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Center for Equitable Artificial Intelligence and Machine Learning Systems

History

Founding & Vision- 2022
  • CEAMLS officially launched at Morgan State University
    Backed by $3.1M state funding, $2M legislative support, and a $9M DoD research grant

Program Launch & Research Growth- 2023

  • SARI (Summer AI Research Institute) – Year 1
    Launch of 6-week equity-focused AI summer research program

  • Monthly AI Workshops (K–12)
    Community engagement events start at Enoch Pratt and Baltimore City Public Schools

  • Partnerships

    • Consumer Reports → Early warning system for product safety

    • Maryland Department of IT → CEAMLS joins AI Advisory Committee

  • Award-Winning Innovation
    Autonomous Wheelchair Project wins 1st Prize at Morgan Tech Fest

  • Patent Filed
    "Automated Wheelchair Specifications and Architecture" – Kofi Nyarko

Public Spotlight & National Events- 2024

  • National Symposium on Equitable AI (N‑SEA)
    Conference on AI fairness, attended by researchers & community leaders

  • SARI – Year 2
    Expanded cohort, poster sessions, and workshops

  • AI in the Press

    • 🎙 Dubai’s Agenda Podcast – Voice cloning

    • 📺 WMAR News – CEAMLS wheelchair demo

    • 📰 Scripps Network – Speech-impairment AI solutions

  • New Grants Awarded

    • EQUATE (NIST) → $240,644

    • Google Grant → $90,000

  • New Patents Filed

    • “Digital Cognitive Debiasing” – Gabriella Waters

    • “Site Sense” – Gabriella Waters

Research & Strategic Visibility- 2025

  • SARI – Year 3
    Projects in algorithmic transparency, image fairness, and inclusive design

  • AIM-LIFT Lecture Series
    Dr. Eric Scott: “Accountable AI in Health Care”

  • CodeBears Research Team
    Pre-college students mentored on ML projects

  • 2nd National Symposium (N‑SEA)
    Theme: "AI in Practice: Impacts, Risks, and Opportunities"

  • Major Publications (2025)

    • Artificial Intelligence Review

    • Scientific Reports

    • MDPI Algorithms

Goals

  1. Conduct theoretical and applied socially responsible AI research aimed at solving complex real-world problems while creating trustworthy intelligent systems.
  2. Address algorithmic bias in AI research and educate the public on the possible disproportional impact to health, prosperity, and society.
  3. Increase the diversity of thought in the field of AI by attracting significantly more underrepresented computer scientists and engineers.
  4. Collaborate with educational, nonprofit, government, and industrial organizations to study, document, and mitigate the effects of algorithmic bias.