Pandemic Juba

Juba Ziani

Assistant Professor of Industrial and Systems Engineering at the Georgia Institute of Technology

Contact information

E-mail addresses
<first name>.<last name>@isye.gatech.edu
<first name>.<last name>@gmail.com
Office
343,
Groseclose building,
765 Ferst Dr NW,
Atlanta, GA.

About me

I am an Assistant Professor in the H. Milton Stewart School of Industrial and Systems Engineering (ISyE) at Georgia Tech. Previously I got: Here is a link to my Google Scholar profile and to my CV.

If you are interested in working with me, mentioned my name in your application instead of contacting me directly. However, I am unlikely to hire more Ph.D. students at this time.

Research Interests

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:

Awards and recognitions

Papers

Manuscripts:

Bayesian Strategic Classification
L. Cohen, S. Sharifi-Malvajerdi, K. Stangl, A. Vakilian, J. Ziani
Manuscript
Equilibria of Data Marketplaces with Privacy-Aware Sellers under Endogenous Privacy Costs
D. Sen, J. Wang, J. Ziani.
Manuscript
Personalized Differential Privacy for Ridge Regression
K. Acharya, F. Boenisch, R. Naidu, J. Ziani.
Manuscript
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.

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:

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
Causal Feature Discovery through Strategic Modification
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:

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

Service

Conference Organization

Outreach

Seminar Organization

Journal Reviews

Program Committees

External Reviewer

WINE 2015, TCC-b 2016, SAGT 2016, SODA 2017, UAI 2018, SODA 2019, STOC 2019, WINE 2019, SODA 2020, ITCS 2021, SODA 2022, ITCS 2022.

Grant Reviews and Panels

Other service

Teaching

Lecturer: