Institut d'Astrophysique de Paris (IAP)
I am a Postdoctoral Fellow at the Institut d'Astrophysique de Paris, having previously obtained my DPhil in Astrophysics under the supervision of Prof. Pedro Ferreira and Dr Harry Desmond at the University of Oxford. I am also a member of the Simons Foundation on Learning the Universe. I am interested in statistical and machine learning methodology in astrophysics and cosmology, Bayesian large-scale structure inference, field-level inference using BORG (Bayesian Origin Reconstruction from Galaxies), and probing dark energy and constraining dark matter with astronomical surveys.
Chotipan Boonkongkird Access to author's publication
Chotipan Boonkongkird is a PhD student at Sorbonne Université. His work involves machine learning techniques to develop cosmological tools for the Lyman-alpha forest to gain better insights from the current and future observations. He is also interested in weak gravitational lensing and large scale structure physics.
Simon Ding Access to author's publication
Simon Ding is a PhD student at the Institut d'Astrophysique de Paris under the joint supervision of Guilhem Lavaux and Jens Jasche. He is also a member of the Euclid consortium and the Simons Foundation collaboration on Leraning the Universe. He is generally interested in all things machine learning and statistical inference. His research focuses on constraining the initial conditions and primordial non-gaussianities from galaxy clustering surveys. To this end, he develops and tests new forward modeling approaches. Currently, he is working on the halo/galaxy bias problem.
Remi Fahed Access to author's publication
Rémi Fahed is a research engineer at the Institut d'Astrophysique de Paris. His expertise includes software and pipeline design, with an 8 year experience in the Euclid Science Ground Segment. He is now working on the implementation of a forward modelling approach for the Euclid data analysis in collaboration with Guilhem Lavaux and Florent Leclercq. He also contributes to the Euclid SGS simulation team as the main developper of the ground based observations simulation code.
Matthew Ho is a postdoctoral fellow at the Institut d'Astrophysique de Paris. His research focuses on using higher-order information from large scale structure surveys to do precision parameter inference. This includes studying the use of data-driven tools such as machine learning models to capture these signals, accelerate their forward modeling, and robustify their inference.
Tristan Hoellinger is a PhD student in Cosmology at the Institut d'Astrophysique de Paris, and a member of the Euclid consortium. His main research focuses on the development of novel Bayesian approaches to get precise and unbiased constraints on dark energy and the sum of neutrino masses from cosmic web probes, towards application to extract as much information as possible from current and future large galaxy surveys.
Axel Lapel Access to author's publication
Axel Lapel is a PhD student in the Cosmology group of the Institut d'Astrophysique de Paris. His main research focuses on the development of new statistical tools beyond the standard 2-point analysis to infer the mass of neutrinos from Large Scale Structures and the Cosmic Microwave Background. His work involves exploring a forward modeling approach, higher-order summary statistics, likelihood-free inference, and cross-correlation of cosmological probes through the preparation of Nx2pt analyses for next-generation surveys.
Guilhem Lavaux is a permanent research scientist. He is interested in constraining fundamental physics through the use of cosmological probe. To achieve this he builds high performance and scalable algorithms to make optimal use of existing and future cosmological data sets like galaxy surveys or the cosmic microwave background. He works at the intersection of data analysis, physical modeling of observations, large scale statistical inference, high performance computing, simulations and visualization. He is a cofounder of the Aquila consortium.
Florent Leclercq is an interdisciplinary CNRS researcher in cosmology and information science. The general goal of his work is to maximise the scientific potential of large cosmological data sets to test theories of fundamental physics. To do so, he develops and uses innovative and dedicated information science and data science techniques, including statistical inference, machine learning, and high-performance computing.
Rosa Malandrino Access to author's publication
Rosa Malandrino is a PhD student in Cosmology at the Institut d'Astrophysique de Paris, working under the supervision of Benjamin Wandelt. Her research focuses on extracting the cosmological parameters from voids, in order to complement the constraints from other cosmic web probes and fully leverage the information contained in large galaxy surveys. This includes employing machine learning techniques for Simulation Based Inference.
Benjamin Wandelt is a professor at the Sorbonne Université and the director of the Institut Lagrange de Paris. His research connects fundamental physics and cosmology with astronomical data on scales ranging from the inner halos of galaxies to the largest scales accessible to observations.
