CARNEGIE MELLON . MACHINE LEARNING . PUBLIC POLICY

AI, Machine Learning, and Data Science for Real-World Impact

I work at the intersection of machine learning, public policy, and human decision-making—designing, building, evaluating, and governing AI systems that improve outcomes across health, human services, and government.

I collaborate with governments, nonprofits, and industry partners to move beyond prototypes and co-design systems that work in practice.

AI for Social Good

Designing Machine Learning and AI  systems that support high-stakes decisions.

AI Evaluation and Evidence

Rigorously measuring real-world outcomes, not just model accuracy.

Human-AI collaboration

Understanding how systems are actually used.

Responsible implementation

Translating fairness and governance into practice.

About me

I am a Distinguished Career Professor at Carnegie Mellon University, with appointments in the Machine Learning Department and Heinz College of Information Systems and Public Policy.

My work focuses on how AI systems can be designed, deployed, and governed to produce measurable improvements in real-world outcomes. I work across research, practice, and policy, with an emphasis on building systems that are not only technically sound but usable, accountable, and effective.

I have worked with governments, nonprofits, and mission-driven organizations on public health, behavioral health, criminal justice, homelessness prevention, and other policy problems where AI is often discussed but rarely evaluated well.

Rayid Ghani

AI, Machine Learning, and Data Science for Real-World Societal and Policy Impact

I work at the intersection of machine learning, public policy, and human decision-making—designing, building, evaluating, and governing AI systems that improve outcomes across health, human services, and government.

I collaborate with governments, nonprofits, and industry partners to move beyond prototypes and co-design systems that work in practice.

What I Work On

  • AI for public sector decision-making
  • Human-AI collaboration systems
  • Evaluation of AI systems, including randomized trials
  • AI Governance
  • Responsible and accountable AI in practice
  • Behavioral and policy interventions informed by machine learning

About Me

I am a Distinguished Career Professor at Carnegie Mellon University, with appointments in the Machine Learning Department and the Heinz College of Information Systems and Public Policy.

My work focuses on how AI systems can be designed, deployed, and governed to produce measurable improvements in real-world outcomes. I work across research, practice, and policy, with an emphasis on building systems that are technically sound, usable, accountable, and effective.

Selected Impact Areas

  • Public health
  • Human services
  • Criminal justice and public safety
  • Housing and homelessness prevention

Many ML and  AI projects fail to produce real impact. My work focuses on understanding why—and building systems that succeed.