Dr. Jamell Dacon is a (Tenure-Track) Assistant Professor in the Department of Computer Science at Morgan State University, where he serves as the Director & Lead Principal Investigator of the Machine Intelligence and Data Science (MINDS) Lab, and a faculty at the Center for Equitable Artificial Intelligence and Machine Learning Systems (CEAMLS). His work is dedicated to harnessing AI, ML and Data Science to address both error and outcome disparities (e.g., poor system performance or non-interpretable results) — the core philosophy of his work is to better understand the complex relationships between technology and society.
Dr. Dacon earned a Ph.D. and M.S. in Computer Science from Michigan State University in 2023 and 2020, respectively, supported by prestigious Michigan State University's University Enrichment Fellowship (UEF) and National Science Foundation GRFP fellowship under the guidance of Dr. Jiliang Tang. Prior to his doctoral studies, Dr. Dacon completed a B.S. in Mathematics and an A.S. in Computer Science at City University of New York—Medgar Evers College in 2018 amd 2017, respectively. In addition to his academic pursuits, Dr. Dacon actively contributes to the scholarly community as a Program Committee member and reviewer for top-tier international conferences and journals in machine learning and data science, including Nature, *ACL, AAAI, TheWebConf (previously WWW), ICML, IJCAI, CHI, KDD, LREC, etc.
Interdisciplinary AI Applications: Exploring AI's role in healthcare, epidemiology, computational biology, social sciences, and education, with a particular emphasis on addressing societal challenges such as health disparities and digital inclusion.
Social Good Applications: Investigating how AI can promote digital well-being and inclusive digital environments, particularly in the context of fostering ethical AI frameworks.
Fairness & Bias in AI: Advancing the development of interpretable and explainable AI models, focusing on applications in health equity, criminal justice, education, and social welfare policy.
Trustworthy AI demands robust governance and unwavering regulatory compliance across the entire AI lifecycle—from conceptualization to design, development, and deployment. This comprehensive framework ensures that AI technologies remain transparent, accountable, and secure. It prioritizes explainability, robustness, and reliability, while steadfastly upholding privacy, safety, and security. Furthermore, it is grounded in a deep commitment to social and environmental responsibility, ensuring that AI serves the greater good of society.
AI algorithms have long been criticized for producing biased and opaque results. In response, our mission is to pioneer computational techniques that are not only groundbreaking but also responsible. By placing paramount importance on issues of Fairness, Accountability, Transparency, and Ethics (FATE), it is crucial to ensure that AI, Machine Learning (ML), and Natural Language Processing (NLP) address the complex societal challenges they create. This approach is designed to foster trust, mitigate harm, and shape AI systems that truly benefit all.
Data Science for Social Good is dedicated to answering the most pressing questions of human well-being through the power of machine learning, data science, and AI. This initiative focuses on projects that prioritize social impact, working hand-in-hand with governments and nonprofit organizations to tackle real-world challenges across critical sectors such as health, criminal justice, political science, and more. The goal is to leverage data-driven insights to drive meaningful, lasting change for society at large.
Much like Data Science for Social Good, AI+X embraces interdisciplinary collaboration across a wide spectrum of fields—both within STEM and beyond. This initiative seeks to push the boundaries of knowledge by conducting pioneering research at the intersection of AI and diverse disciplines, including Education, Biology, Psychology, Linguistics, Social Science, Healthcare, and beyond. By blending AI with other domains, AI+X aims to unlock innovative solutions to complex global challenges, enhancing the impact of AI across every facet of human endeavor.
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Machine Intelligence and Data Science (MINDS) Lab
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