I am a Research Scientist at Soroco, working on foundation models for interaction data. Previously, I was a 2021 Computing Innovation Fellow and postdoctoral researcher jointly at MLD@CMU and Chicago Booth, where I worked with Bryon Aragam and Pradeep Ravikumar.

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

I serve as Production Editor of the Journal of Machine Learning Research (JMLR), the flagship journal for the field of machine learning. For JMLR related inquiries please reach out to bello@jmlr.org.

Research

My research goal is to develop next-generation ML systems that will tackle some of the current major challenges, such as robustness, interpretability, and fairness. These systems necessitate a shift from standard statistical models that are susceptible to capture undesired nonlinear correlations to ones that can potentially discover (causal) relations from multimodal, complex data.

Topics of interest:

  • Causal machine learning: Structure learning, invariant/causal representations
  • Generative models: Probabilistic models, latent variable modeling
  • Statistical learning: Structured prediction, sample complexity, exact inference

News

Service

Leadership

  • Production Editor Journal of Machine Learning Research (JMLR)
  • Mentor Data Science Institute Summer Lab, UChicago (2023)
  • Web Chair LatinX AI Workshop at ICML 2020

Conference Reviews

NeurIPS (2019--2024)
ICML (2021--2025)
ICLR (2021--2025)
CLeaR (2024--2025)
AISTATS (2021, 2025)
UAI (2025)
AAAI (2022)
LATIN Symposium (2022)
IJCAI (2020)

Journal Reviews

  • Journal of Machine Learning Research (JMLR)
  • IEEE Trans. Pattern Analysis and Machine Intelligence (TPAMI)
  • Transactions on Machine Learning Research (TMLR)
  • Annals of Applied Statistics (AOAS)
  • Journal of the Royal Statistical Society: Series B (JRSSSB)
  • Journal of Computational and Graphical Statistics (JCGS)