A unique path

I'm a physician and researcher dedicated to improving patient care by bridging data science, basic biology, and emerging AI technologies. My passion for leveraging AI in healthcare drives my work, combining rigorous epidemiological and scientific methods with innovative AI solutions to address critical challenges. From clinical research design and real-world data analysis (EHR) to AI integration, my experience focuses on translating research, including my work on brain cancer, into tangible improvements in patient outcomes and experiences.

Education

PhD in Epidemiology and translational science

University of California, San Francisco & UC Berkeley

Designated emphasis in Computational Precision Health

Masters in Advanced Studies

Escuela Superior de Medicina, National Polytechnic Institute (Mexico)

Medical Surgeon and Birth attendant

Medical Doctor

University of California, San Francisco

Clinical Research Methods

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Professional experience

8 20+

Study protocols managed

Years of clinical research experience

5

Projects authored

14

Publications

4

Health AI projects

2

Book chapters co-authored

Presentations

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2017

San Francisco, CA

2019

Lyon, France

2019

Phoenix, AZ

2020

Virtual Conferences

2022

Vienna, Austria

2023

Vancouver, Canada

2022

Webinar for patients

2023

San Francisco, CA

2024

Glasgow, Scotland

I have presented my work at national and international conferences

Projects

My projects span from molecular and genetic biology, to AI implementation, to observational studies

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RAS-MAPK pathway mutations associated with inferior survival in IDH-mutant gliomas

In this project we propose RAS-MAPK pathway mutations as a potential therapeutic target for patients with IDH-diffuse astrocytomas (RAS-MAPK). The project used next-generation sequencing genetic data from sequential brain tumor tissue samples from patients with this disease.

Agent-based modeling for patient-centered clinical decision support in neuro-oncology

Empowering neuro-oncologists and patients with AI-driven insights. This project uses Large Language Models and an agentic framework to analyze real-world clinical data, enabling more informed and patient-centric clinical management decisions. The result: improved care and outcomes for patients with neuro-oncological conditions.

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Impact of cannabis use on quality of life in patients with central nervous system tumors

This project seeks to understand how cannabis and cannabis products affect patients with brain tumors. By addressing this knowledge gap, we hope to improve patient care and inform evidence-based recommendations.

A web-based exercise application for patients with brain tumors

Developing a patient-centric, web-based exercise intervention for brain tumor patients. This collaborative project leverages expertise in patient advocacy, physical training, software development, and data science to create a tailored exercise program designed to improve physical fitness and positively influence clinical outcomes.

Home Lab

Beyond my professional work, I'm a continuous learner, always exploring new ways to use technology. My projects showcase my programming and technology skills, including practical applications of Docker, Raspberry Pi, and local Large Language Models.

Go to tech projects