ASL LabStanford University
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Robin Brown

rabrown1 _at_ stanford _dot_ edu

Robin Brown

Alumni · now at OpenAI

Robin is a second-year PhD student at the Institute for Computational and Mathematical engineering. Prior to coming to Stanford, she attended the California Institute of Technology where she received her B.S. in Mathematics; Business, Economics, and Managements, and Control and Dynamical Systems (minor). Her current research focuses on scalable and efficient algorithms for large-scale multi-agent systems.

Publications

9 publications · full lab bibliography

2024
  1. R. A. Brown, D. E. Bernal Neira, D. Venturelli, and M. Pavone, “A Copositive Framework for Analysis of Hybrid Ising-Classical Algorithms,” SIAM Journal on Optimization, vol. 34, no. 2, pp. 1455--1489, 2024.
  2. R. Brown, “Exploring Hybrid Algorithms and Optimization Strategies in Non-Conventional Computing Architectures,” Ph.D. dissertation, Stanford University, 2024.
  3. R. A. Brown, D. Venturelli, M. Pavone, and D. E. Bernal Neira, “Accelerating Continuous Variable Coherent Ising Machines via Momentum,” Int. Conf. on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, 2024.
  4. D. E. B. Neira, R. Brown, P. Sathe, F. Wudarski, M. Pavone, E. G. Rieffel, and D. Venturelli, “Benchmarking the Operation of Quantum Heuristics and Ising Machines: Scoring Parameter Setting Strategies on Optimization Applications,” 2024. (Submitted)
  5. L. F. Valenzuela, R. Brown, and M. Pavone, “Decentralized Implicit Differentiation,” IEEE Transactions on Control of Network Systems, 2024. (Submitted)
  6. I. W. Wang, R. Brown, T. L. Patti, A. Anandkumar, M. Pavone, and S. F. Yelin, “Sum-of-Squares inspired Quantum Metaheuristic for Polynomial Optimization with the Hadamard Test and Approximate Amplitude Constraints,” 2024. (Submitted)
2022
  1. R. Brown, E. Schmerling, N. Azizan, and M. Pavone, “A Unified View of SDP-based Neural Network Verification through Completely Positive Programming,” Int. Conf. on Artificial Intelligence and Statistics, 2022.
2021
  1. R. A. Brown, F. Rossi, K. Solovey, M. Tsao, M. T. Wolf, and M. Pavone, “On Local Computation for Network-Structured Convex Optimization in Multi-Agent Systems,” IEEE Transactions on Control of Network Systems, vol. 8, no. 2, pp. 542-554, 2021.
2020
  1. R. A. Brown, F. Rossi, K. Solovey, M. T. Wolf, and M. Pavone, “Exploiting Locality and Structure for Distributed Optimization in Multi-Agent Systems,” European Control Conference, 2020.