Juba Ziani

E-mail addresses

<first name>.<last name>@isye.gatech.edu

<first initial><last name>3@gatech.edu

Office

343,
Groseclose building,
765 Ferst Dr NW,
Atlanta, GA.

I am an Assistant Professor in the H. Milton Stewart School of Industrial and Systems Engineering (ISyE) at Georgia Tech. Previously I got:

• a Warren Center Postdoctoral Fellowship in the Department of Computer and Information Science at UPenn.
• a PhD in Computer Science from the Computing and Mathematical Science Department at Caltech, where I was advised by Adam Wierman and Katrina Ligett. During my PhD:
  • I participated in the Data Privacy semester at the Simons Institute for the Theory of Computing in Spring 2019.
  • I visited Aaron Roth at University of Pennsylvania during Summer 2018.
  • I visited and interned at Microsoft Research New England in Spring and Summer 2017, where I worked with Yiling Chen, Nicole Immorlica, Brendan Lucier and Vasilis Syrgkanis.
• a Master's in Operations Research at Columbia University. During my master's, I also worked with Augustin Chaintreau and Maria Chudnovsky.

Here is a link to my Google Scholar profile.

Joining the lab

• I am currently looking for a postdoc to start in Spring or Fall 2025. If you are interested, please apply through one of the following programs: PPFP, ISyE named postdoctoral positions, and ARC

• If you are a Ph.D. student interested in working with me, mentioned my name in your application instead of contacting me directly.

My main interests lie at the intersection of Computer Science, Operations Research, and Economics. My primary focus is to study the new algorithmic, economic, and societal challenges posed by the generation of larger and larger amounts of data. In particular, I am interested in the following areas of research, and their intersections:

• Pricing and mechanism design for data markets;
• Differential Privacy, in particular in the context of data transactions;
• Algorithmic Fairness, with long-term and human-in-the-loop considerations;
• Game theory and machine learning, e.g. learning from games and strategic classification.

• NSF CAREER Award 2336236 in the CISE directorate, Human-Centered Computing program, 2024.
• 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: Spring 2023 CIOS Honor Roll
• Best Paper at SATML 2023
• IsyE DEI fellow, 2022-2023 cohort
• Student Recognition of Excellence in Teaching: Annual CIOS Award, 2022
• Student Recognition of Excellence in Teaching: Fall 2022 CIOS Honor Roll
• Student Recognition of Excellence in Teaching: Spring 2022 CIOS Honor Roll
• Bhansali Family Doctoral Prize in Computer Science for my dissertation on data, and its implications for markets and society
• Linde Graduate Fellowship at Caltech
• Inaugural PIMCO Graduate Fellowship at Caltech

Student Awards

• Diptangshu Sen: Georgia Tech ARC-ACO Fellowship, Spring 2025.

Manuscripts:

Fairness Issues and Mitigations in (Differentially Private) Socio-demographic Data Processes

J. Ko, J. Ziani, S. Das, M. Williams, F. Fioretto.

Manuscript

Differentially Private Data Release on Graphs: Inefficiencies and Unfairness

F. Fioretto, D. Sen, J. Ziani.

Manuscript

On Rider Strategic Behavior in Ride-Sharing Platforms

J. Mulay, D. Sen, J. Ziani.

Manuscript

Personalized Differential Privacy for Ridge Regression

K. Acharya, F. Boenisch, R. Naidu, J. Ziani.

Privacy Regulation and Protection workshop at ICLR 2024

Producers Equilibria and Dynamics in Engagement-Driven Recommender Systems

K. Acharya, V. Vangala, J. Wang, J. Ziani.

Manuscript

Randomized Quantization is All You Need for Differential Privacy in Federated Learning

Y. Yoon, Z. Hu, J. Ziani, and J. Abernethy.

Federated Learning and Analytics in Practice: Algorithms, Systems, Applications, and Opportunities Workshop at ICML 2023.

Incentivizing the Production of Equitable Datasets

A. Chaintreau, R. Maio, and J. Ziani

Algorithmic Fairness under the lens of Time (AFT) workshop at Neurips 2023.

Inference on Auctions with Weak Assumptions on Information

V. Syrgkanis, E. Tamer, and J. Ziani

Manuscript.

Book Chapters:

Differential Privacy: Overview and Fundamental Techniques

F. Fioretto, P. V. Hentenryck, and J. Ziani

Chapter 1 of “Differential Privacy in Artificial Intelligence: From Theory to Practice"

Journals:

The Privacy Paradox and Optimal Bias-Variance Trade-offs in Data Acquisition

G. Liao (co-first author), Y. Su (co-first author), J. Ziani, A. Wierman, J. Huang

Mathematics of Operations Research, 2023.

Conference and workshop versions below.

Pipeline Interventions

E.R. Arunachaleswaran, S. Kannan, A. Roth, and J. Ziani

Mathematics of Operations Research, 2022.

Conference and workshop versions below.

Third-party Data Providers Ruin Simple Mechanisms

Y. Cai, F. Echenique, H. Fu, K. Ligett, A. Wierman, and J. Ziani

Proceedings of the ACM on Measurement and Analysis of Computing Systems (POMACS), 2020

Conference version below

Joint Data Purchasing and Data Placement in a Geo-Distributed Data Market

X. Ren, P. London, J. Ziani, and A. Wierman (contribution order)

IEEE/ACM Transactions on Networking 2018 (ToN)

Cliques in the union of graphs

R. Aharoni, E. Berger, M. Chudnovsky, and J. Ziani

Journal of Combinatorial Theory, Series B, 2015

Conferences:

Algorithmic Collusion Without Threats

N. Collina, E.R. Arunachaleswaran, S. Kannan, A. Roth, J. Ziani.

Innovations in Theoretical Computer Science (ITCS), 2025.

