Driving Global Inference for New Physics with Machine Learning, Big Data and Large-scale Statistical Simulation

The physical sciences have entered the era of big data, and particle physics is no exception. Extremely powerful particle colliders, telescopes observing light across the energy spectrum, and precise underground experiments have been running for years and have produced remarkably detailed and complex data sets. While no definitive signal of new physics has yet emerged from these experiments, it is quite possible that hints of new phenomena are hidden in these results, only missed due to the limitations of our analysis methods. In this workshop, we will bring together statisticians and physicists to discuss novel methods of data analysis, with a focus on machine learning, in which computers are programmed to think in ways akin to humans. We will launch the development of new computer tools that will allow us to overcome current computational limitations and fully test particle physics theories against all available data, potentially leading to discoveries that will shed light on some of the most profound questions in physics.