Center for Equitable Artificial Intelligence and Machine Learning Systems
Research
CEAMLS research combines advanced computing with human-centered ethics to shape a more just AI future.
We are driven by deceptively simple yet profoundly important questions:
Could an AI model cause harm? Could it reinforce social hierarchies that deny equitable opportunity?
At CEAMLS, we don’t just study AI — we interrogate it. Our interdisciplinary research spans data science, philosophy, engineering, and education to investigate the risks and remedies of algorithmic systems.
We work to formalize best practices for data preparation, model training, deployment, and evaluation — building scalable frameworks that promote fairness, transparency, and accountability. This includes rigorous testing protocols that identify and reduce algorithmic bias before AI models reach the public.
Our research focuses on:
-
Best Practices & Standards
-
AI Transparency
-
Objectivity Optimization
-
Bias Detection & Remediation
-
Testing & Validation
-
AI Misapplication
-
Model Stress Testing
Explore:
Get Matched to a Research Opportunity
Join our talent pool and we'll connect you with suitable projects as opportunities arise.