I have worked on a broad variety of topics in astronomy and cosmology, including the structure and dynamics of globular clusters, fundamental properties of galaxies and their evolution, gamma-ray bursts, early phases of galaxy and structure formation, distant quasars, gravitational lenses and binary quasars, cosmological tests, dark energy, exploration of the time domain, etc. I also worked on large digital sky surveys, Virtual Observatory and other cyber-infrastructure, and the growing field of astroinformatics. I am mainly interested in how Machine Learning and AI can be used to systematically analyze and explore these large and complex data sets and the observable parameter space, possibly even to discover new types of astrophysical objects and phenomena. My current interests are in developing tools for collaborative human-AI discovery, and the uses of Extended Reality technologies for science and education.
More broadly, I am interested in the ways in which computational and information technology changes the ways we study and understand the world around us. This ongoing revolution is changing all of science and scholarship, along with nearly every other aspect of modern society. As all fields of science face the challenges of exponential growth of data volumes and complexity, and extraction of knowledge and understanding from the data, we are essentially forging new, general tools for the scientific methodology in the 21st century. To this effect, I have been working on the data science methodology transfer between different fields, for example from astronomy and space science to medicine.