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Dr. Talitha Washington
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Staff

Talitha Washington, Ph.D.

Executive Director, Center for Applied Data Science and Analytics

  • Office of the Provost
  • Executive Director
    Center for Applied Data Science and Analytics
  • Sean McCleese Endowed Chair
    Office of the Provost
  • Professor
    Mathematics
  • AI Advisory Council Co-Chair
    AI Advisory Council
  • Data Science Program
  • Capstone Institute

Biography

Talitha Washington, Ph.D., is the Executive Director of the Center for Applied Data Science & Analytics (CADSA), Sean McCleese Endowed Chair, and Professor of Mathematics at Howard University. She also serves as Co-Chair of the President's AI Advisory Council, which guides the University's AI strategy across research, academic, and enterprise initiatives. Her work spans applied mathematics, dynamical systems, data science, artificial intelligence, and STEM education, with a focus on expanding opportunity, advancing innovation, and strengthening the impact of research and education.

Washington serves as Principal Investigator of the U.S. National Science Foundation–funded Research Coordination Network on Assessing and Predicting Job Outcomes in AI, a national initiative focused on building a coordinated understanding of AI jobs, skills, and credentials to strengthen the nation’s AI workforce ecosystem. She is Past-President of the Association for Women in Mathematics and a former member of the Census Scientific Advisory Committee of the U.S. Census Bureau. She has led and contributed to major externally funded initiatives in data science, AI, workforce development, and STEM education.

An accomplished scholar and advocate for excellence, Washington has been recognized with numerous honors. She was elected to Phi Beta Kappa and Sigma Xi, as well as mathematics honor societies Kappa Mu Epsilon and Pi Mu Epsilon. Her accolades include the 2019 BEYA STEM Innovator Award, the 2019 Outstanding Faculty Award from Howard University, and the 2020 NSF Director’s Award for Superior Accomplishment. She is a Fellow of the African Scientific Institute (ASI), the American Mathematical Society (AMS), the Association for Women in Mathematics (AWM), and the American Association for the Advancement of Science (AAAS).

Washington was a VIGRE Research Associate in the Department of Mathematics at Duke University and served as the inaugural Director of the Atlanta University Center (AUC) Data Science Initiative and the NSF National Data Science Alliance. Her academic appointments include assistant professorships at The College of New Rochelle and the University of Evansville, and a full professorship at Clark Atlanta University. As a former Program Director at the National Science Foundation (NSF), she worked in the Convergence Accelerator within the Directorate for Technology, Innovation, and Partnerships (TIP) and in the Division of Undergraduate Education (DUE), where she led the development of NSF's first Hispanic-Serving Institutions Program.

After graduating early from Benjamin Bosse High School in Evansville, Indiana, she studied abroad in Juan Viñas, Costa Rica. She earned her undergraduate degree in mathematics from Spelman College, including a semester abroad at the Universidad Autónoma de Guadalajara in Mexico. She later completed her master’s and doctoral degrees in mathematics at the University of Connecticut, which also awarded her an honorary Doctor of Science. She also completed Carnegie Mellon University’s Chief Data and AI Officer Certificate Program.

Across her scholarship, leadership, and service, Washington remains committed to expanding opportunity, advancing innovation, and strengthening the impact of research, education, and emerging technologies.

Education & Expertise

Education

Certificate Program

Chief Data and AI Officer (CDAIO)
Carnegie Mellon University
2026

Doctor of Science (D.Sc.)

Honorary
University of Connecticut
2023

Doctor of Philosophy (Ph.D.)

Mathematics
University of Connecticut
2001

Master of Science (M.S.)

Mathematics
University of Connecticut
1998

Bachelor of Science (B.S.)

Mathematics
Spelman College
1996

Areas of Expertise

Artificial Intelligence

Data Science

Mathematics

Accomplishments

Accomplishments

Fellow, American Mathematical Society (AMS)

Fellow, Association for Women in Mathematics (AWM)

Fellow, American Association for the Advancement of Science (AAAS)

Past-President, Association for Women in Mathematics

Featured News

Publications and Presentations

Publications and Presentations

Dr. Washington’s Notes on AI

A LinkedIn Newsletter on how AI and data are transforming higher education across teaching, research, workforce development, and institutional strategy.

Leveraging Multi-institutional Collaborations to Unlock Impactful Undergraduate Data Science Programs

This article details how a multi-institutional collaboration among Historically Black Colleges and Universities (HBCUs) established a coordinated framework to launch rigorous data science academic programs. Through a cohort-based faculty model, the project successfully developed the curricula and high-impact strategies across HBCUs to scale the national data science workforce.

Curriculum Guidelines for Undergraduate Programs in Data Science

These Curriculum Guidelines provide a foundational framework for institutions to develop rigorous, adaptable data science curricula that bridge the gap between academic training and industry demands.

Developing Ethics and Equity Principles, Terms, and Engagement Tools to Advance Health Equity and Researcher Diversity in AI and Machine Learning: Modified Delphi Approach

This paper details the framework by the Artificial Intelligence/Machine Learning Consortium to Advance Health Equity and Researcher Diversity (AIM-AHEAD) Ethics and Equity Workgroup (EEWG) for integrating ethics and fairness into biomedical AI, focusing on mitigating algorithmic bias and cultivating the research workforce.

Nonstandard finite difference scheme for a Tacoma Narrows Bridge model

This paper develops dynamically consistent nonstandard finite difference (NSFD) schemes that accurately simulate nonlinear bridge oscillations, successfully overcoming the computational instabilities of standard numerical methods.

Construction and analysis of a discrete heat equation using dynamic consistency: The meso-scale limit

This paper develops a dynamically consistent nonstandard finite difference scheme for the heat equation that preserves physical properties while mathematically bridging microscopic particle movement and macroscopic thermal conduction.

A mathematical model for LH release in response to continuous and pulsatile exposure of gonadotrophs to GnRH

This paper applies differential equations to investigate the release of Luteinizing Hormone (LH) in response to varying patterns of Gonadotropin-releasing hormone (GnRH), providing a predictive tool for LH release patterns.

Recent Articles

Multimedia

Executive Mosaic | Howard University's Dr. Talitha Washington Debriefs Post 2025 AI Summit

In this AI Summit interview, Dr. Talitha Washington discusses the strategic integration of AI into the workforce. She emphasizes the roles of data security, prompt engineering, and cross-sector partnerships in driving innovation. Ultimately, she highlights how ethical AI application enhances human performance and solves complex societal challenges.

Mastercard News | Cultivating the Talent Pipeline for the Digital Future

Dr. Talitha Washington shares how her work with Historically Black Colleges and Universities (HBCUs) is creating robust pathways for students to enter the AI-driven workforce through new majors, minors, and national research alliances. She said, "We need all hands on deck...to really move the needle and ensure that every student has access to data science and AI because it makes it better for everyone."

LifeBeat Podcast | Harnessing AI for Better Health and Smarter Living

In this LifeBeat Podcast interview, Dr. Talitha Washington explores how AI and data science can be harnessed to improve community health and drive social impact through ethical stewardship. She emphasizes that technology should augment human performance rather than replace it, requiring a foundation of curiosity and critical thinking to ensure responsible innovation.