Ph.D. in Electrical Engineering from Universidad de Chile, specialized in Image Processing and Artificial Intelligence. My research lies at the intersection of deep learning, image processing, and data science. I completed my undergraduate studies in Ecuador, earning a degree in Electronic Engineering with a specialization in Instrumentation.
I am currently a faculty member at Universidad Diego Portales.
Current Research
My current research focuses on weakly supervised learning applied to the detection of irregularities in histopathological tissue. Specifically, I work with Multiple Instance Learning (MIL) frameworks for Whole Slide Image (WSI) analysis, aiming to identify pathological patterns without requiring exhaustive pixel-level annotations.
Selected Publications
J. E. Zambrano, A. Luarte, J. Contreras, J. P. Perez, L. Yantén-Fuentes, M. Prieto, P. Lazcano, U. Wyneken and C. A. Perez, "Deep Learning-Based Differential Diagnosis of Major Depression and Bipolar Disorder Using Microglia-Cellular Sensors and Patient-Derived Small Extracellular Vesicles," in Scientific Reports, vol. 16, no. 1, p. 11679, 2026, doi: 10.1038/s41598-026-47476-9. [Details]
J. E. Zambrano, J. I. Pilataxi, C. A. Perez and K. W. Bowyer, "Iris Recognition Using an Enhanced Pre-Trained Backbone Based on Anti-Aliased CNNs," in IEEE Access, vol. 12, pp. 94570-94583, 2024, doi: 10.1109/ACCESS.2024.3425648. [Details]
J. I. Pilataxi, J. E. Zambrano, C. A. Perez and K. W. Bowyer, "Improved Search in Neuroevolution Using a Neural Architecture Classifier With the CNN Architecture Encoding as Feature Vector," in IEEE Access, vol. 12, pp. 11987-12000, 2024, doi: 10.1109/ACCESS.2024.3355804. [Details]
Doctoral stage and research
During my doctoral studies I specialized in biometric modeling using convolutional neural networks (CNNs). I have participated in the FONDECYT 1231675 and 1191610 projects, focused on facial biometrics, 3D iris modeling, and deep learning, as well as in the IMPACT Basal Project (FB210024), where I investigated the use of deep learning for biomedical image analysis, including the detection of psychiatric disorders from extracellular vesicles.
Postdoctoral stage
During my postdoctoral stage, a key contribution was my participation in the FONDEF ID24I10408 project, where I developed intelligent systems for the detection of illegal products through the multimodal integration of text and image.
Teaching and collaboration
I have teaching experience since 2019 in courses on programming, signals and systems, image processing, and artificial intelligence, and I maintain active scientific collaboration networks both nationally and internationally.
Contact
For collaborations or inquiries: jorge.zambrano@mail.udp.cl