IT-centric and data-intensive scientific discovery offers boundless opportunities for impact on complex systems, as well as the means to infer intelligence and actionable information from big data. The field requires cutting-edge high-performance computing, internet and data engineering expertise, strongly coupled with mathematics. Many industries and businesses have already built state-of-the-art data and information processing infrastructure for their operations. The Laboratory for High-Performance Data Signal Processors (DSP) & Data Engineering Research (HPDER) is a research and development laboratory that advances the theory and implementation of analytically oriented high-performance DSP, machine learning and data engineering methods to address big data and signal processing problems of various application domains, ranging from quantitative finance to data networks. Current projects include explainable machine learning methods and algorithmic trading for U.S. equities.