Jesus Alan Hernandez Galvan
Recent graduate in biomedical engineering with 6 years of hands-on research experience in multiple laboratories in Mexico and Japan. Published researcher with 4 publications in AI/ML applications for healthcare. Passionate about Brain-Computer Interfaces and Artificial Intelligence, with proven leadership skills and industry experience applying research expertise to practical solutions.
About
Biomedical Engineer with extensive research background spanning EEG signal processing, molecular property prediction, and medical AI applications. Co-authored 4 publications while leading research initiatives across international collaborations. Currently transitioning research expertise to industry, with demonstrated ability to develop scalable software solutions and lead cross-functional teams.
Education
Universidad Autónoma de Chihuahua, Facultad de Medicina y Ciencias Biomédicas
Work Experience
Safran Engineering ServicesMexicoInnovation
Innovation Engineer
Biomedical Solutions EoniaMexicoStartup
Co-founder / Technical Lead
AI & Medical Computing Lab, Universidad Autónoma de ChihuahuaMexicoResearch
Research Assistant
Computer Vision Lab, Universidad Autónoma de ChihuahuaMexicoResearch
Undergraduate Researcher
Mirai Innovation Research InstituteOsaka, JapanResearch
Undergraduate Researcher
Computational Physical Chemistry Lab, Universidad Autónoma de ChihuahuaMexicoResearch
Undergraduate Researcher
Publications
A prototypical network for few-shot recognition of speech imagery data
Biomedical Signal Processing and Control, 86 (2023)
Validación de un modelo de inteligencia artificial para la predicción de la mortalidad del paciente con sepsis
Medicina Interna de México, 40(3) (2024)
Outcome classification model for Covid-19 patients using artificial intelligence
Salud Pública de México, 65(1) (2023)
Imagined Speech Recognition in a Subject Independent Approach Using a Prototypical Network
XLV Mexican Conference on Biomedical Engineering (2022)
Projects
ScOPE Algorithm
Novel parameter-free, training-free approach for molecular property prediction that outperformed state-of-the-art AUC benchmarks on multiple datasets (BBBP, HIV, BACE, ClinTox).
EEG Speech Recognition System
Subject-independent EEG-based speech recognition system using meta-learning that reduced data requirements by 90% while maintaining robust cross-device performance.
Multi-GPU Segmentation Network
First multi-GPU computational implementation in the faculty using distributed PyTorch for medical image segmentation with automatic load balancing.
AI-Powered CV Classifier
Developed for Safran Engineering Services to streamline recruitment process using job descriptions as reference criteria and OCR-based validation systems.