Candidate President 2024-2027, 50 words summaries
David van Dyk (Imperial/UK)
David van Dyk is Professor of Statistics at Imperial College London. He has held positions at Harvard and University of California, Irvine. He is a Fellow in the American Statistical Association (2006), the Institute of Mathematical Statistics (2010), and the International Astrostatistics Association (2016). He is a recipient of the Wolfson Merit Award (2011) and the ASA Founders Award (2019) and was elected to the Board of Directors of the ASA (2015-17). He focuses on methodological and computational issues with Bayesian analysis of highly structured models and emphasizes interdisciplinary research, especially in astrophysics, solar physics, and high-energy physics. He founded and coordinates the CHASC International Astrostatistics Center and is interested in improving the efficiency of computationally intensive methods involving data augmentation, such as EM-type algorithms and various Markov chain Monte Carlo methods.
Elena Sellentin (Leiden/Netherlands)
Elena Sellentin is Associate Professor at the Mathematics Institute and Leiden Observatory at the University of Leiden, the Netherlands. She specialises in the statistical analysis of cosmological data and is also PI of a medical imaging study. She has explored the challenges of gaussian and non-gaussian likelihoods, of relevance to much of cosmological survey data analysis, including fusions between Bayesian and machine learning likelihoods, and replacing the Hartlap factor with a principled Bayesian approach. She graduated from the University of Heidelberg in 2016, was a DAAD postdoctoral fellow at the University of Geneva and Imperial College, and won several interdisciplinary prizes of mathematics and physics, including the IAA Outstanding Paper award in 2020. She serves on the Editorial Board of the Euclid satellite, and after winning several competitive grants, she is now faculty at the University of Leiden.
Candidate Council Members 2024-2027, 50 words summaries
Aaron Robotham (ICRAR-UWA/Australia)
Aaron Robotham (PhD University of Bristol 2005-2008) worked at the University of St Andrews as a post doc until 2012 where he developed the GAMA galaxy group catalogue. He is now faculty at ICRAR-UWA, when he became more invested in developing statistically motivated techniques and software for data analysis, such as the Bayesian decomposition code ProFit, rigorous source extraction code ProFound and SED fitting code ProSpect. These all came together with his spectral spatial decomposition code ProFuse. He is a passionate advocate of rigorous statistics and has written and released many analysis packages over the years to encourage others in this direction. He has also been teaching a Masters level computational Bayesian statistics course for the last 5 years. He presents regularly regarding statistical topics, including to the IAA in 2022.
Andrew Jaffe* (Imperial/UK)
Andrew Jaffe is Director of the Imperial Centre for Astrophysics and Professor of Astrophysics & Cosmology at Imperial College London, specialising in statistical analysis of cosmological data, especially from the CMB and cosmic shear surveys. He graduated with a BS from Yale, and a PhD from Chicago, before moving to CITA as a postdoctoral fellow and then to Berkeley as Assistant Research Physicist/CfPA Fellow. He came to Imperial in 2001 first as an Advanced Fellow. He is a named Gruber prize winner with the Planck team.
Andriy Olenko (La Trobe/Australia)
Andriy Olenko (PhD National Kyiv University Ukraine), where he worked as an Associate Professor until 2007. He is now an Associate Professor of Statistics at La Trobe University. Dr Olenko has published more than 90 peer-reviewed papers, one monograph, nine textbooks, and two books on methods of computational statistics. He is on the editorial boards of 4 international journals. Andriy was a Chief Investigator of seven European and NATO grants, and two Australian Research Council Discovery grants. His research areas include spatial statistics, time series analysis, theory of random processes and fields, stochastic approximation and wavelet methods and their applications, in particular in signal processing, cosmology, and environmental sciences. His work focuses on evolutionary models for the universe and the exploration of Cosmic Microwave Background radiation, including the investigation of associated anomalies.
Arrykrishna Mootoovaloo (Oxford/UK)
Arrykrishna is an LSST Catalyst fellow at the University of Oxford from Mauritius, building emulating frameworks for nuisance-marginalized posteriors, e.g., for the Planck likelihood. He is also embedding differentiable emulators in JAX-COSMO. He is also developing a Bayesian Hierarchical pipeline for inferring the redshift distributions of objects in a catalogue.
Ashley Villar (Harvard/USA)
Ashley Villar is an assistant professor of Astronomy at Harvard University. Her research focuses on data-driven analysis of optical transients, including core-collapse supernovae and kilonovae. She is particularly interested in representation learning for sparse, multivariate light curves. Ashley is the co-Chair of the LSST Informatics and Statistics Science Collaboration and a member of the Rubin Science Advisory Council.
Benjamin Wandelt (IAP-Sorbonne/France)
Professor Benjamin Wandelt (Ph.D., Imperial College, Fellow of the International Association of Astrostatisticians and the American Physical Society) is the International Chair of Theoretical Cosmology at Sorbonne University and the IAP. He has held (visiting) faculty positions at Caltech, Illinois, the IAS, Princeton, MPA, NYU, and the Flatiron Institute. His awards include the Bessel prize, the Sofia Kovalevskaja award, a senior Excellence Chair of the Agence Nationale de Recherche, and the 2018 Gruber Prize in Cosmology.
Daniela Huppenkothen (SRON/Netherlands)
Daniela Huppenkothen is a staff scientist at the SRON Netherlands Institute for Space Research, where she works at the intersection of space research, statistics and machine learning. Before, she was the Associate Director at the DIRAC Institute at the University of Washington, and a Moore-Sloan Data Science Postdoctoral Fellow at NYU. She holds a PhD in Astronomy from the University of Amsterdam, where she now also has a guest appointment and works with a wonderful group of students on neural network emulators, simulation-based inference and representation learning on a range of different astronomical topics.
David Stenning (Simon Fraser/Canada)
David Stenning is an Assistant Professor in the Department of Statistics & Actuarial Science at Simon Fraser University (SFU). His research is focused on developing statistical methodology to tackle diverse challenges in astronomy and astrophysics, such as detecting exoplanets and inferring their population distributions, characterizing fast radio bursts, and predicting the timing and morphology of the solar cycle. This work typically involves Bayesian modelling and computing, Gaussian process emulation and uncertainty quantification, and/or machine learning. David is a member of the Canadian Hydrogen Intensity Mapping Experiment, and prior to SFU held positions at Imperial College London, the Statistical and Applied Mathematical Sciences Institute/Duke University, and Institut d'Astrophysique de Paris.
Domenico Marinucci* (Rome Tor Vergata/Italy)
Domenico Marinucci is a full Professor of Probability and Mathematical Statistics at the Department of Mathematics of the University of Rome Tor Vergata, which he directed for 8 years. He is a former ERC grantholder, a member of the Planck and Euclid missions of the European Space Agency, a collaborator of other astroparticle experiments such as PAMELA and ARGO-YBJ and the editor in chief of the Electronic Journal of Statistics. He is also an invited speaker for the European Congress of Mathematics in 2021. His research interests are mainly in the analysis of spherical random fields, with applications to Cosmic Microwave Background radiation data, see https://www.mat.uniroma2.it/~marinucc/
Elena Sellentin* (Leiden/Netherlands)
Elena Sellentin is Associate Professor at the Mathematics Institute and Leiden Observatory at the University of Leiden, specialising in the statistical analysis of cosmological data. She has explored the challenges of gaussian and non-gaussian likelihoods, of relevance to much of cosmological survey data analysis, including improving the Hartlap correction with a principled Bayesian approach. She graduated from the University of Heidelberg, was a DAAD postdoctoral fellow at the University of Geneva and Imperial College, and is now University of Leiden faculty.
Eric Feigelson (Penn State/USA)
Eric Feigelson has worked on the interface between statistics and astronomy for 40 years. This includes outreach to the astronomical community: organizing Summer Schools for young astronomers and cross-disciplinary conferences for researchers, authoring a graduate textbook, initiating Commission B.3 in the International Astronomical Union, and currently serving as Statistics Editor for the American Astronomical Society journals. He also leads a research enterprise that brings new time series methodology to the discovery of transiting planets.
Gwen Eadie (Toronto/Canada)
Gwendolyn Eadie is an Assistant Professor of Astrostatistics at the University of Toronto, jointly appointed between the Departments of Astronomy & Astrophysics and Statistical Sciences. She is the founder and co-leader of the Astrostatistics Research Team at the University of Toronto. She studies galaxy and globular cluster evolution in the context of dark matter halos, using novel statistical techniques and hierarchical Bayesian models. She is also the PI on two interdisciplinary research grants in astrostatistics to (1) bring together statisticians and the CHIME/Fast Radio Burst collaboration to better understand the nature of FRBs, and (2) study stellar flares in M-dwarf stars using novel statistical methods from time series analysis. Past awards include the 2021 Polanyi Prize in Physics, the 2020 Connaught New Researcher Award, and the 2018 J.S. Plaskett Medal.
Hyungsuk Tak (Penn State/USA)
Dr. Hyungsuk Tak is an Assistant Professor in the Department of Statistics, Department of Astronomy and Astrophysics, and Institute for Computational and Data Science at the Pennsylvania State University. He was an Assistant Professor at the University of Notre Dame from 2018-2019, and a postdoc at the SAMSI ASTRO program from 2016-2018. Dr. Tak develops practically motivated data analytic tools to tackle statistical challenges in analyzing astronomical data. In particular, he is actively working on time delay cosmography to infer the Hubble constant, and deal with statistical challenges in modeling stochastic variability of irregularly-spaced time series data and developing Markov chain Monte Carlo methods to better explore multimodal parameter spaces. He is also interested in measurement-error astronomy, solving issues in high-redshift quasar classification or outlier-robust time series analysis in the presence of measurement error.
Ilya Mandel* (Monash/Australia)
Ilya Mandel is a theoretical astrophysicist and astrostatistician with particular interests in gravitational-wave astrophysics, binary star evolution, dynamics and high-energy astrophysics. In the context of astrostatistics, he has worked particularly on inference, hierarchical modelling, and time-domain astronomy. He is a Professor at Monash University, Australia (previously at the University of Birmingham, UK). Ilya is a previous member of the Council.
Jogesh Babu (Penn State/USA)
Jogesh Babu is a Past President of IAA, and is a Statistician at Penn State. The term \u201cAstrostatistics\u201d was coined by Babu and Feigelson in 1990s, when they published a book by the same name. Babu contributed extensively to mathematical statistics, probability, probabilistic number theory, and their applications. Babu led year-long and semester- long Astrostatistics programs at SAMSI, that helped careers of many scientists.
Josh Speagle (Toronto/Canada)
Josh Speagle is an Assistant Professor of Astrostatistics at the University of Toronto. He has been involved with astrostatistics efforts for several years and is currently a member of the American Astronomical Society (AAS) Working Group on Astroinformatics and Astrostatistics (WGAA) and the Webmaster for the American Statistical Association (ASA) Astrostatistics Interest Group (AIG). If elected as a member of the IAA Council, he looks forward to supporting ongoing IAA efforts for education, discussion, and outreach as well as improving coordination between various astrostatistics-affiliated organizations.
Kaisey Mandel (Cambridge/UK)
Kaisey Mandel is Professor of Astrostatistics and Data Science at the University of Cambridge, with a joint, interdisciplinary appointment at the Institute of Astronomy and at the Statistical Laboratory of the Department of Pure Mathematics and Mathematical Statistics. He is particularly interested in Bayesian modelling and machine learning for time-domain and transient astronomy and cosmology. He currently serves as Chair of the Astrostatistics Interest Group of the American Statistical Association.
Klea Panayidou (European University/Cyprus)
Klea Panayidou focuses on statistical modelling. Her past team\u2019s medical work has been used as a reference for HIV treatment and Care guidelines and publications of the World Health Organization (WHO). Currently as an educator, she has been promoting data literacy and statistical modelling in Medical and Physical Sciences.
