Joe Near

Assistant Professor
University of Vermont
Office: E458 Innovation Hall
E-mail: jnear at uvm dot edu
[ CV ]

[ Books | Teaching | Students | Service | Publications ]

Research Interests

My research interests include data privacy (especially differential privacy), security (especially secure/verified computation), fairness, programming languages, and machine learning.


Programming Differential Privacy
A book about differential privacy, for programmers.
By Joseph P. Near and Chiké Abuah

Differential Privacy for Databases
By Joseph P. Near and Xi He


Graduate Students (advised or co-advised)



Program Committees

  • 2024: CCS, AISTATS
  • 2023: CCS, VLDB, TPDP
  • 2021: TPDP
  • 2020: TPDP, FCS


Recent Publications

  • OLYMPIA: A Simulation Framework for Evaluating the Concrete Scalability of Secure Aggregation Protocols
    Ivoline C. Ngong, Nicholas Gibson, Joseph P. Near
    In IEEE SaTML, 2024
  • Contextual Linear Types for Differential Privacy
    Matias Toro, David Darais, Chike Abuah, Joseph P. Near, Damian Arquez, Federico Olmedo, Eric Tanter
    ACM Transactions on Programming Languages and Systems, 2023
  • Solo: A Lightweight Static Analysis for Differential Privacy
    Chike Abuah, David Darais, Joseph P. Near
    In OOPSLA, 2022
  • Efficient Differentially Private Secure Aggregation for Federated Learning via Hardness of Learning with Errors
    Timothy Stevens, Christian Skalka, Christelle Vincent, John Ring, Samuel Clark, Joseph P. Near
    In USENIX Security, 2022
  • PrivGuard: Privacy Regulation Compliance Made Easier
    Lun Wang, Usmann Khan, Joseph P. Near, Qi Pang, Jithendaraa Subramanian, Neel Somani, Peng Gao, Andrew Low, and Dawn Song
    In USENIX Security, 2022
  • Zero Knowledge Static Program Analysis
    Zhiyong Fang, David Darais, Joseph P. Near, and Yupeng Zhang
    In Communications and Computer Security (CCS), 2021

E458 Innovation Hall, Burlington, VT