Work Experience

Hewlett Packard Enterprise

Working to develop Chapel, a modern parallel programming language to bring the power of parallel computing to the masses

Designed and implemented parallel sorting algorithms for GPUs in Chapel with performance on par with Nvidia's CUDA

Worked on core module stabilization efforts for release 2.0 of Chapel

Working to develop Arkouda, a distributed data science library for Python, written in Chapel

Improved CSV parsing performance by 50x in Arkouda

Engaged in community outreach efforts to promote Chapel and Arkouda

Collaborated with a team of 20 developers online using MS Teams, Slack, and Github

Department of Computer Science, University of Arizona

Mentored 4 freshmen CS students 1:1 to help them succeed in their major and find internships

Held weekly office hours and group meetings to interact with mentees and ecourage them to get involved on campus

Hewlett Packard Enterprise

Developed GPU support in the Chapel language and ported the Scalable HeterOgeneous Computing (SHOC) benchmark suite to Chapel

Improved performance by 2x compared to the original CUDA implementation and reduced code size by 3x

Worked on core module stabilization efforts

Hewlett Packard Enterprise

Added interfaces for Apache Arrow and Parquet libraries to the Chapel programming language

Pioneered the design for the high-level interface to reduce verbosity by 50x

The interface is used in Arkouda, a distributed data science library for Python, written in Chapel

Won "Best in class" award from a pool of 50 interns for the project

Department of Computer Science, University of Arizona

Ported Haskell code into C++ to increase performance by 2x for the CHiLL-I/E and EPWD projects

Worked on EBNF grammars and JavaCUP to get a performacne benchmark against other expert parsing tools

Collaborated with a team of 10 people from different technical, educational, and cultural backgrounds