Open source developer advocate and community manager with over ten years of experience in building infrastructure and AI communities, with a focus on:
Managing the Developer Advocacy team, including AI Developer Advocates and a Community Manager, supporting Modular's mission to reinvent how AI is developed and deployed with MAX, a next-generation developer platform, and Mojo, a new programming language designed for portable, high-performance computation on CPU and GPUs, including Nvidia accerators. Accomplishments include:
Lead company efforts to build a community around the open source project Label Studio. This work included managing a team of advocates and technical writers to develop content, support end-users, encourage developer contributions, foster strategic partnerships, and actively participate in industry events. Accomplishments included:
Developed a strategic program focused on expanding the matrix of supported software and hardware
platforms. Documented the front-end operators that could be imported into TVM from popular frameworks
such as TensorFlow, PyTorch, and ONNX, pairing them with TVM's hardware support matrix, assisting
hardware vendors in understanding how TVM could deploy ML models to their next-generation hardware.
Senior Developer Advocate for the open source Apache TVM project, a machine learning compiler framework dedicated to expanding the limits of machine learning by allowing users to deploy optimized ML models on any platform, from resource-constrained embedded systems to the latest generation of GPU and TPUs.
Planned and implemented an open source strategy designed to grow and support the user and developer communities. This work covered several dimensions of community management, including:
Community advocate and developer supporting the strategic goals of the OpenStack Foundation. Focused on expanding the reach and scope of the OpenStack community across two major areas: building OpenStack integrations into Kubernetes and expanding the OpenStack Foundation to include new projects.
Work in the Kubernetes community included:
Expanded the OpenStack (now OpenInfra) Foundation's project scope by managing projects focused on container orchestration. This included:
Assisted companies in the OpenStack ecosystem to productively engage as part of the community, both upstream as part of the development process and downstream, as they turned OpenStack code into products and services, with the overall goal of improving interoperability. Guided the launch of the OpenStack Powered Trademark Program, which used community-developed tests to guarantee interoperability between commercial OpenStack clouds. Defined required capabilities, identified tests to measure those capabilities, updated the tests to work in public and private cloud environments, and produced the interoperability standard guidelines. Administered the technical aspects of the OpenStack Powered program and served as Project Technical Lead (PTL) for the RefStack project, an interoperability test-harness and reporting tool.
Technical lead on the launch of the OpenStack Certified Administrator exam. Drawing from questions written by a community panel, edited the exam for consistency of content and voice, worked with third-party contractors to implement the exam, and did quality assurance on the initial launch and subsequent updates.
Worked as a software developer and community liaison between the Puppet and OpenStack communities. Was the Project Technical Lead (PTL) for the puppet-openstack modules. Was responsible for testing, release management, and project guidance, including developing shared tools and libraries to reduce code duplication in the puppet-openstack modules. Advocated for creating a new track at the OpenStack summits to give open source projects adjacent to the OpenStack community collaboration and development space. Supported the marketing team in promoting Puppet at industry events.
ACISS project technical lead. Responsible for acquiring and administering a $2 million research cloud computer for the College of Arts and Sciences at the University of Oregon. For over three years, ACISS supported over forty research projects. Taught courses in cloud computing and delivered several talks on using OpenStack for scientific computing at conferences, including OSCON. Expertise in OpenStack, scientific cloud computing, research workflows, and data warehousing. Activities also included supporting research in brain imaging for diagnosis and treatment of traumatic brain injury. Worked in C++, Java, Python, and Clojure.
Worked with a team of developers to produce a software interface for a magnetically guided catheter heart and vascular surgery platform. Responsible for:
Developed high-performance signal process algorithms for analyzing dense-array EEG data in C++ with MPI and OpenMP. Created a template-based MPI data library to serialize objects automatically and optimally. Implemented a test framework to validate the correctness of MPI instrumentation libraries, helping to guarantee that automated instrumentation libraries did not lose or corrupt data.
Implemented machine learning algorithms focusing on satisfiability-proof solvers, search, and ad-hoc routing heuristics. Worked on applying AI principles to network graph data structures. Developed primarily in C++, with prototyping using Matlab and Python.
Lead developer on the implementation of wavelet-based machine learning and classification algorithms. Using multi-dimensional wavelet decomposition on training sets, the algorithms generated fingerprints that were then used to identify features in medical images and mass spectroscopy samples. Implemented high-performance algorithms using C++, with compile-time optimizations written using template meta-programming.
Mathematician, with primary work in supporting the development of simulations in C++ and Matlab. Research areas included modeling electromagnetics, solving equations of motion, and stochastic signal processing.
Applied Math degree with an interdisciplinary collaboration in biomechanics. Focus on computational solutions of differential equations related to physical processes, fluid dynamics, and biomechanics. Masters Thesis: "A Model for Integrating the Internal and External Mechanics of a Soft-Bodied Anguilliform Swimmer"
Applied Math degree with a focus on optimization and control systems. Minors in Computer Science and Philosophy, with additional work on artificial intelligence and logic.