Max Planck Institüt für Astrophysik
Martin Reinecke Access to author's publication
Fabian Schmidt is a research group leader at MPA. He is interested in theoretical approaches to large-scale structure, and to using large-scale structure to learn about gravity, dark energy, and the early Universe.
Julia Stadler Access to author's publication
Julia Stadler is a Postdoc at the Max-Planck-Institut für Astrophysik. Her research focuses on parameter inference from Large Scale Structure and how to control theoretical and observational biases. She is also interested in forward modeling, Bayesian analysis and numerical methods in a broader context, in particular interferometric imaging of the Galactic Center.
University of Michigan
Minh Nguyen is a postdoctoral research fellow at the Leinweber Center for Theoretical Physics (LCTP), University of Michigan. His interests and works in Bayesian forward modeling span the scale of galaxies, clusters and the Cosmic Microwave Background (CMB), and the range of method-algorithm development to (real) data application. He obtained his PhD at the Max Planck Institute for Astrophysics in 2020, where he developped the first Bayesian framework to optimally extract the kinematic Sunyaev-Zeldovich signal from the CMB. He is now at LCTP working on new probes to hunt and test new physics beyond the Standard Model of Cosmology - LambdaCDM. He is a big believer in diversity in science and an equally big fan of cue sports.
Metin Ata Access to author's publication
Aline Chu Access to author's publication
Ludvig Doeser Access to author's publication
Ludvig Doeser is a PhD student at Stockholm University. His research mainly involves large-scale structure analysis through the incorporation of machine learning techniques. In particular, his work involves using and developing field-level emulators to accelerate forward simulations within field-level inference of the initial conditions of the Universe. He is also interested in how the use of physics-informed priors can robustify the use of flexible machine learning networks in inference.
Jens Jasche is an associate professor at the University of Stockholm working at the interface between theory and observations. His research focuses on understanding the gravitational evolution of the cosmic large-scale structure and the imprints of dark matter and dark energy in large surveys of the observed galaxy distribution. A common element in all his research is the development and application of modern data science as well as artificial intelligence techniques to characterize fundamental properties of the dark sector physics, test the theory of gravity and identify new physical phenomena in observations.
Arthur Loureiro is a researcher at the Oskar Klein Centre at Stockholm University and has been a visiting researcher at Imperial College London since 2020. He is a member of several astronomical collaborations, including the Kilo Degree Survey, the Euclid Consortium, and LSST's DESC. Arthur's research focuses on statistical analysis of the large-scale structure of the universe, with a particular emphasis on galaxy clustering and weak lensing. He is interested in employing advanced statistical tools such as Bayesian hierarchical models, Hamiltonian Monte Carlo, Variational Inference, and machine learning-accelerated sampling to study neutrino properties and primordial non-gaussianities in the late universe.
Stuart McAlpine Access to author's publication
Stephen Stopyra Access to author's publication
Stephen Stopyra is a postdoctoral researcher at the University of Stockholm and the Oskar Klein Centre. His research sits at the interface of particle physics and cosmology, with a current focus on large scale structure. On the particle physics side, he has worked on electroweak vacuum decay during inflation, and the behaviour of stochastic spectator fields. On the cosmology side, he studies cosmological voids and has contributed to the development of the genetically-modified N-body initial conditions generator, "genetIC". He is interested in how cosmology can be used to learn about high-energy physics and vice versa (such as through neutrinos, the nature of dark matter, and modified gravity).
Eleni Tsaprazi Access to author's publication
Eleni Tsaprazi is a PhD student at Stockholm University working with probes of the cosmic large-scale structure and supernova distance tracers to study the physics of the Dark Universe. Her research employs a cosmological Bayesian inference framework to constrain cosmological parameters and test various Dark Energy and Modified Gravity models. She is also interested in the origin and evolution of the large-scale peculiar velocity field and its effects on cosmological observations.
University of Oxford
Natalia is a Beecroft fellow at Oxford University. Her research focuses on understanding how cosmic structures form and the imprints of dark matter and dark energy on galaxies. To do so, she develops data analysis techniques to analyse cosmological surveys at the pixel level and constrain the cosmological parameters and the dark matter distribution.
