Amazon Web Services recently announced the selection of Howard University as one of five regional lead institutions for the AWS–Machine Learning University (AWS-MLU), enabling the creation of the Howard AI Network powered by AWS. Through the network, Howard will advance AI research, expand infrastructure and capacity, and help other colleges and universities build sustainable AI readiness across the Washington, D.C. metro area and beyond. 

The Howard-led network will increase access to cloud-enabled learning environments, enhance faculty development, and facilitate applied AI training — strengthening workforce readiness for students and communities and deploying open-source curricular resources designed to integrate AI and machine learning into undergraduate instruction and research. As a regional lead institution, Howard University will lead the design, coordination, and scaling of faculty-led AI and machine learning bootcamps, professional development workshops, and a regional student business case competition in collaboration with AWS-MLU.

Through this collaboration, we are expanding opportunities to equip faculty and students with industry-aligned tools needed to thrive in an AI-driven future.

Being selected as a regional lead institution reflects Howard University’s leadership in advancing artificial intelligence research, infrastructure, and talent development," said Dawn Williams, Ph.D., Howard University's interim provost and chief academic officer. "Through this collaboration, we are expanding opportunities to equip faculty and students with industry-aligned tools needed to thrive in an AI-driven future."

Through its Machine Learning University (MLU) Educators Consortium and Transformation Alliance, AWS is sponsoring initiatives that help faculty and senior administrators integrate industry-aligned AI and machine learning into instruction and research through hands-on technical training, open-access curricula, and peer collaboration. By promoting industry-aligned tech education, AWS is helping to cultivate the next generation of skilled technology leaders.

In 2026, Howard University will host two multi-day AI/ML bootcamps, intensive summer grant-writing workshops, individualized virtual mentoring, and a regional AWS business case competition to provide applied learning experiences in machine learning, deep learning, natural language processing, computer vision, and real-world problem-solving.

While the bootcamps and competition will primarily serve the Washington, D.C. metro area, the grant-writing initiative will be made available to 1000+ faculty nationwide who develop competitive proposals aligned with national AI priorities for the AWS-MLU program.

The network is led by Talitha Washington, Ph.D., executive director of Howard University's Center for Applied Data Science and Analytics, along with faculty co-leads Jeremy Blackstone, Ph.D., Legand Burge, Ph.D., and Harry Keeling, Ph.D., from the College of Engineering and Architecture, and Etoulia Salas-Burnett, M.S.Ed., from the Center for Digital Business. With combined expertise spanning artificial intelligence, data science, digital business, and STEM education, the team is uniquely positioned to align research, instruction, industry engagement, and workforce development under a unified vision for AI innovation at Howard University. 

By combining faculty development, infrastructure expansion, and workforce pathways, we are catalyzing the development of sustainable, scalable, AI-ready capacity at consortium institutions," said Washington.

Through its university-wide AI Initiative, including the Howard AI Advisory Council, the university is fostering a multidisciplinary, multifunctional approach to artificial intelligence research, infrastructure, and workforce development, preparing students to lead in an AI-enabled economy and tooling the university to embrace technology that can drive effectiveness. 

"Establishing five regional lead institutions for the AWS-MLU program marks a powerful step forward in scaling AI and machine learning education nationwide,” said Margie Vela, Ph.D., head of strategic initiatives for AWS-MLU. “By co-developing content with HBCUs and community colleges, we're uniting faculty expertise with industry insight to create learning experiences that are rigorous, relevant, and accessible. HBCUs continue to lead at the forefront of AI innovation, and community colleges serve as critical engines of workforce mobility. Together, they are not simply participating in the AI future — they are defining it."

Other regional lead institutions include Delaware State University, Alabama Agricultural and Mechanical University, City Colleges of Chicago, and Oklahoma City Community College.