Machine Intelligence and Data Science Lab
By leveraging advanced machine learning and data mining algorithms, we focus on the analysis, experimental evaluation, design and implementation of theory, logic and systems, with an emphasis on developing explainable, interpretable and theoretically sound tools to create new and innovative technology.
READ MOREWe are the MINDS lab at Morgan State University, led by Dr. Jamell Dacon. We focus on developing Trustworthy AI by prioritizing Safety & Security, Robustness & Realiability, Responsibility, Explicability, and Well-Being. Our research explores FATE in AI, ensuring fair, transparent and ethical frameworks guide AI systems. We apply Data Science for Social Good, harnessing data to tackle global challenges. Additionally, we pioneer AI+X, integrating AI across diverse fields to drive impactful innovation.
"Empowering innovation with AI you can trust, ensuring transparency, fairness, and reliability in every decision."
"Fostering Accountability, Transparency, and Ethics in AI to build a fairer and more responsible future."
"Leveraging data science to drive positive social impact and create solutions for pressing global challenges."
"Transforming interdisciplinary projects by seamlessly integrating AI with diverse fields to drive innovation and efficiency."
We harness AI and data science to uncover insights and drive innovation. Our research focuses on advanced algorithms that analyze complex data, empowering informed decisions and transforming industries.
Trustworthy AI requires governance and regulatory compliance throughout its AI lifecycle from initial ideation to design, development, and deployment of AI technologies. Our Trustworthy AI framework encompasses—explainability, robustness and reliability, while being respectful of privacy, safety & security, and social and environmental well-being.
AI algorithms often produce biased and non-interpretable results.Our aim is to facilitate computational techniques that are both innovative and responsible, while prioritizing issues of Fairness, Accountability, Transparency, and Ethics (FATE) as they relate to AI, ML, and NLP to adequately address complex societal implications of AI.
Data Science for Social Good seeks to answer fundamental questions of human well-being via machine learning, data science, and AI projects that prioritizes social impact. Our aim is to working closely with governments and nonprofits to tackle real-world problems in health, criminal justice, political science, and more.
Similiarly to Data Science for Social Good, AI+X consists of interdisciplinary projects across a diverse range of STEM and Non-STEM fields. Our aim is to conduct cross-disciplinary research in areas such as Education, Biology, Psychology, Linguistics, Social Science, Healthcare, and more.
Predictive analysis and forecasting empower organizations to anticipate trends, mitigate risks, and make data-driven decisions with confidence. By leveraging historical data and advanced algorithms, businesses can optimize strategies, improve outcomes, and stay ahead of the curve in an ever-changing world.
As AI continues to evolve, so must our approach to its ethical implications. We are committed to shaping a future where AI is developed and deployed responsibly—ensuring fairness, transparency, and accountability in every decision. Our research explores the evolving landscape of AI ethics to create systems that benefit all of society.
Have questions or want to collaborate on AI research? We're always excited to connect with fellow researchers, innovators, and organizations. Reach out to us, and let's explore the future of AI together.
Address: 1700 East Cold Spring Lane, Baltimore, MD 21251
Email: jamell.dacon@morgan.edu
Business Hours: Mon-Fri, 9 AM - 5 PM (EST)