Equilibria of Data Marketplaces with Privacy-Aware Sellers under Endogenous Privacy Costs

D. Sen, J. Wang, J. Ziani.

International Conference on Algorithmic Decision Theory (ADT), 2024.

Bayesian Strategic Classification

L. Cohen, S. Sharifi-Malvajerdi, K. Stangl, A. Vakilian, J. Ziani

Annual Conference on Neural Information Processing Systems (NeurIPS), 2024.

Oracle Efficient Algorithms for Groupwise Regret

K. Acharya, E. R. Arunachaleswaran, S. Kannan, A. Roth, J. Ziani

International Conference on Learning Representations (ICLR), 2024.

Optimization for Machine Learning (OPT) workshop at NeurIPS 2023.

Sequential Strategic Screening

L. Cohen, S. Sharifi-Malvajerdi, K. Stangl, A. Vakilian, J. Ziani

International Conference on Machine Learning (ICML), 2023.

Wealth Dynamics Over Generations: Analysis and Interventions

K. Acharya, E.R. Arunachaleswaran, S. Kannan, A. Roth, J. Ziani

IEEE Conference on Secure and Trustworthy Machine Learning (SATML), 2023.

Optimal Data Acquisition with Privacy-Aware Agents

R. Cummings, H. Elzayn, V. Gkatzelis, E. Pountourakis, J. Ziani

IEEE Conference on Secure and Trustworthy Machine Learning (SATML), 2023.

Best Paper Award.

Information Discrepancy in Strategic Learning

Y. Bechavod, C. Podimata, Z.S. Wu, J. Ziani

International Conference on Machine Learning (ICML), 2022

NeurIPS 2021 workshop on Strategic Machine Learning

The Privacy Paradox and Optimal Bias-Variance Trade-offs in Data Acquisition

G. Liao (co-first author), Y. Su (co-first author), J. Ziani, A. Wierman, J. Huang

ACM Conference on Economics and Computation (EC), 2021

Algorithms and Learning for Fair Portfolio Design

E. Diana, T. Dick, H. Elzayn, M. Kearns, A. Roth, Z. Schutzman, S. Sharifi-Malvajerdi, and J. Ziani

ACM Conference on Economics and Computation (EC), 2021

Gaming Helps! Learning from Strategic Interactions in Natural Dynamics

Y. Bechavod, K. Ligett, Z. S. Wu, and J. Ziani

The 24th International Conference on Artificial Intelligence and Statistics (AISTATS), 2021

To appear at the NeurIPS workshop on Strategic Machine Learning

Appeared at the Workshop on Incentives in Machine Learning (IML) at the 2020 International Conference on Machine Learning (ICML)

Pipeline Interventions

E.R. Arunachaleswaran, S. Kannan, A. Roth, and J. Ziani

Innovations in Theoretical Computer Science (ITCS), 2021.

Appeared as an oral presentation at the Workshop on Mechanism Design for Social Good (MD4SG), 2020.

MD4SG talk available here

Differentially Private Call Auctions and Market Impact

E. Diana, H. Elzayn, M. Kearns, A. Roth, S. Sharifi-Malvajerdi, and J. Ziani

ACM Conference on Economics and Computation (EC), 2020

Third-party Data Providers Ruin Simple Mechanisms

Y. Cai, F. Echenique, H. Fu, K. Ligett, A. Wierman, and J. Ziani

ACM SIGMETRICS Conference on Measurement and Modeling of Computer Systems, 2020

Talk available here

Journal version above

Downstream Effects of Affirmative Action

S. Kannan, A. Roth, and J.Ziani

ACM Conference on Fairness, Accountability, and Transparency (FAccT, formerly known as FAT*), 2019

Talk available here

Access to Population-Level Signaling as a Source of Inequality

N. Immorlica, K. Ligett, and J.Ziani

ACM Conference on Fairness, Accountability, and Transparency (FAccT, formerly known as FAT*), 2019

Talk available here

Optimal Data Acquisition for Statistical Estimation

Y. Chen, N. Immorlica, B. Lucier, V. Syrgkanis, and J. Ziani

ACM Conference on Economics and Computation (EC), 2018

Talk available here

Non-Exploitable Protocols for Repeated Cake Cutting

O. Tamuz, S. Vardi, and J. Ziani

AAAI Conference on Artificial Intelligence (AAAI), 2018

Accuracy for Sale: Aggregating Data with a Variance Constraint

R. Cummings, K. Ligett, A. Roth, Z. S. Wu, and J. Ziani

Innovations in Theoretical Computer Science (ITCS), 2015

Other:

We Found the Best Shuffled Deck, a.k.a. "This is Not the Best Paper, no, this is Just a Tribute"

Tenacious Academics

SIGBOVIK 2024 (https://sigbovik.org/2024/)

Efficiently Characterizing Games consistent with Perturbed Equilibrium Observations

V. Chandrasekaran, K. Ligett, and J. Ziani

Poster at the ACM Conference on Economics and Computation 2016 (EC)

Master's thesis at Caltech