Matthew Graham* (ZTF/USA)
Matthew Graham is a senior researcher in the application of advanced statistical and machine learning methods to astronomical problems, particularly large sky surveys and time series. He is the Project Scientist for the Zwicky Transient Facility as well as the Vice Chair of the AAS WG for Astrostatistics and Astroinformatics.
Maya Fishbach (CITA-Toronto/Canada)
Maya Fishbach is an assistant professor in the Canadian Institute for Theoretical Astrophysics (CITA) at the University of Toronto. Her research strives to understand how, where and when black holes and neutron stars are made, particularly those in gravitational-wave binaries. She applies statistical methods such as hierarchical Bayesian inference to analyze and interpret populations of gravitational-wave sources and their environments. She is generally interested in the statistical inference of astronomical catalogs and the connection between observational data and theoretical models.
Dr Natalia Porqueres is a Bayesian Astrophysicist, specializing in field-level inference of non-Gaussian data. She has lead research on field-level cosmological data analysis from the Lyman-alpha forest, galaxy surveys and weak lensing surveys. With a PhD from 2019, she became postdoc at Imperial College London and is now the Beecroft fellow at the University of Oxford. She serves on the Editorial Board of the Euclid satellite and is the equity and diversity officer of several academic consortia.
Pauline Barmby (Western/Canada)
Pauline Barmby is Professor and Chair in the Department of Physics & Astronomy at Western University. Her research interests include astroinformatics and multi-wavelength studies of galaxies and their star clusters. She was previously an astrophysicist at the Smithsonian Astrophysical Observatory and a member of the IRAC instrument team for the Spitzer Space Telescope. Barmby co-chaired the 2020 Long Range Plan for Canadian Astronomy.
Snehanshu Saha (BITS-Pilani Goa/India)
Snehanshu Saha is a Professor of Computer Science and Heads the Anuradha and Prashanth Palakurthi Centre for Artificial Intelligence Research(APPCAIR) at BITS Pilani Goa Campus. He has published 110+ peer-reviewed articles in International journals and conferences including several MNRAS and ASCOM papers. Dr. Saha is a Fellow of IETE. His current and future research interests lie in Data Science, theory of Machine Learning and AstroInformatics.
Google Scholar: https://scholar.google.com/citations?user=C-Qm2LcAAAAJ&hl=en
His H-index is 19 with a cumulative citation of 1656.
Stefano Andreon* (INAF-Brera/Italy)
Stefano Andreon is an astronomer of INAF-Osservatorio Astronomico di Brera, one of the vice-presidents and the secretary of IAA, and the vice-president of the Astroinformatics and Astrostatistics Commission Organizing Committee of IAU. He is the chair of the organizing board of the IAU-IAA Astrostatistics and Astroinformatics seminars. He teaches Astrostatistics in several european universities (>15 in 9 countries thus far) and is an (2016) IAA fellow. As an astronomer, his main current astronomical interest is understanding, using Bayesian methods and observational data, how galaxy clusters evolve.
Vinay Kashyap* (Center for Astrophysics/USA)
Vinay Kashyap is an Astrophysicist specializing in solar and stellar coronae, astrostatistics, and algorithmic tools for the analysis of high-energy astronomical data. He is a calibration scientist at the Chandra X-ray Observatory at the Center for Astrophysics at Cambridge, MA. He is a charter member of the CHASC Astrostatistics Center, and a former Chair of the Astrostatistics Interest Group of AmStat. He also leads the Calibration Statistics Working Group of the International Astronomical Consortium for High-Energy Calibration, and is a member of several Astrostatistics organizations.
Yang Chen (Michigan/USA)
Yang Chen is an Assistant Professor in the department of statistics and a research assistant professor of MIDAS at the University of Michigan, Ann Arbor. She has worked on various astrostatistics problems including astronomical instrument calibration and solar flares predictions and published in leading journals of statistics and astronomy. Yang had served as the secretary in 2018-2020, program chair elect in 2021, and program chair in 2022 for the ASA Astrostatistics Interest Group (AIG).
* current members of IAA Council nominated for reelection