Dr. Gilberto Ochoa-Ruiz
PhD students
Tecnologico de Monterrey (main advisor or co-advisor)
- Mansor Ali Teevno, Robust Surgical Tool Segmentation, Tracking and Depth Perception
Co-advisor: Sharib Ali, University of Leeds
- Daniel Flores Ariza, Integrating causality in the interpretability of artificial intelligence models applied to medicine [Github]
Co-advisor; Miguel Gonzalez Mondoza, Tec de Monterrey
- Francisco Javier Lopez Tiro, Automatic real-time identification of kidney stones and their composition from ureteroscopic images using deep learning and computer vision techniques [Github]
Co-advisor: Christian Daul, CRAN, Nancy
- Ricardo Abel Espinosa Loera, Endoscopic View Enhancement using Deep Learning-based 3D Reconstruction Techniques
Co-advisor: Christian Daul, CRAN, Nancy
- Pablo Cesar Ruiz, Gaussian Splatting for Deformable Surgical Scene Reconstruction and instrument tracking
Co-advisor: Nazim Houachine, Harvard Medical School, USA
- Alexis Iván López Escamilla, Deep learning for motor signal processing
Co-advisor: Christian Daul, CRAN, Nancy
CINVESTAV Guadalajara (co-advisor)
- Jorge Gonzalez Zapata, GEMINI: Guided Metric Learning
Main advisor: Andres Mendez-Vazquez, CINVESTAV
- Ivan Reyes Amezcua, [Github]
Main advisor: Andres Mendez-Vazquez, CINVESTAV
Master students
- Helena Velencia, Categorization of pre-cancerous inflammations in colonoscopic images using artificial intelligence models
- Ruben Gonzalez Perez, Generation of Realistic Endoscopic Images to Identify and Classify Kidney Stones
- Cuathemoc Alonso Guerrero Ramirez, Skill Assessment in Minimally Invasive Surgery using Computer Vision for Instance Segmentation
- Carlos
- Obed
- Eduardo Guarduño Martinez, Implementation of optimized segmentation model on edge devices for wildfire spread forecasting
- Javier Cerriteño Magaña, Real time Endoscopic image Enhancement using LMSPEC techniques with added attention blocks
- Jesus Antonio Low Castro: Crowdsensing-based Wildland-Urban Interface Fire Risk Assessment Using Artificial Inteligence and data collected from phones
- Ilse Karena de Anda Garcia, Exploring hyphesis driven decision support systems in the context of endoscopic stome recognition
Graduated students
- Elias Villalvazo Avila
Thesis Title Improved Kidney Stone Recognition Through Attention and Feature Fusion Strategies
- David Alberto Laines Vazquez
Theis Title Sign Language Recognition with Tree Structure Skeleton Images and Densely Connected CNNs n
- Pablo Cesar Quihui Rubio
Thesis Title: Automatic Detection and Segmentation of Prostate Cancer Using Deep Learning Techniques
- Rafael Martinez Garcia-Peña
Thesis title: Lights, Camera, and Domain Shift: Using Superpixels for Domain Generalization in Image Segmentation for Multimodal Endoscopies
- Daniela Herrera Montes de Oca
Thesis Title: Automatic segmentation and classification of vascular pattern symmetries on cerebral vessels using DL
Current Position: Research Engineer: Hopital d’Orleans, France
- Pedro Esteban Chavarrias Solano
Thesis Title: Automatic Categorization of Gastro-Intestinal Inflammations using Deep Learning
Current Position: Phd: University of Leeds
- Carlos Axel Garcia Vega
Thesis title: Deep Learning Lightinhg Enhancement for Endoscopic Computer Integrated Surgery
- Jorge Francisco Ciprian Sanchez
Thesis Title: Deep Learning model for early wildfire detection through the fusion of visible and infrared information Github
Current Position: Phd: Hasso Platner Institute, University of Postdam
- Carmina Perez Guerrero
Thesis Title Characterization of Jet Fire Flame Temperature Zones Using a DeepLearning-based Segmentation Approach Github
Current Position: * Research Engineer: [EugenIA]* (https://www.eugenia.tech/es/inicio/)
- Juan Carlos Angeles Ceron
Thesis Title: Attention YOLACT++: Achieving robust and real-time medicalinstrument segmentation in endoscopic procedures
Current Position: Research Engineer, Microsoft
- Mauricio Mendez Ruiz
Thesis title: Model Extensions for Semantic Segmentation using Few-Shot Learning Approach
Current Position: * Research Engineer: [EugenIA]* (https://www.eugenia.tech/es/inicio/)
- Oscar Hinojosa
Thesis title: Automated classification method for ureteroscopic kidney stone images using machine learning [Github]
Current Position: Amazon