My current research looks at how to use tools from theoretical CS, particularly cryptography, to support accountability in data sharing systems, including statistical data analysis and machine learning. In undergrad, I did research in computational complexity theory, specifically within proof complexity and meta-complexity. Underlying my research is an abiding interest in TCS methodology, namely: what makes a mathematical abstraction "good," and what are useful methods for designing good abstractions?
Bell, Z. R., S. Goldwasser, M. P. Kim, J. Watson. “Certifying Private Probabilistic Mechanisms” Crypto (2024): https://eprint.iacr.org/2024/938.
Bell, Z. R. “Going Meta on the Minimum Circuit Size Problem: How Hard Is It to Show How Hard Showing Hardness Is?” HMC Senior Theses (2021), 250: https://scholarship.claremont.edu/hmc_theses/250.
Bell, Z. R. “Automating Regular or Ordered Resolution is NP-Hard.” Electronic Colloquium for Computational Complexity (2020), 105: https://eccc.weizmann.ac.il/report/2020/105/.
Bell, Z. R., J. Camero, K. Cho, T. Hyde, C. Lu, R. Miller, B. Thompson, E. Zhu. “Density of Periodic Points for Lattès Maps over Finite Fields.” The Journal of Number Theory (2022), Volume 238 p. 951-966: https://www.sciencedirect.com/science/article/abs/pii/S0022314X2100367X.