As the leader of D-Wave's benchmarking team I am broadly responsible for the internal evaluation of our quantum processing units (QPUs) after initial calibration. The task at hand is to take an analog superconducting quantum processor and distil its complex performance signature into clear, actionable metrics. This involves a combination of algorithm research and data science. I communicate performance measurements internally through membership on multiple core teams, and externally through technical exchanges and outward-facing publications. Our team also engages in greenfield research of hybrid quantum/classical algorithms.

As a senior algorithm researcher on of D-Wave's benchmarking team I managed a team of researchers and software developers assessing the performance of the latest quantum annealing chips to come out of fabrication. This involved research and development of classical optimization and sampling algorithms, design and development of a benchmarking framework and analytics suite, and administration of a database server.

As a researcher on D-Wave's benchmarking team I acted as an algorithm researcher, data scientist, and manager, assessing the performance of the latest quantum annealing chips to come out of fabrication. This involved research and development of classical optimization and sampling algorithms, design and development of a benchmarking framework and analytics suite, and administration of a database server.

In my position at Pulse Energy I led their team in the analysis of energy data that informs their Energy Information Systems, primarily those that help utilities engage their small and medium enterprise customers. Pulse Energy's analytics team develops prototype software for automated energy analysis and performs research into what insights can be gleaned from the application of machine learning techniques to data from hundreds of thousands of smart meters. I was also responsible for Pulse Energy's program evaluation, performing econometric/statistical analysis of energy efficiency programs to determine program-level energy savings.

Developed and analyzed agent-based models for spreading processes on social networks for an interdisciplinary collaboration. Developed a high-throughput engine in C# for feature-based analysis of combinatorial energy landscapes associated with optimization problems.

Analyzed data using Matlab and developed graphical models using C# and Infer.NET. Participated in an interdisciplinary research team investigating the nature of asthma and allergies.