Lior’s research focuses on data science. His approach to data science is holistic, combining a broad range of methods in machine learning, soft computing, and computational statistics to develop new paradigms that can turn data into knowledge and scientific discoveries. The other part of his research is the application of the data science methodology to data from a large number of disciplines. So far he made data-driven discoveries in fields such as astronomy, biology, medicine, humanities (art, music), psychology, marine biology, and more. He takes part in multiple collaborations such as the Large Synoptic Survey Telescope (LSST), the Astrophysics Source Code Library (ASCL), and the Midwest Big Data Hub (MBDH), where he has been serving on the steering committee since it was founded.
