Jessica Sorrell

Assistant Professor
Department of Computer Science
Johns Hopkins University
Office: 6225 Smith Ave, SE311
jess@jhu.edu

Research. I'm broadly interested in the theoretical foundations of machine learning, particularly questions related to stability, ensembling, and reinforcement learning. I am also interested in lattice-based cryptography, with a focus on secure computation.

About me. I am an Assistant Professor in the Department of Computer Science at Johns Hopkins University with a secondary appointment in the Department of Applied Math and Statistics. I'm a member of the Data Science and AI (DSAI) Institute and the Mathematical Institute of Data Science (MINDS). Previously, I was a postdoc at the University of Pennsylvania, working with Aaron Roth and Michael Kearns. I completed my PhD in Computer Science at the University of California, San Diego, advised by Daniele Micciancio and Russell Impagliazzo. I did my undergrad in Applied Mathematics at the Rochester Institute of Technology.

Students

  • Anh Do
  • Rupkatha Hira (co-advised with Raman Arora)
  • Moshe Noivirt
  • Omobolade Odedoyin (co-advised with Joshua Vogelstein)

    • Teaching

  • Spring 2026. Modern Topics in Machine Learning Generalization (EN.601.776)
  • Fall 2025. Introduction to Algorithms (EN.601.433/633)
  • Spring 2025. Theory of Replicable Machine Learning (EN.601.774)

    • Publications and Manuscripts

    Model Agreement via Anchoring

    Eric Eaton, Surbhi Goel, Marcel Hussing, Michael Kearns, Aaron Roth, Sikata Sengupta, Jessica Sorrell
    [arXiv]

    Computationally Efficient Replicable Learning of Parities

    Moshe Noivirt, Jessica Sorrell, Eliad Tsfadia
    [arXiv]

    Replicable Reinforcement Learning with Linear Function Approximation

    Eric Eaton, Marcel Hussing, Michael Kearns, Aaron Roth, Sikata Sengupta, Jessica Sorrell
    ICLR 2026
    [arXiv]

    Sensitivity of Stability: Theoretical & Empirical Analysis of Replicability for Adaptive Data Selection in Transfer Learning

    Prabhav Singh, Jessica Sorrell
    [arXiv]

    Intersectional Fairness in Reinforcement Learning with Large State and Constraint Spaces

    Eric Eaton, Marcel Hussing, Michael Kearns, Aaron Roth, Sikata Sengupta, Jessica Sorrell
    ICML 2025
    [arXiv]

    Oracle Efficient Reinforcement Learning for Max-Value Ensembles

    Marcel Hussing, Michael Kearns, Aaron Roth, Sikata Sengupta, Jessica Sorrell
    NeurIPS 2024
    [arXiv]

    Replicable Reinforcement Learning

    Eric Eaton, Marcel Hussing, Michael Kearns, Jessica Sorrell
    NeurIPS 2023
    [arXiv]

    Stability is Stable: Connections between Replicability, Privacy, and Adaptive Generalization

    Mark Bun, Marco Gaboardi, Max Hopkins, Russell Impagliazzo, Rex Lei, Toniann Pitassi, Satchit Sivakumar, Jessica Sorrell
    STOC 2023
    [arXiv]

    Multicalibration as Boosting for Regression

    Ira Globus-Harris, Declan Harrison, Michael Kearns, Aaron Roth, Jessica Sorrell
    ICML 2023
    [arXiv]

    Securing Approximate Homomorphic Encryption Using Differential Privacy

    Baiyu Li, Daniele Micciancio, Mark Schultz, Jessica Sorrell
    Crypto 2022
    [ePrint]

    Reproducibility in Learning

    Russell Impagliazzo, Rex Lei, Toniann Pitassi, Jessica Sorrell
    STOC 2022
    [arXiv]

    Boosting in the Presence of Massart Noise

    Ilias Diakonikolas, Russell Impagliazzo, Daniel Kane, Rex Lei, Jessica Sorrell, Christos Tzamos
    COLT 2021
    [arXiv]

    Simpler Statistically Sender Private Oblivious Transfer from Ideals of Cyclotomic Integers

    Daniele Micciancio, Jessica Sorrell
    Asiacrypt 2020
    [eprint]

    Efficient, Noise-Tolerant, and Private Learning via Boosting

    Mark Bun, Marco Leandro Carmosino, Jessica Sorrell
    COLT 2020
    [arXiv]

    The Fiat-Shamir Zoo: Relating the Security of Different Signature Variants

    Matilda Backendal, Mihir Bellare, Jessica Sorrell, Jiahao Sun
    NordSec 2018
    [eprint]

    Ring Packing and Amortized FHEW Bootstrapping

    Daniele Micciancio, Jessica Sorrell
    ICALP 2018
    [eprint]

    Interests

    In my free time, I enjoy aerial silks and attempting to walk my cat.

    silks adventure-cat