In Episode 23, Patrick and Ciprian speak with Steve Reinhardt of Quantum Computing Inc.

The team discuss multidimensional graphs, optimization problems, and the strategy of exposing concepts in quantum computing to traditional users in familiar terms.

Steve Reinhardt joined QCI in May 2019 to lead QCI’s development of quantum-ready applications and tools, with a focus on delivering differentiated performance using quantum concepts on classical computers and on hybrids of quantum and classical. He has nearly 40 years of senior level experience in software and hardware engineering, development, and innovation.

 He has built award-winning systems that delivered new levels of computational performance and analytic capability, yet were usable via conceptually simple interfaces. He has focused on graph analytics since 2003, developing graph-analytic core software and using it to solve end-user problems particularly in cybersecurity.

 Prior to joining QCI, he was director of software tools and later director of customer applications at D-Wave Systems, the world’s first commercial supplier of quantum computers. At D-Wave, he led teams involved in developing quantum computing tools like qbsolv and worked with customers to map out problems for effective execution on D-Wave’s quantum-annealing-based quantum computer.

 At YarcData/Cray, he led the implementation of key graph-analytic functions for their Urika graph engine and applied them to early customer analytics. This resulted in the Pittsburgh Supercomputer Center and YarcData winning the 2013 HPCwire Editors’ Choice Award for Best Application of Big Data in High Performance Computing.

 Previously, he served as vice president of joint research for Interactive Supercomputing Corp. (ISC), where he secured funding for projects to implement advanced graph-analytic capabilities in Star-P (distributed MATLAB). After Microsoft acquired ISC, he served as principal architect in charge of architecture and development of its Knowledge Discovery Toolkit for distributed graph-analysis, intended for use by subject-matter experts who are not graph-analytic experts.

 He also served as chief engineer at Silicon Graphics, where he led the development of Altix, a scalable shared-memory Linux-based system that generated revenue of more than $600 million. He earlier served as the project director for Cray Research’s Cray T3E, the first production distributed-memory supercomputer, which generated more than $700 million in revenue for Cray.

 He earned his Bachelor of Science in Computer Science from Yale University and Master of Biological Sciences with a minor in Bioinformatics from the University of Minnesota.