Join us in welcoming the 6 newest members of the xD team's Emerging Technology Fellowship (ETF)!
These visionary technologists and innovators bring highly sought-after skills to the Census Bureau, including artificial intelligence (AI), machine learning, data science, data engineering, and project management with specializations in cryptography, privacy, theory of mind, algorithmic transparency, algorithmic bias mitigation, and cybersecurity.
“We couldn’t be more excited about this amazing group – not only as impressive individuals but as a collective. I can’t wait to see all that they’ll do for the public good.” - Kate McCall-Kiley, xD Lead
The Emerging Tech Fellowship is a key component of xD’s mission to advance the delivery of data-driven services through new and transformative technologies. The 2023 cohort will work on mission-critical technology challenges at the Census Bureau with the Geography Division, Economics Directorate, Research & Methodology Directorate, and the Deputy Director’s Office as well as the Bureau of Economic Analysis and other partner agencies such as the National Institute of Standards and Technology and the General Services Administration.
“Our goal is to incubate and accelerate key innovations powered by emerging technologies. This outstanding group of individuals will help us better understand the landscape of opportunity and unlock the next generation of innovation at the Census Bureau.” - Luke Keller, Chief Innovation Officer
If you’d like to learn more about this year’s projects or discuss future projects, you can reach team xD at email@example.com. To learn more about xD and the Emerging Technology Fellowship, please visit https://www.xd.gov.
Meet the 2023 Emerging Technology Fellows:
Anna Vasylytsya (she/her) is excited to start as an Emerging Technology Fellow at the Census Bureau. She is excited about data-driven decision-making, being able to combine her passions for technology, policy, and data. Prior to working with the Census Bureau, Anna was a Senior Data Scientist at the National Associations of REALTORS (NAR), one of the largest trade associations in the US. At NAR, she produced data analyses and delivered insights, built dashboards, and worked on improving data quality on a broad range of topics that impact Realtors. Anna started her career as a federal contractor at the Department of State and she is excited to return to public service.
Anna graduated from the Georgetown University McCourt School of Public Policy with a Master of Public Policy degree with a focus on econometrics, causal inference, and quantitative research. She also holds a dual Bachelor of Arts in International Relations and Environmental Studies from American University.
Curtis Mitchell (he/him) is excited to be an Emerging Technology Fellow on the xD team. His career has gone through several transitions, including being a data analyst at an energy consulting firm before working at several data analysis and machine learning startups as a software engineer. Before joining xD, he worked with multiple teams at NASA’s Ames Research Center on a research platform to integrate drones and air taxis into the air traffic control system.
A native Texan, Curtis has called the San Francisco Bay Area home for over 10 years. Outside of work he regularly contributes to open-source software projects such as OpenMined’s PySyft.
Diamond Nwankwo (she/her) has a proven data-based track record with 10 years of experience in data engineering and quality assurance/control field within aerospace manufacturing. Diamond worked as a Senior Data Engineer; where she was responsible for designing, building, and maintaining data pipelines and systems. Prior to that, she worked in Solar Renewable Energy as a Data Engineer where she was the lead on an irradiance ETL pipeline development and reporting data quality.
Before she transitioned into data engineering, she worked within Aerospace Manufacturing as a Quality and Process Improvement Engineer, where she led the SMART Manufacturing initiatives and led the transition from AS 9100 Rev C to Rev D as Lead Auditor. Diamond earned a BS in Industrial Engineering from Missouri University of Science and Technology, formerly known as the University of Missouri - Rolla, and an MS in Quality Management from Eastern Michigan University. Diamond’s article Data Quality Management for Industry 4.0: A Survey was published in the America Society of Quality’s Software Quality Professionals Journal.
Ian Munoz (he/him) started his career at a National Science Foundation-funded environmental research center at University of Maryland. Later he worked for bioinformatics at Oregon State University. He then spent time working for FinTech startups as a DevOps engineer. His most recent private sector employer was Amazon Web Services (AWS) where he worked as a Sr. Infrastructure Architect.
He is coming to the Census Bureau from the Center for Medicare and Medicaid via the U.S. Digital Service where he has been supporting their payment systems modernization effort as a Digital Services Expert. He is interested in privacy enhancing tech, federated data, and innovative technology.
Mike Walton (he/him) is a researcher, technologist, and writer endlessly fascinated by the study of cognition and intelligent systems. His research aims to synthesize ideas from multi-agent reinforcement learning, game theory, and participatory design to address socially impactful cooperation and coordination problems.
Mike’s research has been supported by the Office of Naval Research (ONR), the Defense Advanced Research Projects Agency (DARPA), and The Naval Information Warfare Center (NIWC) In-house Laboratory Independent Research Program. His work has been presented at various conferences and workshops, including NeurIPS (Conference on Neural Information Processing Systems), Association for the Advancement of Artificial Intelligence, International Joint Conferences on Artificial Intelligence, and Queer in AI. Mike is a passionate advocate for STEM educational equity and environmental conservation.
Tomo Lazovich (they/them) is a Senior Research Scientist at the Institute for Experiential AI at Northeastern University. Prior to joining the institute in 2023, they were a senior machine learning researcher at Twitter, developing a suite of metrics to measure inequality in outcomes for the ML Ethics, Transparency, and Accountability (META) team.
Tomo has a significant amount of experience as an interdisciplinary researcher and machine learning practitioner, with defined expertise in building technical solutions to complex problems from the ground up. Their work currently focuses on understanding the impacts of algorithmic systems, developing novel technical approaches that better account for model impacts, and creating more just and equitable socio-technical infrastructures. They are also dedicated to bridging the gap between academia, industry practitioners, and policymakers to better operationalize responsible machine learning practice.
Tomo holds a Ph.D. in Physics from Harvard University, where their thesis was based on the discovery and subsequent study of the Higgs Boson at the Large Hadron Collider in Switzerland. They are also currently a part-time JD candidate at Northeastern University, hoping to fuse their technical knowledge with legal expertise to build practical regulatory solutions for AI.