I am a Postdoctoral Scholar in the Department of Computing and Mathematical Sciences at Caltech, hosted by Professor Yisong Yue. I recently obtained my Ph.D. in Operations Research and Information Engineering from Cornell University, where I was fortunate to work under the supervision of Professor Peter Frazier. Before that, I completed the undergraduate program in Mathematics offered jointly by the University of Guanajuato and the Center for Research in Mathematics. In 2021, I was a Visiting Researcher at Meta within the Adaptive Experimentation team led by Eytan Bakshy.

My research interests lie at the intersection between operations research and machine learning, with an emphasis on Bayesian methods for efficient sequential data collection. My work combines principled decision-theoretic foundations with sophisticated machine learning tools to develop frameworks for adaptive experimentation in robotics, materials design, cellular agriculture, among other scientific applications.

- Bayesian Optimization
- Preference Elicitation
- Adaptive Experimentation
- Simulation Optimization
- Optimal Learning
- Bayesian Machine Learning

Ph.D., Operations Research and Information Engineering, 2022

Cornell University

B.S., Mathematics, 2016

University of Guanajuato & Center for Research in Mathematics (Mexico)

Thinking Inside the Box: A Tutorial on Grey-Box Bayesian Optimization.
*Proceedings of the 2021 Winter Simulation Conference*.

(2021).
Multi-Step Budgeted Bayesian Optimization with Unknown Evaluation Costs.
*Advances in Neural Information Processing Systems*.

(2021).
Bayesian Optimization of Function Networks.
*Advances in Neural Information Processing Systems*.

(2021).
(2020).
Multi-Attribute Bayesian Optimization With Interactive Preference Learning.
*Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics*.

(2020).