Richard Stiskalek is a DPhil candidate at the University of Oxford supervised by Julien Devriendt, Adrianne Slyz and Harry Desmond. He concentrates on devising novel tests of physics through the use of constrained cosmological simulations. In addition, his research encompasses galaxy kinematics, the galaxy-halo connection, and the strong-field lensing of gravitational waves.
Imperial College London
Lucas Makinen Access to author's publication
James Prideaux-Ghee Access to author's publication
James Prideaux-Ghee is a PhD Student at the Imperial Centre for Inference and Cosmology (ICIC) at Imperial College London working on using Bayesian methods to improve understanding of large-scale structure. His work involves improving the statistics of 3D reconstructions of the large-scale dark matter density and peculiar velocity fields produced by the Aquila software package BORG.
University of Groningen
Amina Helmi Access to author's publication
Ewoud Wempe Access to author's publication
Ewoud Wempe is a PhD student at the Kapteyn Astronomical Institute in Groningen. He is simulating the Local Group in BORG, embedding them in the Local Large Scale Structure.
Laboratoire de Physique Nucléaire et des Hautes Énergies (LPNHE)
Pauline Zarrouk Access to author's publication
Pauline Zarrouk is a permanent research scientist. She is interested in understanding the fundamental laws of the universe through cosmological probes, in particular the nature of gravity. She is performing galaxy clustering analysis using spectroscopic surveys and she is mainly involved in DESI which is the first new generation of large-scale galaxy survey that has started taking data since May 2021. She is also developing beyond standard galaxy clustering analyses that exploit non-Gaussian and non-linear information to improve the constraints on cosmological parameters.
Laboratoire de Mathématiques Blaise Pascal
Vincent Souveton is a PhD student in Applied Mathematics. His research focuses on studying, developing and deploying sampling algorithms with applications in Cosmology. More specifically, he is interested in both Machine Learning techniques, such as Normalizing Flows, and non reversible Monte Carlo methods relying on Piecewise Deterministic Markov Processes.
Luz Angela Garcia holds a Ph.D. in Astrophysics from CAS at Swinburne University of Technology. She is a postdoctoral researcher at Universidad ECCI, investigating the nature of Dark Energy and the Early Universe with high-resolution cosmological simulations. She is also interested in outreach and science communication and actively promotes more diverse and inclusive environments for women in STEM.
Tata Institute of Fundamental Research
Suvodip Mukherjee is an observational cosmologist, interested to study different aspects of fundamental physics, astrophysics and cosmological phenomena using Cosmic Microwave Background (CMB), large scale structure and gravitational waves as observational probes. His work encompasses theoretical analysis, numerical calculations and developing statistical tools to understand the imprints of cosmological and astrophysical phenomena from the observed data.
University of Arizona
University of Waterloo
Michael Hudson Access to author's publication
Mike Hudson is a Professor at the Waterloo Centre for Astrophysics at the University of Waterloo. He is interested in using cosmological data sets to uncover the distribution of dark matter over a range of scales, from galaxy halos to large-scale cosmic structures, and its relationship to the distribution of galaxies.
Observatoire de la Côte d'Azur
Università di Bologna
Adam Johansson Andrews Access to author's publication
Adam Johansson Andrews is a PhD student at Stockholm University whose research involves large-scale structures and 3D reconstruction of the dark matter fields. By employing modern data science techniques e.g. Bayesian inference and machine learning, Adam’s main research interest is to probe into the fundamental aspects of physics: nature of dark matter and dark energy, neutrino masses, and galaxy formation.
University of Leiden
Martijn Oei Access to author's publication
Martijn Oei is an incoming postdoctoral fellow studying the intersection of cosmology, radio astronomy, and statistics. A major goal of his work is to observe the magnetised Cosmic Web, so that the primordial and astrophysical contributions to magnetogenesis can be disentangled and quantified. Exciting observational probes for this goal are accretion shocks, fast radio bursts, giant radio galaxies, and radio bridges between clusters on the cusp of merging.
University of Portsmouth
Harry Desmond is a Royal Society University Research Fellow at the Institute of Cosmology and Gravitation. He is interested primarily in devising and conducting novel tests of gravity using galaxy-scale signals. These tests often rely on precise characterisation of galaxies' gravitational environments, and hence require statistical knowledge of the distribution of surrounding matter. He also studies the relation between light and mass in galaxies, i.e. the galaxy-halo connection.