I am a CI Fellow and postdoctoral researcher in the Booth School of Business at the University of Chicago and in the Machine Learning Department at Carnegie Mellon University. I am fortunate to be co-mentored by Bryon Aragam and Pradeep Ravikumar.

I am broadly interested in Artificial Intelligence and Machine Learning. My research focuses on developing principled algorithms that are computationally and statistically efficient for various machine learning problems. Current interests include structure learning (a.k.a., causal discovery), and learning invariant/causal representations. Also, I have recently worked in structured prediction, studying efficient learning with latent variables (NeurIPS’18), minimax bounds (AISTATS’20), and exact inference (NeurIPS’19, NeurIPS’20).

Previously, I received my PhD in Computer Science from Purdue University, where I was advised by Jean Honorio. Before my PhD, I received a BSc in Mechatronics Engineering from the National University of Engineering in Lima, Peru.


09/22: Our paper “DAGMA: Learning DAGs via M-matrices and a Log-Determinant Acyclicity Characterization” has been accepted to NeurIPS!
09/22: Will be presenting about DAGMA at the Bay Area Machine Learning Symposium (BayLearn) on Oct. 20!
05/22: One paper accepted to ISIT.
01/22: One paper accepted to AISTATS.
09/21: Started a joint postdoc at UChicago and CMU. I’ll be working on projects that focus on causal discovery and learning invariant/causal representations.
09/21: One paper accepted to NeurIPS.
06/21: Excited to have been awarded the Computing Innovation Fellowship!
04/21: One paper accepted to ISIT.
04/21: Talk at Pradeep Ravikumar’s lab at CMU on April 15.
04/21: Talk at MIT CSAIL (event) on April 14.
04/21: Talk at Tomaso Poggio’s lab at MIT CBMM on April 5.
03/21: Honored to have been awarded the Bilsland Dissertation Fellowship at Purdue!
01/21: Talk at Peru’s 3rd Symposium of Deep Learning on Jan 29.
09/20: Talk at TECHSUYO’20 on October 29.
09/20: One paper accepted to NeurIPS.
05/20: Summer internship at Facebook AI.
01/20: One paper accepted to AISTATS.
09/19: One paper accepted to NeurIPS.
05/19: Summer internship at Facebook Ads Ranking team.
09/18: Two papers accepted to NeurIPS.

Academic Service

  • Chair of LatinX AI Workshop at ICML 2020.
  • Conferences (reviewer): ICLR 2023, NeurIPS 2022, ICML 2022, ICLR 2022, AAAI 2022, NeurIPS 2021, ICML 2021, AISTATS 2021, ICLR 2021, NeurIPS 2020, IJCAI 2020, NeurIPS 2019.
  • Journals (reviewer):
    • Journal of Machine Learning Research (JMLR).
    • IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI).
    • Transactions on Machine Learning Research (TMLR).
    • Journal of Computational and Graphical Statistics (JCGS).