Prof. Ashutosh Kotwal

Since the discovery of the Higgs Boson at the LHC over a decade ago, the search for Dark Matter has emerged as a new frontier in fundamental physics, pursued through both direct-detection and collider-based experiments. Simultaneously, Artificial Intelligence (AI) is rapidly advancing in various aspects of our lives. Most AI applications rely on mathematical models that are trained to recognize or replicate data generated or validated by human intelligence. However, I will discuss a different type of AI that is grounded in fundamental logic and does not require prior training. I will demonstrate how this AI can be utilized to search for Dark Matter at the LHC. Additionally, by embedding this AI directly onto silicon chips, it can operate much faster than traditional computers.These concepts may also be applied to other areas of computer vision. Furthermore, I will address a growing perspective that emphasizes the need for AI to be explainable in order to ensure its reliability.