy classification using unsupervised machine learning |

Ann Lee | Carnegie Mellon University | Statistical and machine learning methods, high-dimensional data |

Boris Leistedt | Imperial College London | cosmology (3x2pt, LSS, photo-z’s), astro-statistics, deep learning |

Chris Lintott | University of Oxford | Machine learning, citizen science, serendipity |

Xin Liu | UIUC | AI for Astronomy, Astronomy for AI, Foundation models |

Michelle Lochner | University of the Western Cape/ South African Radio Astronomy Observatory | unsupervised learning, radio galaxies, transients |

James Long | MD Anderson Cancer Center | Machine learning, signal frequency estimation, measurement error models, functional data analysis |

Thomas Loredo | Cornell University | Statistical methods, Bayesian analysis, high energy astrophysics |

Olivia Lynn | Carnegie Mellon University / LINCC Frameworks | Software engineering |

Ashish Mahabal | Caltech | Astrophysical transients |

Konstantin Malanchev | University of Illinois Urbana-Champaign | anomaly detection, light-curve feature extraction, light-curve classification |

Alex Malz | Carnegie Mellon University | Uncertainty quantification and propagation, experimental design and metrics |

Kaisey Mandel | University of Cambridge | Supernova cosmology, time domain and transient astronomy, Bayesian modelling |

Luca Masserano | Carnegie Mellon University | Likelihood-Free Inference, Deep Learning, Uncertainty Quantification |

Justyn Maund | Unversity of Sheffield | Massive stars to supernovaes |

Juan Carlos Maureira | Universidad de Chile | Discrete systems simulation |

Francesca Mauro | MAS/Universidad de Concepcion | |

Jon McAuliffe | University of California, Berkeley | Machine learning, statistical prediction, variational inference |

Bruce McCollum | Caltech | |

Jason McEwen | University College London | Harmonic and wavelet transforms, compressed sensing, Bayesian inference |

Sean McGuire | Carnegie Mellon University / LINCC Frameworks | Software engineering, Large scale data analysis |

Summer McLaughlin | University of Sheffield | Classification methods, Gaussian Processes, Bayesian statistics |

Simona Mei | Universite de Paris | Large-scale structure, galaxy evolution |

Aaron Meisner | NSF’s NOIRLab | data-intensive science, anomaly detection |

Ismael Mendoza | University of Arizona | Bayesian Inference, Deep Generative Models, Galaxy Blending |

Christopher Miller | University of Michigan | Large-scale structure, galaxy clusters, astroinformatics |

Anais Moller | CNRS / LPC Clermont-Ferrand | Reproducibility, statistical coherence, transient classification |

Arrykrishna Mootoovaloo | University of Oxford | Bayesian methods, deep learning, data compression |

Marcelo Mora | Pontifica Universidad Catolica de Chile | Galaxy formation |

Daniel Mortlock | Imperial College London | Bayesian inference applied to astronomy |

Roberto Pablo Munoz | Pontifica Universidad Catolica de Chile | Formation and evolution of galaxies in high-density environments |

Craig Pellegrino | University of Virginia | Classification methods |

Silvia Pietroni | INAF-OAC | classification methods, machine learning, monitoring and data analyzes |

Agnieszka Pollo | NCBJ & UJ Poland | classification, regression, deep learning, anomaly search |

Becky Nevin | Fermilab | Deep learning, Bayesian inference, uncertainty in ML |

Bob Nichol | ICG Portsmouth | Large-scale structure, supernovae, advanced statistical methods |

Brian Nord | Fermilab and University of Chicago | Simulation-based inference, uncertainty quantification, deep learning |

Franc O | Northeastern University | Classification Methods, Geometric Deep Learning |

Drew Oldag | University of Washington / LINCC Frameworks | LINCC Frameworks |

Daniel de Oliveira | Universidade Federal Fluminense | Databases, distributed systems, scientific workflows |

Giuliano Pignata | Universidad Andres Bello | Supernovae, cosmology, solar system |

Kara Ponder | SLAC | SN cosmology, Classification and Follow-up for Transients, Bayesian inference |

Maria Pruzhinskaya | Laboratoire de Physique de Clermont, IN2P3/CNRS | supernovae, anomaly detection |

Andrew Ptak | NASA GSFC | Extragalatic X-ray astrophysics, software development |

Troy Raen | University of Pittsburgh | Classification methods |

Fernando Rannou | Universidad de Santiago de Chile | Image Synthesis, Big Data, Big Compute, ML |

Markus Michael Rau | Argonne National Laboratory | Inverse problems, spatial statistics, machine learning |

Umaa Rebbapragada | NASA JPL | Astronomical optical transient vetting, active learning |

Karthik Reddy | University of Maryland, Baltimore County | Extragalactic jets, X-ray and radio astronomy |

Jeffrey Regier | University of Michigan | Bayesian inference, deep learning, deblending |

Eniko Regos | Konkoly | Large scale structure |

Benjamin Remy | CEA Paris-Saclay | Bayesian Inference, Machine Learning, Generative Models |

Giuseppe Riccio | INAF - Astronomical Observatory of Capodimonte (Napoli - Italy) | machine learning, web applications, software developer |

