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Annie Ulichney

Statistics PhD Student
UC Berkeley
annie_ulichney (at) berkeley.edu


I am a PhD Student in Statistics at UC Berkeley advised by Michael I. Jordan and Nika Haghtalab. My research focuses on developing responsible and reliable learning and decision-making algorithms by integrating tools from statistics and computer science.

I am grateful to have my work supported by the NSF Graduate Research Fellowship.

Previously, I earned a Bachelor of Science from Yale University with majors in Applied Mathematics and Mechanical Engineering.

Research

  1. The Statistical Fairness-Accuracy Frontier
    Alireza Fallah, Michael I. Jordan, Annie Ulichney
    NeurIPS Workshop: Reliable ML from Unreliable Data, 2025
    Foundations of Responsible Computing (FORC), 2026 [highlight track]
    ESIF Economics and AI+ML Meeting, 2026
    PDF

  2. Beyond the Training Distribution: Evaluating Predictions Under Distribution Shift and Selection Bias
    Annie Ulichney, Amanda Coston
    Preprint
    PDF

  3. Revisiting mean estimation over ℓp balls: Is the MLE optimal?
    Liviu Aolaritei, Michael I. Jordan, Reese Pathak, Annie Ulichney
    The Annals of Statistics, 2026
    PDF

  4. Fair Allocation in Dynamic Mechanism Design
    Alireza Fallah, Michael I. Jordan, Annie Ulichney
    NeurIPS 2024
    ICML Workshop: Humans, Algorithmic Decision-Making and Society, 2024
    PDF

  5. {BalanceProofs}: Maintainable Vector Commitments with Fast Aggregation
    Weijie Wang, Annie Ulichney, Charalampos Papamanthou
    32nd USENIX Security Symposium, 2023.
    PDF

  6. Automatic Infectious Disease Classification Analysis with Concept Discovery
    Elena Sizikova, Joshua Vendrow, Xu Cao, Rachel Grotheer, Jamie Haddock, Lara Kassab, Alona Kryshchenko, Thomas Merkh, RWMA Madushani, Kenny Moise, Annie Ulichney, Huy V Vo, Chuntian Wang, Megan Coffee, Kathryn Leonard, Deanna Needell
    Machine Learning for Health (ML4H) 2022 Extended Abstract.
    PDF Code

  7. Population-Based Hierarchical Non-Negative Matrix Factorization for Survey Data
    Xiaofu Ding, Xinyu Dong, Olivia McGough, Chenxin Shen, Annie Ulichney, Ruiyao Xu, William Swartworth, Jocelyn T Chi, Deanna Needell
    2022 IEEE/ACM International Conference on Big Data Computing, Applications and Technologies (BDCAT)
    PDF


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