Scholar
Jordan Awan
Google Scholar ID: fhCtCW8AAAAJ
Assistant Professor, University of Pittsburgh
Citations & Impact
Citations
563
H-index
15
i10-index
19
Publications
20
Co-authors
32
list available
Contact
Publications
Resume (English only)
Academic Achievements
- - Published papers:
- - "Differentially Private Bootstrap: New Privacy Analysis and Inference Strategies" in JMLR
- - "Best Linear Unbiased Estimate from Privatized Contingency Tables" in JMLR
- - "Particle Filter for Bayesian Inference on Privatized Data" in ICML
- - Preprints:
- - "Incomplete U-Statistics of Equireplicate Designs: Berry–Esseen Bound and Efficient Construction"
- - "Optimal Debiased Inference on Privatized Data via Indirect Estimation and Parametric Bootstrap"
- - "Optimal Survey Design for Private Mean Estimation"
- - "dapper: Data Augmentation for Private Posterior Estimation in R"
- - "Formal Privacy Guarantees with Invariant Statistics"
- - "Differentially Private Covariate Balancing Causal Inference"
- - Other academic achievements:
- - "Simulation-based Finite-sample Inference for Privatized Data" in Journal of the American Statistical Association
- - "Differentially Private Topological Data Analysis" in Journal of Machine Learning Research
- - "Canonical Noise and Private Hypothesis Tests with Applications to Difference of Proportions Testing" in Annals of Statistics
- - "Log-Concave and Multivariate Canonical Noise Distributions for Differential Privacy" in Advances in Neural Information Processing Systems 36
- - "Data Augmentation MCMC for Bayesian Inference from Privatized Data" in Advances in Neural Information Processing Systems 36
- - "Use of a Vortex Whistle" (incomplete)
Research Experience
- - Assistant Professor of Statistics at University of Pittsburgh, 2025-present
- - Assistant Professor of Statistics at Purdue University, 2020-2025
- - Differential privacy consultant for the federal non-profit, MITRE
Education
- - Ph.D. in Statistics from Penn State University, 2020, advised by Dr. Aleksandra Slavkovic and Dr. Matthew Reimherr
- - M.A. in Mathematics from Brandeis University, 2016, advised by Dr. Olivier Bernardi
- - B.S. in Mathematics from Clarion University, 2014
Background
- - Primary research interest is in data privacy, particularly in the framework of differential privacy, focusing on statistical inference, designing privacy-aware algorithms, and foundations of data privacy.
- - Works as an applied statistician on problems related to diagnosing and treating voice disorders, and developing low-cost spirometry methods.
Miscellany
- - Personal interests: Discrete mathematics problems, such as graph theory, matroid theory, and discrete geometries
