Assistant Professor
Education
- Postdoctoral Fellow Warren Center for Network and Data Sciences (2021), University of Pennsylvania
- Ph.D. Computing and Mathematical Science (2019), California Institute of Technology
- M.S. Operations Research (2012), Columbia University
- B.S. Electrical Enginering and Computer Science (2011), Ecole Superieure D'Electricite
- M.S. Electrical Engineering and Computer Science (2013), Ecole Superieure d'Electricite
Expertise
- Game Theory
- Mechanism Design
- Markets for Data
- Differential Privacy
- Online Learning
- Responsible AI
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, and Aaron Roth. Juba completed his Ph.D. at Caltech in the Computing and Mathematical Sciences department, where he was advised by Katrina Ligett and Adam Wierman.
Research
My research lies at the intersection of Computer Science, Operations Research, and Economics. I 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. I am 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 societal considerations around AI, understanding the impact of AI tools on and ensuring that algorithms and automated decision-making tools do not harm society;
4. The performance of ML models in high-stake environments when strategic user responses and distribution shifts are commonplace.
Teaching
My teaching interests lie at the intersection of game theory, microeconomics, fundamental algorithms in AI and ML, and responsible AI. I teach these foundations both that the undergraduate and graduate level, and integrate theory and practical applications to equip students with analytical tools for decision making in real-life contexts.
Awards and Honors
- INFORMS MIF Early Career Award
- Student Recognition of Excellence in Teaching: Spring 2025 CIOS Honor Roll
- NSF CAREER Award 2336236
- Student Recognition of Excellence in Teaching: Spring 2023 CIOS Honor Roll
- Student Recognition of Excellence in Teaching: Annual CIOS Award, 2023
- Student Recognition of Excellence in Teaching: Fall 2023 CIOS Honor Roll
- Student Recognition of Excellence in Teaching: Fall 2022 CIOS Honor Roll
- Student Recognition of Excellence in Teaching: Spring 2022 CIOS Honor Roll
- Student Recognition of Excellence in Teaching: Annual CIOS Award, 2022
Representative Publications
*Last-iterate Convergence for Symmetric, General-sum, 2×2 Games Under The Exponential Weights Dynamic
G. Wang, K. Acharya, L. Lakshmikanthan, J. Ziani, V. Muthukumar, 2025.
International Conference on Algorithmic Learning Theory (ALT), 2026.
*Incentivizing Desirable Effort Profiles in Strategic Classification: The Role of Causality and Uncertainty
V. Efthymiou, C. Podimata, D. Sen, J. Ziani, 2025.
The Thirty-Ninth Annual Conference on Neural Information Processing Systems (NeurIPS), 2025.
*The Disparate Effects of Partial Information in Bayesian Strategic Learning
S. Avasalara, S. Wang, J. Ziani.
The 8th AAAI/ACM Conference on AI, Ethics, and Society (AIES), 2025.
*Differentially Private Data Release on Graphs: Inefficiencies and Unfairness
F. Fioretto, D. Sen, J. Ziani.
The 28th International Conference on Artificial Intelligence and Statistics (AISTATS), 2025.
*The Cost of Balanced Training-Data Production in an Online Data Market
A. Chaintreau, R. Maio, and J. Ziani
The International World Wide Web Conference (TheWebConf) 2025.