Gordon Richards | Drexel University | Extragalactic astrophysics, AGN |

Joseph Richards | GE Digital | Statistical and machine learning methods for noisy, high-dimensional data |

Mickael Rigault | CNRS/IN2P3 | Forward Modeling, GPU pipeline |

Thales Rodrigues | Universidade Federal de Juiz de Fora | Deep learning, self-attention, computational physics |

Reinaldo Rosa | Lab for Computing and Applied Math - INPE -MCTI-Brazil | Data cubes, machine learning, gradient pattern analysis |

David Ruppert | Cornell University | Functional data analysis, measurement error models, semi-parametric methods, time series; for variable stars and extragalactic astronomy |

Vitor Sampaio | Universidade Cidade de São Paulo | Galaxy evolution, bayesian inference, deep learning |

Paula Sanchez Saez | Millenium Institute of Astrophysics / Pontificia Universidad | Classification of time series |

Nikolina (Niko) Sarcevic | Newcastle University | Bayesian inference |

Rubens Sautter | Lab for Computing and Applied Math - INPE | Pattern recognition, statistics, data mining |

Jeffrey Scargle | NASA Ames | High-energy astrophysics, time series and image analysis |

Chad Schafer | Carnegie Mellon University | Statistical methods, cosmological parameter estimation |

Samuel Schmidt | UC Davis | Photometric redshifts |

Nima Sedaghat | University of Washington / LSST | Deep learning, computer vision, transient detection |

Timofey Semenikhin | Lomonosov Moscow State University, Sternberg astronomical institute | neural networks, computer vision |

Lior Shamir | Lawrence Tech | Image analysis, galaxy morphology |

Xinyue Sheng | Queen’s University, Belfast | classification methods, deep learning |

Raphael Shirley | University of Southhampton | Bayesian inference, image classification |

Aneta Siemiginowska | Harvard CFA | Supermassive black holes, quasars and active galaxies |

Heloisa da Silva Mengisztki | Laboratório Interinstitucional de e-Astronomia | Photometric redshifts, object classification, machine learning |

Colin Slater | University of Washington | Image differencing algorithms, Milky Way structure |

Joshua Speagle | University of Toronto | Uncertainties in machine learning, scalable inference |

Jennifer Sobeck | University of Washington | Large survey datasets and databases, data mining, stellar populations |

Aleksandra Solarz | National Center for Nuclear Research | Classification |

Niharika Sravan | Drexel University | reinforcement learning, design of experiments |

Sreevarsha Sreejith | University of Surrey | Deep learning, Variational inference, Machine learning in Astronomy |

Keivan Stassun | Vanderbilt University | Formation of stars and planetary systems |

Connor Stone | Université de Montréal | forward model photometry, machine learning, galaxies |

Fiorenzo Stoppa | Radboud University | Statistics, Astrostatistics, Uncertainties characterization in ML |

Hyungsuk Tak | University of Notre Dame | Time series. image data analysis, Bayesian hierarchical modeling |

Jefferson Toledo | Universidade Federal da Paraiba | Ensemble methods, time series analysis, deep learning |

Martin Topinka | OA Cagliari | |

Tilman Troester | ETH Zurich | Spatial statistics, Bayesian inference in high dimensions, deep learning |

Eleni Tsaprazi | Imperial College London | Bayesian inference, field-level inference, high-order statistics |

Anke van Dyk | South African Astronomical Observatory | Stellar population studies, inference, capture-recapture |

Ricardo Vilalta | University of Houston | Pattern recognition, data mining, artificial intelligence |

Ashley Villar | Harvard University | Transient classification, hierarchical modelling |

Lucianne Walkowicz | Adler Planetarium | Discovery of unusual events, stellar magnetic activity |

John Wallin | Middle Tennesee State Univ. | Gravitational interactions |

Sam Ward | Institute for Astronomy, University of Cambridge | Bayesian Inference, Type Ia supernovae cosmology |

Larry Wasserman | Carnegie Mellon University | Statistical methods and theory |

Martin Weinberg | University of Massachusetts | Galaxy dynamics, simulation models |

Max West | University of Washington / LINCC Frameworks | software engineering, astronomical survey data |

Robert Wolpert | Duke University | Statistical methods and theory |

Huangfei Xiao | Florida State University | Bayesian inference; Machine learning |

Xiaomeng Yan | Texas A&M University | Time series classification |

Ilsang Yoon | NRAO | Classification and characterization of AGN |

Justine Zeghal | APC CNRS | Deep learning, bayesian inference, implicit inference (or likelihood-free inference / simulation-based inference) |

Yuanyuan Zhang | NSF’s NOIRLab | Bayesian inference, deep learning |

Conghao Zhou | UC Santa Cruz | Galaxy clusters |

## Affiliate Members

Member |
Institution |

Stephen Bailey | Lawrence Berkeley Laboratory |

Niel Brandt | Penn State University |

Salman Habib | Argonne National Laboratory |

Lynne Jones | University of Washington |

Kian-Tat Lim | SLAC |

Phil Marshall | KIPAC |

Jeffrey Newman | University of Pittsburgh |

Joshua Pepper | Lehigh University |

Cathy Petry | AURA/LSST |

Jonathan Sick | LSST |

Michael Strauss | Princeton University |

Jon Thaler | University of Illinois |