Current Position
- Research Fellow
From 1st December 2017
Dept. of Astronomy, Yonsei University, Seoul, Korea
Grants and Awards
- National Research Foundation (NRF, South Korea) Creative Challenge Grant
Title: Testing Cosmological Models with Large Galaxy Surveys and Deep Learning Techniques
Amount: $150,000-250,000 (dependent on approval)
Duration: 06/2020 – 06/2023 - National Research Foundation (NRF, South Korea) individual grant
Title: Probing Dark Energy with Higher Order Statistics
Amount: $150,000
Duration: 06/2017 – 06/2020
Past employment
- Research Fellow
Korean Astronomy & Space Science Institute, Daejeon, Korea
November 2014 – November 2017 - Research Fellow (with Prof. Changbom Park)
Korea Institute for Advanced Study, Seoul, Korea
October 2012 – October 2014 - Postdoctoral Research Assistant (with Prof Ofer Lahav)
University College London, London, UK
October 2009 – October 2012
Education
- Institute of Cosmology & Gravitation, University of Portsmouth, UK
Ph.D in Cosmology, October 2009
Thesis: Large Scale Structures in the Sloan Digital Sky Survey
Supervisors: Prof. Robert Nichol, Prof. William Percival - Astronomy & Astrophysics Group, University of Glasgow, UK
MSc in Cosmology, 2006
Thesis: Probing the Large Scale Homogeneity of the Universe
Supervisors: Prof. Martin Hendry, Dr. Luis Teodoro - University of Glasgow, Glasgow, UK
BSc combined Honours in Physics & Astronomy, 2001-2005
Teaching Experience
- 2019, Yonsei University, Seoul – Machine Learning and Big Data Analytics in Astronomy
- 2012, KIAS, Korea – Graduate lecture course: Weak Gravitational Lensing
- 2012, University College London – 2 Summer intern students
- 2012, University College London – Physics laboratory demonstrator (2nd year)
- 2011, University College London – MSc project supervisor – Scott Burger (MSc passed)
- 2011, University College London – Physics laboratory demonstrator (1st year)
- 2010, University College London – Physics tutorial class leader
- 2005/06, University of Glasgow – Tutorial classes / Lab demonstrating
Computer Skills
- OS administration: Macintosh, Windows and Unix
- Languages: Fortran (expert), Python (expert), C/C++ (experienced)
- Parallelisation (OpenMP, MPI) for large scale shared and distributed memory architectures.
- Other: Matlab, IDL
Codes developed
- GRaph Made Statistics for Cosmological Inference (GRAMSCI): A big data analytic approach to higher-order correlation function estimation. The code is driven by a custom graph database and a powerful kd-tree implementation. Running in serial, OpenMP, MPI and hybrid parallel schemes. Source code available from: https://bitbucket.org/csabiu/gramsci
- KD-treeStatisticsPackage(Kstat): A fast and efficient framework for computing spatial statistics in a discrete point set. It is based on kd-tree structures for fast nearest neighbour searches and MPI for large scale parallelism. Source code available from: https://bitbucket.org/csabiu/kstat
- Pseudo Shear Power Spectrum (PS2): This code estimates the galaxy shear power spectrum. It uses at its core the Healpix package for spherical decomposition of discrete data. It works on the full sky and will reconstruct the true power spectrum in the presence of masking. Source code available from: https://bitbucket.org/csabiu/ps2
Languages
English (native), Italian (basic), Korean (TOPIK level 1)
