I'm an Applied Scientist at Amazon working on bad actor detection using machine learning. I received my PhD in computer science at the University of Colorado Boulder in the summer of 2022, where I was fortunate to be advised by Rafael Frongillo and Joshua Grochow. Before my PhD, I completed an MS in applied math at UMass Amherst.

__Research Buzzwords__:

Online Optimization, Algorithmic Economics, Game Theory, Dynamical Systems, Complex Networks, and Multi-Agent Learning

- No-Regret Learning in Games is Turing Complete, G. P. Andrade, R. Frongillo, and G. Piliouras. (arXiv:2202.11871)
- Learning in Matrix Games Can Be Arbitrarily Complex, G. P. Andrade, R. Frongillo, and G. Piliouras. In Proceedings of the 34th Annual Conference on Learning Theory (COLT 2021)
- Graphical Economies with Resale, G. P. Andrade, R. Frongillo, E. Gorokhovsky, and S. Srinivasan. In Proceedings of the 21st ACM Conference on Economics and Computation (ACM EC 2021)
- Graph Models of Neurodynamics to Support Oscillatory Associative Memories, G. P. Andrade, M. Ruszinkó, and R. Kozma. In Proceedings of the 2018 International Joint Conference on Neural Networks (IJCNN 2018)

- Math Systems for Diagnosis and Treatment of Breast Cancer, C. Amorin, G. P. Andrade, S. Castro-Pearson, A. K. Geraldo, B. Iles, D. Katsaros, T. Mullen, S. Nguyen, O. Spiro, and M. Sych. In UMass Amherst Department of Mathematics & Statistics Newsletter (2017)
- A Matroid Generalization of Sperner's Lemma, G. P. Andrade, A. R. Rey, A. J. R. Sandoval, M. Sondjaja, and F. Su. (2015)