I specialize in artificial intelligence, big data, and natural language processing. My professional interest is in the management and application of artificial intelligence to responsibly improve policymaking and government effectiveness.
I am passionate about improving policymaking by harnessing the power of data science and artificial intelligence. As a data science manager at the Federal Reserve Board, I lead a team with a diverse project workload that includes research, policy, and operational data and software projects. My personal portfolio includes technology leadership, research efforts, technical expertise, and teaching experience. My research includes work on international trade, graph neural networks, natural language processing, and more. I am experienced with technologies such as PyTorch, TensorFlow, Hadoop, Spark, Impala, spaCy, NLTK, R, and Python.
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MS in Data Science and Analytics
Georgetown University
BA in Chemistry, Economics, and Mathematics
Vanderbilt University
As the Federal Reserve Board’s inaugural Chief AI Officer, I am responsible for all aspects of the Board’s AI use:
I am the inaugural manager for the Data Science and Application Development (DSAD) group in the International Finance Division. The team serves as in-house experts in application design, UX design, robotic process automation, data science, big data, and artificial intelligence for research, policy, and operational needs at the Federal Reserve Board.
I lead a team of 5 full-time data scientists and application developers who manage application and data products that serve hundreds of internal staff. We contribute to the Board’s cloud adoption, artificial intelligence maturity development, and maintain several important climate, textual, and trade databases.
In the Fall 2022 and Spring 2023 semesters, I served as the Instructor of Record for the Howard University course run by the Federal Reserve Board on statistical programming and economic literacy.
Responsibilities included:
Accomplishments:
Accomplishments:
Developed skills in data science, machine learning, and deep learning.
Majors in Chemistry, Economics, and Mathematics