My research explores the intersection of AI and healthcare, aiming to develop innovative solutions for clinical and medical challenges. Key areas of interest include:

Neurosymbolic Programming for Healthcare: Developing advanced AI models that integrate symbolic reasoning with neural networks to enhance medical diagnostics and treatment planning.

Digital Phenotyping and Mental Health: Utilizing mobile sensing and network analysis to gain insights into mental health conditions such as schizophrenia, aiming to provide personalized and effective interventions.

Healthcare Data Science: Analyzing large-scale healthcare data to uncover patterns and improve patient care through predictive analytics and personalized medicine.

Dive in to explore my background, research projects, publications, and interdisciplinary endeavors. I am always open to collaborations, speaking opportunities, and connecting with fellow researchers to exchange ideas and insights.

To learn more about my research interest, here is a perspective paper my team and I wrote, and here is a talk I gave recently summarizing it.

I am fortunate to be the project manager of the multidisciplinary NSF expeditions in computing projectUnderstanding the world through code led by Prof. Armando Solar-Lezama. Our goal is to advance artificial intelligence and programming languages research for scientific discovery.

I also lead an initiative for artificial intelligence in Latin America.

Check out the neurosymbolic programming for science seminars I have been hosting as part of our NSF expeditions in computing initiative.

I am organizing the first workshop on computational advances for scientific discovery and interpretability at MIT 2024, please join us:

Highlighted Research:

Computer Science

  1. Neurosymbolic Programming for Science (Neurips 2022)
  2. Lemma – Bootstrapping High-Level Mathematical Reasoning with Learned Symbolic Abstractions (Neurips 2022)


  1. Pattern Recognition of Deep and Superficial Layers of the Macaque Brain Using Large-Scale Local Field Potentials (MIT News) (Cognitive Computational Neuroscience)
  2. Automatic Methods for Cortex-Wide Layer Identification of Electrophysiological Signals Reveals a Cortical Motif for the Expression of Neuronal Rhythms (Cognitive Computational Neuroscience)

Mental Health

  1. Counterfactual Explanations of Clinical Alerts in Schizophrenia using Digital Phenotyping (working paper)
  2. Individual Behavioral Insights in Schizophrenia: A Network Analysis and Mobile Sensing Approach (EAI PervasiveHealth 2023)

Engineering and Computer Science

  1. Gait Analysis Applications to Healthcare and Security with Machine Learning (PhD Thesis)

Featured Projects:

Fairness in algorithmic decision-making

Mental Health

Digital healthcare

Latin America


Academic Journey: