As Director of AI for Woebot Health, I led teams responsible for building ML-powered features and workflows that drove elements of the Woebot app experience meant to deepen connection with users through enhanced language understanding. - Successfully designed, tested, and delivered several NLP-based features into the Woebot application, resulting in improved engagement metrics and higher endorsement of language understanding- Modernized the data collection & annotation, model selection, model training & deployment processes, reducing time to deployment and increasing uptime for Woebot’s machine learning model services- Grew the AI engineering team from 2 to 5 within first 9 months, and successfully navigated multiple reorganizations to optimize organizational dynamics- Advanced Woebot’s AI capabilities by successfully designing, testing, and delivering the first generative version of the Woebot application, which was tested in a randomized, double-blind, controlled clinical trial (BUILD study, n=160)- Spearheaded the adoption of scrum methodology for roadmap & iteration management on the AI team, and advised teams for broader adoption across product & engineering departments- Delivered regulatory-grade documentation and instituted process enhancements around ML development, testing, and monitoring to align with FDA guidelines given corporate strategy to pursue regulatory clearance

2021:My leadership focus is overseeing multiple teams and missions within the space of Watson Core, Watson NLP, and the Watson end-to-end developer experience. My aim is to enable leaders over some of IBM's most strategic AI initiatives to do their absolute best work, and to maintain the highest levels of employee engagement, as well as technical eminence, throughout my organization. My teams work on:- the Watson NLP tech stack, as well as the flagship NLP offering that showcases it, IBM's Watson Natural Language Understanding; - core development of reusable AI components and libraries applicable for embedding in any number of software offerings at IBM; - a variety of assets designed to make the end-to-end experience of developing with cloud-based Watson APIs a delightful one for our end-users (e.g., SDKs in multiple programming languages)2019-2020:I worked with the R&D teams that own the Watson Speech, Language, and Vision products in the Watson AI portfolio. Focusing on building cross-functional teams, enabling hybrid multi-cloud AI solutions for our clients, and navigating my team members' career growth in the AI space.

I manage the engineering teams behind Watson AI's flagship NLP offerings in Public and Private cloud environments.

Working in the IBM Watson division, helping to bring AI to the forefront. Striving to provide amazing solutions in healthcare, finance, retail, and the public sector.

C++ software engineer; big data, machine learning, computer vision, artificial intelligence; GPU computing, Amazon Web Services, CUDA programming, high performance, scalable systems.

Supervising new undergraduate research assistants, I worked on multiple projects related to studies of the Higgs boson with ATLAS data. Generation of physics event using the Pythia8 Monte Carlo generator, data analysis of 2012 LHC collision data.

Software development of ROOT-based framework designed for new physics searches with LHC data. Data management, selection and filtering, visualization, statistical interpretation of LHC data. Background estimation using data-driven approaches. Database administration, developing Python interfaces for Oracle database with cx_Oracle.

Supervised 50 sections of graduate-instructed introductory laboratories. Pre-semester training and early semester assessment of new instructors. Development and maintenance of course materials, curriculum, online quizzes. Collusion detection of undergraduate lab write-ups. Editing of lab manuals.

Instructed 2 sections of 20 students each, for two semesters. Class format: brief lecture followed by supervision of student-run experiments. Extensive use and instruction of Excel for recording and manipulating experimental data. Quick feedback provided for students, along with weekly office hours for help with general introductory physics.

Working with incoming crews of 8-12 young Scouts and their advisors, prepared novice and experienced backpackers with necessary resources to begin a 10-day trek in the New Mexico backcountry. Guided each crew's trek for the first two nights, teaching backcountry practices such as Leave No Trace ethics.