Welcome! As a Research Scientist at MIT's CSAIL, I'm passionate about harnessing the power of neurosymbolic programming techniques to explore and deepen our understanding of the world. My interdisciplinary research spans across machine learning, programming languages, neuroscience, mental health, and personalized education. By leading various initiatives, including the NSF Expeditions in Computing project as project manager, and AI efforts in Latin America, I am dedicated to fostering scientific discovery and driving global positive impact. 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.

I am Research Scientist at the computer-aided programming research group part of the Computer Science and Artificial Intelligence Laboratory (CSAIL) at MIT.

Generally, my research aims to develop neurosymbolic programming techniques to advance our understanding of the world.

My research projects focus on machine learning, programming languages and interpretability, for digital mental health, mathematical discovery, and computational cognitive science for personalized education.

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 project:  Understanding 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.

Highlighted Research:

Computer Science

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

Neuroscience

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

Mental Health

  1. Counterfactual Explanations of Clinical Alerts in Schizophrenia using Digital Phenotyping (in press)
  2. Developing Clinical Insights into Schizophrenia at an Individual Level (n=1) using a Combination of Digital Phenotyping and Network Analysis Techniques Focusing on Variations in the Number of Recorded Daily Locations Visited (in press)

Human behavior: Gait analysis and machine learning

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

Featured projects:

Mental Health

  1. Senses and Art

Latin America

  1. Impact of Artificial Intelligence in Latin America (Book Download) | Presentation
  2. Global AI Agenda: Latin America

Education

  1. Education as a Tool for Prevention: Addressing and Countering Hate Speech

 

Academic Journey: