Longmont, Colorado, United States
As a Senior Software Engineer at NVIDIA, I work on cuQuantum, a library of GPU accelerated primitives for quantum simulation. My goal is to expose the performance of NVIDIA's ecosystem to all quantum simulation frameworks and enable novel applications in the sciences. Previously, I was a Senior Solutions Architect at NVIDIA, working in higher education research at the intersection of AI and computational physics. I helped accelerate end-to-end pipelines leveraging multiple languages, such as Python, C, C++, and Fortran, and using RAPIDS and the NVIDIA HPC SDK. I also contributed to the design and development of solutions that serve the collective RAPIDS ecosystem for accelerating data science. I have strong skills in machine learning, Linux, and scalable design and performance, as well as a demonstrated history of working in the computing industry. I am passionate about advancing the frontiers of science and technology through GPU computing and quantum simulation.
As a part of the Math Libraries team, I work on GPU accelerated primitives for quantum system simulation. We are building highly optimized and efficient libraries and tools in cuQuantum to expose the performance of Nvidia's ecosystem to all quantum simulation frameworks.
I work in higher education research at the union of AI and computational physics. My focus is accelerating end-to-end pipelines leveraging multiple languages, like Python, C, C++, and Fortran, to facilitate novel applications in the sciences. I work primarily with RAPIDS and the NVIDIA HPC SDK.
I design and develop solutions that serve the collective RAPIDS ecosystem for accelerating end-to-end data science. To make the ecosystem itself better, I also help improve interoperability with the libraries and tools RAPIDS serves.