RESEARCH:

Colm Talbot works on applications of computational Bayesian inference in gravitational-wave astronomy. Collisions of black holes and neutron stars in the distant universe emit more energy in their final moments than all of the stars in the Universe. This energy is carried away as gravitational radiation, stretching and squeezing spacetime as they travel. After the first observation by advanced LIGO in 2015, these waves are now routinely observed. Talbot is interested in developing statistical methods, computational techniques, and theoretical models that enable us to use these observations to learn about the astrophysics of massive stars and the nature of relativity. In the coming years, the field of gravitational-wave astronomy will enter a data-rich era allowing for high-precision tests of astrophysics and fundamental physics. However, leveraging this larger dataset will require novel analysis techniques where AI methods show great promise. Additionally, Talbot is committed to developing open-source software tools for astrophysics.

BIO:

Colm Talbot joined the University of Chicago in 2023 as a Schmidt AI in Science Postdoctoral Fellow, working at the Kavli Institute for Cosmological Physics. Talbot received a B.A. in astrophysics and M. Math in applied mathematics and theoretical physics from the University of Cambridge in 2016 and a PhD in astronomy from Monash University advised by Eric Thrane in 2020. After this, Talbot spent 18 months as a postdoctoral researcher in the LIGO Laboratory, Caltech and two years as a Kavli Postdoctoral Fellow at MIT.