About

Juba Ziani is an Assistant Professor in the H. Milton Stewart School of Industrial and Systems Engineering. Prior to this, Juba was a Warren Center Postdoctoral Fellow at the University of Pennsylvania, hosted by Sampath Kannan, Michael Kearns, Aaron Roth, and Rakesh Vohra. Juba completed his Phd at Caltech in the Computing and Mathematical Sciences department, where he was advised by Katrina Ligett and Adam Wierman.

Juba use tools from learning theory, game theory, and optimization to address technical and societal challenges arising from the rise of AI, ML, and data-driven decision making. He is particularly interested in: 
1. The economics of data, in a world of exchanging data has become crucial to building powerful AI tools;
2. The privacy considerations from using larger and larger amounts of personal and sensitive data, with a focus on Differential Privacy; 
3. The fairness considerations around AI, ensuring that algorithms and automated decision-making tools do not replicate human biases or introduce new biases;
4. The performance of ML models in high-stake environments when strategic user responses and distribution shifts are commonplace.